The Oxford Handbook of Banking [3 ed.] 0198824637, 9780198824633

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t h e ox f o r d h a n d b o o k o f

BA N K I NG

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THE Oxford Handbook of

BANKING Third Edition Edited by

ALLEN N. BERGER, PHILIP MOLYNEUX, and

JOHN O.S. WILSON

1

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1 Great Clarendon Street, Oxford, ox2 6dp, United Kingdom Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and in certain other countries © Oxford University Press 2019 Chapter 17 illustrations © Federal Reserve Bank of New York The moral rights of the authors have been asserted First Edition published in 2010 Second Edition published in 2015 Third Edition published in 2019 Impression: 1 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by licence or under terms agreed with the appropriate reprographics rights organization. Enquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above You must not circulate this work in any other form and you must impose this same condition on any acquirer Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America British Library Cataloguing in Publication Data Data available Library of Congress Control Number: 2019933028 ISBN 978–0–19–882463–3 Printed and bound by CPI Group (UK) Ltd, Croydon, cr0 4yy Links to third party websites are provided by Oxford in good faith and for information only. Oxford disclaims any responsibility for the materials contained in any third party website referenced in this work.

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For Mindy (Allen N. Berger) For Delyth, Alun, Gareth, Gethin, Catrin, Lois, and Rhiannon (Philip Molyneux) In memory of my mother, Jean Wilson (John O.S. Wilson)

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Preface

Ten years on from the Global Financial Crisis, banks are still adapting to new, more ­constrained operating and regulatory environments. Banks now hold more capital and liquidity than they did prior to the crisis, and have had regulatory limits placed upon riskier activities. Large banks have reduced their international activities in order to focus on domestic and select overseas markets. In the US, Europe, and elsewhere banks are now subject to: new capital, liquidity, and tax regulations; resolution regimes; stress tests; bail-in mechanisms; corporate governance; executive compensation and disclosure rules; along with enhanced supervisory oversight, particularly for the thirty globally systemically important banks, the G-SIBs. FinTech developments are creating opportunities for both incumbent banks and new competitors in a diverse array of areas ranging from online banking, robo advisory services and distributed ledger technology (Blockchain) to marketplace or peer-to-peer lending platforms, as well as InsureTech and RegTech. There are now over 2,000 cryptocurrencies in existence, the most well known being Bitcoin with a 54 percent share of the total cryptocurrency market capitalization. These developments present banks with competitive challenges from the entry of technology firms and opportunities to redesign business models, offer new services, and improve efficiency. For example, legacy systems are likely to be gradually replaced with more technology-based systems using distributed-ledger technology and Blockchain. The more competitive environment and stricter regulation have affected bank profits. Banks have to spend more on regulatory compliance and organizational restructuring. As of this writing, many large European banks are generating single digit returns that often do not cover their cost of capital, leading to a destruction of shareholder value. The sluggish performance of the European economy following the European Sovereign Debt Crisis presents further challenges. The Eurozone set its plans out to create a European Banking Union in 2012 in order to establish a more robust framework for dealing with troubled banks, although parts of the new regime (including a Euro-wide deposit insurance scheme) are yet to be fully implemented. Many of the aforementioned pressures continue to have similar influences on banking business globally. The slowdown in economic growth, the low (and in some cases negative) interest rate environment, coupled with regulatory measures designed to improve safety and soundness have generally acted as a drag on bank performance. Markets remain volatile and both banks and regulators continue to grapple with the complexities of measuring and managing a host of systemic as well as bank-level risks. Of particular recent interest has been the accounting treatment of credit risk indicators

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viii   preface such as loan loss provisions and reserves and the fair valuation of financial instruments, as well as issues related to the transparency of off-balance-sheet activities. Uncertainty continues to heighten. Trade wars, Brexit, Euro area challenges (such as Italian indebtedness), the possible end of the bull run in equity markets, the slowdown in emerging markets (China in particular), political polarization (both domestic and international), Middle East tensions, and other factors all add to uncertainty and a less favorable global operating environment for banks. This Third Edition seeks to evaluate many of the aforementioned areas and is a ­substantial update on the Second Edition. There are new chapters on community and mutual banking; Islamic banking; microfinance; modern central banking; bank bail-ins and bailouts; deposit insurance; bank capital; financial literacy and consumer protection; and banking in China, and Australia and New Zealand. Developments in FinTech are discussed in the chapters on small business lending, payments, and financial innovation. General themes relating to the impact of the new regulatory environment and the impact of banks on the real economy are also substantially covered in specific chapters, as well as significant updates to the other topics covered in the Second Edition. Allen N. Berger Philip Molyneux and John O.S. Wilson

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Acknowledgements

First, and most important, we wish to thank the contributors to the Handbook. We are delighted to have brought together such an outstanding set of research experts from academic and policy arenas across Europe, North America, South America, Asia, and Australasia. These experts have shown a high level of commitment and perseverance to the project from beginning to end. Without their expertise, dedication, and efficiency in producing scholarly banking chapters this Handbook would never have been possible. The production of this Handbook has also relied heavily on the exceptional enthusiasm and commitment of Oxford University Press, most notably Adam Swallow, publisher for Economics and Finance, who was crucial in helping us kick-start the project. Oxford University Press delegates and a number of anonymous referees also played an important role in advising on the shape of the Handbook. We would like to thank and acknowledge Verity Rimmer and also Katie Bishop, whose advice was invaluable and who was always on hand to help and worked closely with us throughout the entire process. The team in New York also played a valuable role, and so we’d like to thank Viviana Lachmund and Laura Heston. Manikandan Chandrasekaran and Jen Hinchliffe also played a crucial role toward the end of the project. We would also like to acknowledge the support of our home institutions: the Moore School of Business at the University of South Carolina; the College of Business Administration at the University of Sharjah; and the Centre for Responsible Banking & Finance at the Management School, University of St Andrews. We would especially like to thank Dorothy Campbell who provided excellent assistance in preparing the final manuscript prior to submission. During the writing of this Handbook, Fernando José Cardim de Carvalho, Emeritus Professor at UFRJ (Federal University of Rio de Janeiro, Brazil) and Senior Fellow at the Levy Economics Institute, Bard College in New York passed away on the 16th of May, 2018. He was 64 years old. Fernando was one of Brazil’s most revered economists. A leader of the post-Keynesian economists in Brazil, he was an associate editor of the Journal of Post Keynesian Economics. Among his many published works, he authored Mr Keynes and the Post Keynesians (Edward Elgar, 1992), and Liquidity Preference and Monetary Economics (Routledge, 2015). Fernando was an active and leading voice in ­discussions about money and financial systems and was writing until the time of his passing. Fernando wrote the excellent section on Latin American Development Banks: Some New Developments or an Impasse? in Chapter 37 of this Handbook, Banking in Latin America: Developments and Prospects. As always, Fernando provided valuable

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x   acknowledgements insights, expert analysis, and perfect context, which is indicative of his great intellect and contribution to knowledge. Finally, we would like to thank our families and friends for their encouragement and patience over the last decade while completing the three editions of the Handbook. Their support is always very much appreciated.

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Contents

List of Figuresxv List of Tablesxix List of Abbreviationsxxiii List of Contributorsxxxi

1. Banking: A Decade on from the Global Financial Crisis

1

Allen N. Berger, Philip Molyneux, and John O. S. Wilson

PA RT I   T H E T H E ORY OF BA N K I N G 2. The Roles of Banks in Financial Systems

39

Franklin Allen, Elena Carletti, and Xian Gu

3. Commercial Banking and Shadow Banking: The Accelerating Integration of Banks and Markets and its Implications for Regulation

62

Arnoud W. A. Boot and Anjan V. Thakor

4. Corporate Complexity and Systemic Risk: A Progress Report

95

Jacopo Carmassi and Richard J. Herring

5. Corporate Governance and Culture in Banking

131

Jens Hagendorff

6. Private Information and Risk Management in Banking

153

Linda Allen and Anthony Saunders

7. Creation and Regulation of Bank Liquidity

181

Christa H. S. Bouwman

PA RT I I   AC T I V I T I E S A N D P E R F OR M A N C E 8. The Performance of Financial Institutions: Modeling, Evidence, and some Policy Implications Joseph P. Hughes and Loretta J. Mester

229

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xii   contents

9. Technological Change and Financial Innovation in Banking: Some Implications for FinTech

262

W. Scott Frame, Larry Wall, and Lawrence J. White

1 0. Payments

285

David Humphrey

11. Community Banking Institutions: Commercial Banks, Savings Banks, Cooperative Banks, and Credit Unions

321

Dasol Kim and Donal McKillop

12. Islamic Banking: A Review of the Empirical Literature and Future Research Directions

359

Narjess Boubakri, Ruiyuan (Ryan) Chen, Omrane Guedhami, and Xinming Li

13. Can We Improve the Impact of Microfinance? A Survey of the Recent Literature and Potential Avenues for Success

404

Robert Lensink and Erwin Bulte

14. Small Business Lending: The Roles of Technology and Regulation from Pre-crisis to Crisis to Recovery

431

Allen N. Berger and Lamont K. Black

15. Residential Mortgages

470

Andreas Lehnert and Alex Martin

16. Securitization

503

Barbara Casu and Anna Sarkisyan

17. Shadow Banking

530

Tobias Adrian, Adam B. Ashcraft, Peter Breuer, and Nicola Cetorelli

PA RT I I I   R E G U L ATORY A N D P OL IC Y P E R SP E C T I V E S 18. Modern Central Banking

573

Frederic S. Mishkin

19. Lender of Last Resort: A New Role for the Old Instrument Xavier Freixas and Bruno M. Parigi

602

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contents   xiii

20. Bank Bailouts and Bail-Ins

630

Raluca A. Roman

21. Bank Runs and Moral Hazard: A Review of Deposit Insurance

685

Deniz Anginer and Asli Demirgüç-Kunt

22. Bank Capital Requirements after the Financial Crisis

707

Mark E. Van Der Weide and Jeffery Y. Zhang

23. Market Discipline in Regulation: Pre and Post Crisis

736

Mark J. Flannery and Robert R. Bliss

24. Competition in the Banking Sector

776

Hans Degryse, Paola Morales-Acevedo, and Steven Ongena

25. Behavioral Economics, Financial Literacy, and Consumers’ Financial Decisions814 Gregory Elliehausen

PA RT I V   M AC ROE C ON OM IC P E R SP E C T I V E S 26. Systemic Risk in Banking after the Great Financial Crisis

847

Olivier de Bandt and Philipp Hartmann

27. Hardy Perennials: Banking Crises Around the World

885

Gerard Caprio Jr. and Patrick Honohan

28. Bank Failures, The Great Depression, and Other “Contagious” Events

910

Charles W. Calomiris

29. Banking Globalization: Cross-border Entry, Complexity, and Systemic Risk

928

Claudia M. Buch and Gayle L. DeLong

30. Banking and Real Economic Activity: Foregone Conclusions and Open Challenges Nicola Cetorelli and Michael Blank

953

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xiv   contents

PA RT V   BA N K I N G SYS T E M S A RO U N D T H E WOR L D 31. Banking in the United States

977

Robert DeYoung

32. Banking in Europe: Integration, Reform, and the Road to a Banking Union1000 John Goddard, Philip Molyneux, and John O.S. Wilson

33. Banking in Japan: A Post-global Financial Crisis Perspective

1033

Hirofumi Uchida and Gregory F. Udell

34. Banking in Africa

1076

Thorsten Beck, Robert Cull, and Patricio Valenzuela

35. Banking in China

1113

Leora Klapper, María Soledad Martínez Pería, and Bilal Zia

36. Banking in the Transition Countries of Central, Southern, and Eastern Europe and the Former Soviet Union

1132

Zuzana Fungáčová, Iftekhar Hasan, Laura Solanko, and Paul Wachtel

37. Banking in Latin America: Developments and Prospects

1152

Fernando J. Cardim de Carvalho, Luiz Fernando de Paula, and Jonathan Williams

38. Banking in Australia and New Zealand—Geographic Proximity, Market Concentration, and Banking Integration

1190

Fariborz Moshirian and Eliza Wu

Index

1215

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List of Figures

2.1 Size of the Financial Markets by Country/Region 2001 and 2016, Percentage of GDP

40

2.2 Portfolio Allocation of Households and Non-financial Corporations (Average 1997–2016), Percentage of GDP

41

5.1 Firm Leverage [Liabilities/(Liabilities+Equity)], 2007

135

5.2 A Typical Cash Bonus Function

137

7.1 Total Reserves, Required Reserves, and Vault Cash Over Time

192

7.2 Capital Ratios Over Time (1934–2017)

194

7.3 Traditional Banking vs. Securitization in the Shadow Banking System

199

7.4 Comparison of Basel II and Basel III Capital Requirements

203

8.1 Scale-Related Diversification and Risk-Return Frontiers

232

11.1 Number of US Banks by Institution Type

342

11.2 Mergers & Acquisitions by Institution Type

345

11.3 Bank Entry and Exit Rates by Institution Type

347

12.1 Shares of Global Islamic Banking Assets (1H2017)

362

12.2 Number of Islamic Banks Reporting to Bankscope

363

12.3 Islamic Banks’ Total Assets (million $)

363

12.4 Share of Islamic Banks’ Assets in Total Banking Sector Assets (%)

364

12.5 Share of Islamic Banks’ Assets in Total Banking Sector by Country (1H2016)364 12.6 World Islamic Population 1990, 2010, and 2030 (millions)

365

13.1 Microfinance Services Classified by Objective and Delivery Mode

422

15.1 Credit Scores at Mortgage Origination

473

15.2 Total US Mortgage Foreclosure Starts

474

15.3 US House Price and Mortgage Debt Growth

478

15.4 US Mortgage Rates

479

15.5 Refinancing Incentive and Refinancing Volume

485

15.6 Issuance of US Mortgage-Backed Securities

486

15.7 Holders of US Residential Mortgage Debt

487

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xvi   list of figures 15.8 Primary-Secondary Mortgage Market Spread

488

15.9 US Subprime Mortgage Delinquency Rates

489

15.10 US Household Assets

492

15.11 European House Price Indices

493

16.1 US Securitization Outstanding

506

16.2 European Securitization Outstanding

510

16.3 European Securitization Issuance by Country (2017)

510

16.4 Securitization Transaction (Simplified)

512

16.5 Credit Enhancements

517

17.1 Share of Assets of Non-bank Financial Intermediaries

533

17.2 Average Annual Growth Rate of OFI Sector 2011–15 and 2016

534

17.3 The Credit Intermediation Chain

536

17.4 Composition of Liabilities of Financial Business

538

17.5 US Money Market Fund Assets

551

17.6 “Riskier” US Residential Mortgage-Backed Securities

553

17.7 US Mortgage-Backed Securities: Agency vs. Non-Agency

555

17.8 Non-bank Credit Intermediation in China

556

17.9 Depository Institution Claims on Other Financial Institutions in China

557

17.10 US Leveraged Loans: Outstanding Volume and Spreads

559

17.11 US Leveraged Loans: Issuance of Lowly Rated Debt (B-Rated or Lower)560 17.12 US Leveraged Loans: Average Debt Multiples

560

19.1 Central Banks’ Total Assets

618

19.2 Central Banks’ Key Intervention Rates

619

20.1 TARP Capital Injections to Banks

636

21.1 Number of Countries with Explicit Deposit Insurance

689

21.2 Percentage of Countries with Explicit Deposit Insurance

690

21.3 Percentage of Bank Liabilities Covered by Deposit Insurance

691

21.4 Percentage of Countries that have Increased Coverage as a Result of the Financial Crisis

692

21.5 Percentage of Countries that Charge Risk-adjusted Premiums

700

22.1 US Bank Capital Ratio, 1834–2014

713

22.2 Increase in the Quantity of Capital (Tier 1 Ratio of G-SIBs)

730

22.3 Increase in the Quantity of Capital (Leverage Ratio of G-SIBs)

730

22.4 Increase in the Quality of Capital (Time Series)

731

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list of figures   xvii 22.5 Increase in the Quality of Capital (Cross Sections)

731

22.6 Changes in the Distribution of Capital

732

29.1 Bank Acquisitions (by Year) 1985–2017

930

29.2 Percentage of Bank Acquisitions that Are Cross-Border (by Year) 1985–2017931 29.3 Bank Acquisitions (by Region and Year) 1985–2017

933

29.4 Percentage of Cross-Border Bank Acquisitions (by Region and Year) 1985–2017934 31.1 Number of Commercial Banks and Commercial Bank Branch Offices in the US between 1940 and 2017

982

31.2 Aggregate Return-on-Equity and Equity-to-Assets Ratios for the US Commercial Banking Industry, 1934 to 2017

984

31.3 Merged Banks, Newly Chartered Banks, and Failed Banks, Expressed as a Percentage of the US Commercial Bank Population, each Year from 1970 to 2017

985

31.4 Strategic Map of the Banking Industry

988

31.5 The Changing Distribution of US Commercial Banks by Asset Size (in 2009 dollars) between 1980 and 2017

992

31.6 Commercial Banks, Savings Banks, and Credit Unions in the US in 2017

993

32.1 Price-based and Quantity-based Financial Integration Composite Indicators1007 33.1 Composition of Financial Assets in Japan by Holder

1040

33.2 Loans Outstanding of Private Banks

1041

33.3 Profits and Losses for Ordinary Banks

1064

33.4 Diffusion Index for Lending Attitude of Financial Institutions

1065

34.1 Aggregate Financial Development in International Comparison, 2015

1080

34.2 Private Credit to GDP across Low- and Lower-middle-income African Countries, 2015

1081

34.3 Private Credit to GDP (%)

1081

34.4 Access to and use of Financial Services in International Comparison, 2010–171082 34.5 Short-term Loans as Percentage of Total Loans

1084

34.6 Private Credit/GDP (%) in African Countries 2011–15, Actual vs. Predicted Values

1085

34.7 Use of Formal Account and Loan Services across Firm Size Groups in International Comparison, 2013–17

1090

34.8 Account Penetration across Regions, 2011, 2014, and 2017

1092

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xviii   list of figures 34.9 Gaps in Account Penetration in Sub-Saharan Africa

1094

34.10 Gaps in Mobile Money Account Penetration in Sub-Saharan Africa

1095

35.1 Chinese Financial Sector Assets Over Time

1114

35.2 Financial Sector Size across Countries in US dollars as of 2016

1114

35.3 Credit-to-GDP Gap for China and Other Countries

1115

35.4 Evolution of Financial Institutions in Asset Share

1116

35.5 The Rise of Shadow Banking

1119

35.6 Wealth Management Products, 2007–17

1119

35.7 Barriers to Account Ownership (% of Adults with No Account)

1128

38.1 Asset Composition of Banks in Australia, NZ, and Globally

1198

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List of Tables

4.1 Size and Complexity of G-SIBs, 2018 vs. 2013 (G-SIBs Ranked by Total Assets 2017)

101

4.2 Geographical Diversification of G-SIBs and Subsidiaries in OFCs, 2018 vs. 2013 (G-SIBs Ranked by Number of Countries in 2018)

105

4.3 Breakdown by Industry of Subsidiaries of G-SIBs, October 2018 (in bold) and May 2013

107

4.4 Number of Subsidiaries of US G-SIBs According to the FED/NIC Data Set, 2002–18

112

4.5 Public Sections of Resolution Plans of the 8 US G-SIBs (July 2017): Key Selected Information

126

6.1 List of G-SIBs, November 2017

176

7.1 Countercyclical Capital Buffers

204

7.2 G-SIB Surcharges

206

10.1 Payment Instrument Use, 2016

289

11.1 Cooperative Banks and National Associations for Cooperative Banks

330

11.2 Institution-Type Composition by Size Category

343

12.1 Differences between Islamic and Conventional Banking Systems

367

12.2 Summary of Major Sharia-Compliant Financial Contracts

368

12.3 Stylized Balance Sheet of a Conventional Bank

370

12.4 Stylized Balance Sheet of an Islamic Bank

371

12.5 Comparing Islamic and Conventional Banks

373

12.6 Comparing Islamic and Conventional Banks—Controlling for Bank Characteristics374 12.7 Comparing Islamic and Conventional Banks During Crises

378

12.8 The Effects of Islamic Banks on Bank Liquidity Creation

384

12.9 Islamic Bank and Stock Illiquidity

385

13.1 Impact of Business Training on Business Outcomes

423

16.1 US Securitization Issuance

508

17.1 A Stylized View of the Structural Characteristics of Credit Intermediation541

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xx   list of tables 19.1 LOLR Actions by the FED in the 2007–9 Crisis

621

22.1 Balance Sheet

708

22.2 Minimum Requirements Under Basel II and Basel III

717

22.3 Basel I Risk Weights

718

22.4 Risk Weights Under Basel II

719

22.5 Capital Conservation Buffer (CCB)

721

22.6 Historical CCyB Add-ons

723

22.7 Summary of Capital Buffers

723

22.8 G-SIBs in 2017

724

22.9 Basel III (Method 1) G-SIB Capital Surcharges

725

22.10 Method 1 vs. Method 2 (2016)

725

22.11 Comparison of Leverage Ratios, 2017:Q4

727

23.1 Prescriptive Information Disclosure, Pillar 3 in Basel III

759

23.A1 Percentage of Actual/Fitted, “Negative”/“Positive” Observations

765

24.1 Evolution of Research on the Impact of Bank Concentration and Competition on Bank Performance

779

29.1 Cross-Border Bank Acquisitions by Geographic Region, 1985–2017

932

31.1 Distribution of Financial Assets in the US Across Private Sector Financial Intermediaries in 1980 and 2017

978

31.2 Comparing the Average Values of Selected Financial Ratios between 434 Small and 56 Large US Commercial Banks in 2017

990

31.3 Largest US Banking Companies as of December 31, 2017 by Total Assets ($ billions)

994

31.4 Global Investment Banking Revenue in 2017

994

32.1 Number of Credit Institutions and Foreign Branches

1008

32.2 Total Assets of Domestic Banking Groups and Foreign-Controlled Subsidiaries and Branches

1009

32.3 Concentration in European Banking Herfindahl index for credit institutions and share of total assets of the five largest credit institutions1010 32.4 Bank Profitability—Return on Equity (%)

1015

33.1 Financial Assets in Japan by Holder

1035

33.2 Assets and Liabilities of the Japanese Corporate, Government, and Household Sectors

1037

33.3 Descriptive Statistics for Different Bank Types in Japan

1042

33.4 Four Main Types of Bank in Japan

1049

34.1 Decomposition of Interest Rate Spreads in Uganda in 2008

1087

34.2 Explaining Overhead Costs in Africa

1088

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list of tables   xxi 34.3 Account Penetration over Time and across Countries

1093

34.4 Mobile Phone use in Financial Transactions in Africa by Country, 2017

1102

35.1 Bank Performance Across Countries, 2016

1117

36.1 Deposit Money Banks’ Assets to GDP (%), Average for the Region

1144

36.2 Balance-Sheet Structure of Banking Sectors at end 2016

1146

37.1 Market Concentration and Foreign Bank Penetration

1156

37.2 Financial Depth and Credit Indicators

1165

37.3 Interest Rates, %

1167

37.4 Margins, Diversification, Liquidity, and Profitability, %

1168

37.5 Bank Capital, Stability, Profitability, and Leverage

1174

37.6 Cost Structure and Efficiency

1175

37.7 Bank Solvency and Asset Quality

1181

38.1 Size and Importance of the Financial Services Industry in Australia and New Zealand

1192

38.2 Overall Industry Concentration and Sectoral Concentration

1193

38.3 Bank Funding Sources in Australia and New Zealand, and Globally

1196

38.4 Sector Concentration by Bank Type in Australia and Loan Type in all Australian and New Zealand Banks

1199

38.5 Cost-to-Income Ratios

1202

38.6 Profitability

1203

38.7 Capital Requirements

1207

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List of Abbreviations

AAOIFI ABCP ABL ABS ABSPP ACH ADIs AIG A-IRB AMA AMC AMLF APP APRA AQR ARM ASF ASIC ATM BCBS BCCI BEEPS BHC BIS B/M ratio BoJ BOJ-NET BOLR BOPEC BRRD BRSS C&I CAMELS

Accounting and Auditing Organization for Islamic Financial Institutions asset-backed commercial paper asset-based lending asset-backed securities asset-backed securities purchase program Automated Clearing House Authorised Deposit-taking Institutions American International Group advanced internal ratings-based approach advanced measurement approach asset management company Asset-Backed Commercial Paper Money Market Mutual Fund Liquidity Facility asset purchase program Australian Prudential Regulation Authority asset quality review adjustable rate mortgage available stable funding Australian Securities and Investments Commission automated teller machine Basel Committee on Banking Supervision Bank Credit and Commerce International Business Environment and Enterprise Performance Survey bank holding company Bank for International Settlements book-to-market ratio Bank of Japan Japan’s Real Time Gross Settlement Network buyer of last resort Summary performance ratings assigned to US bank holding companies over the period 1987 to 2004 Bank Recovery and Resolution Directive Bank Regulation and Supervision Survey commercial and industrial Capital, Assets, Management, Earnings, Liquidity, and Sensitivity

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xxiv   list of abbreviations CAPM CAR CATFIN CB CBC CBOT CBPP CCAR CCB CCyB CDCI CDO CDS CEE CFPB CET1 CGFS CHAPS Check 21 CHIPS CISS CLS Bank CLTV CMBS CME CMO CNAV CoCos CoVaR CP CPFF CPP CR3 CR5 CRA CRD CRE CS CSPP CSR CVA DEA

capital asset pricing model cumulative abnormal return early warning systemic risk indicator central bank commercial bank clearinghouse Chicago Board of Trade covered bond purchase program Comprehensive Capital Analysis and Review capital conservation buffer countercyclical capital buffer Community Development Capital Initiative collateralized debt obligation credit default swap Central and Eastern Europe Consumer Financial Protection Bureau Common Equity Tier 1 Committee on the Global Financial System UK’s RTGS network Electronic processing/collection of paper checks in the US A US bank-operated large-value payment network Composite Indicator of Systemic Stress A Continuous Linked Settlement bank handling foreign exchange transactions combined loan-to-value ratio commercial mortgage-backed security Chicago Mercantile Exchange collateralized mortgage obligation constant net asset value Contingent Convertible Bonds Conditional Value at Risk commercial paper Commercial Paper Funding Facility Capital Purchase Program three-bank concentration ratio five-bank concentration ratio credit rating agency Capital Requirements Directive commercial real estate credit spread corporate sector purchase program corporate social responsibility credit valuation adjustment data envelopment analysis

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list of abbreviations   xxv DFA Dodd–Frank Act Dodd–Frank Act Stress Test DFAST DIC Deposit Insurance Company Depository Institutions Deregulation and Monetary Control Act DIDMCA Democratic Republic of Congo DRC DSGE dynamic stochastic general equilibrium D-SIBs domestically systemically important banks DSTI debt-service-to-income debt-to-income ratio DTI delivery versus payment DVP DW discount window exposure at default EAD European Banking Authority EBA earnings before interest, tax, depreciation, and amortization EBITDA European Bank for Reconstruction and Development EBRD European Commission EC European Central Bank ECB EU Council of Finance ECOFIN European Deposit Insurance Scheme EDIS European Economic Community EEC Emergency Economic Stabilization Act EESA European Financial Stability Facility EFSF electronic funds transfer at point of sale EFTPOS European Investment Bank EIB European Insurance and Occupational Pensions Authority EIOPA emergency liquidity assistance ELA EM emerging market Economic and Monetary Union EMU expected shortfall ES enhanced supplementary leverage ratio eSLR European Systemic Risk Board ESRB European Systemic Risk Council ESRC European Union EU A European bank-operated large-value payment network Euro 1 extreme-value theory EVT Financial Access Survey FAS FASB Financial Accounting Standards Board foreign direct investment FDI Federal Deposit Insurance Corporation FDIC US Federal Reserve FED US’s RTGS network Fedwire FHA Federal Housing Administration Federal Housing Finance Agency FHFA

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xxvi   list of abbreviations FHLB FHLMC FICO FILP FINDEX FinTech F-IRB FNMA FRB FSA FSAP FSB FSIs FSOC FSRRA FSU FX G20 GAAP GCC GFC GDP GIIPS Giro GLB GNMA GSE G-SIBs G-SIFIs HAMP HARP HHI HMDA HQLA ICOs IDB IFIs IFRS IFSB IFSI IIFM IMF InsurTech

Federal Home Loan Bank Federal Home Loan Mortgage Corporation (also Freddie Mac) Fair Isaac and Company Fiscal Investment Loan Program Global Financial Inclusion Database financial technologies foundation internal ratings-based approach Federal National Mortgage Association (also Fannie Mae) Federal Reserve Bank Financial Services Agency Financial Sector Assessment Programs Financial Stability Board financial system inquiries Financial Stability Oversight Council Financial Services Regulatory Relief Act Former Soviet Union foreign exchange Group of 20 Heads of State Generally Accepted Accounting Principles Gulf Cooperation Council Global Financial Crisis or Great Financial Crisis Gross Domestic Product Greece, Italy, Ireland, Portugal and Spain European credit transfer network Gramm–Leach–Bliley Act Government National Mortgage Association (also Ginnie Mae) government-sponsored enterprise Global Systemically Important Banks Global Systemically Important Financial Institutions Home Affordable Modification Program Home Affordable Refinance Program Herfindahl–Hirschman Index Home Mortgage Disclosure Act high-quality liquid assets initial coin offerings Islamic Development Bank international financial institutions International Financial Reporting Standards Islamic Financial Services Board Islamic Financial Services Industry International Islamic Financial Market International Monetary Fund insurance technologies

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list of abbreviations   xxvii IO industrial organization individual retirement accounts IRA IRB internal ratings-based ITT intention-to-treat Japan Agriculture Bank JA Bank JBIC Japan Bank for International Cooperation JFC Japan Finance Corporation KYC know your customer know your customer’s customer KYCC local average treatment effects LATE LGFV local government financing vehicle large and complex banking organizations LCBOs liquidity coverage ratio LCR loss given default LGD London Interbank Offered Rate LIBOR loan loss provisioning LLP liquidity mismatch index LMI lender of last resort LOLR limited-purpose finance company LPFC Large-Scale Asset Purchase LSAP Less Significant Institutions LSIs Long-Term Refinancing Operation LTRO LTV loan-to-value LVG leverage M maturity mergers and acquisitions M&A MAC material adverse change mortgage-backed securities MBS Middle East and North Africa MENA Mortgage Electronic Registration System MERS marginal expected shortfall MES microfinance institutions MFIs machine learning ML money market deposit account MMDA Money Market Investment Fund Facility MMIFF money market funds MMFs MMMFs money market mutual funds Ministry of Finance MoF Main Refinancing Operations MRO medium-term note MTN non-bank credit intermediation NBCI NCOF net cash outflows new empirical industrial organization NEIO

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xxviii   list of abbreviations NFC non-financial corporation National Federation of Independent Businesses NFIB NIC National Information Center negative interest rate policy NIRP negotiable order of withdrawal account NOW NPF non-performing financing NPL non-performing loan NRSRO Nationally Recognized Statistical Rating Organization net stable funding ratio NSFR Office of the Comptroller of the Currency OCC OECD Organisation for Economic Co-operation and Development off-shore financial center OFC orderly liquidation authority OLA orderly liquidation fund OLF open market operations OMO outright monetary transactions OMT OTH originate-to-hold OTC over-the-counter OTD originate-to-distribute Office of Thrift Supervision OTS P2P Peer-to-peer People’s Bank of China PBoC prompt corrective action PCA probability of default PD primary dealer credit facility PDCF private equity PE PIN Personal Identification Number public limited company PLC payment protection insurance PPI Prudential Regulatory Authority PRA Payments Systems Directive 2 PSD2 public sector entities PSEs payment versus payment PVP quantitative easing QE risk-adjusted return on capital RAROC randomized controlled trials RCTs RegTech regulatory technology real estate investment trusts REITs real estate mortgage investment conduits REMICs repurchase agreements Repos Reconstruction Finance Corporation RFC RMB renminbi residential mortgage-backed securities RMBS

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list of abbreviations   xxix RMP relative market power return on assets ROA ROE return on equity rotating savings and credit associations ROSCAS required stable funding RSF RTGS Real-Time Gross Settlement RWA risk-weighted assets S&Ls savings and loans Small Business Administration (US) SBA small business credit scoring SBCS SCB stress capital buffer small business economic trends SBET Survey of Consumer Finances SCF Small Business Lending Fund SBLF Supervisory Capital Assessment Program SCAP SCP structure–conduct–performance sectoral capital requirements SCR sustainable development goals SDG Security and Exchange Commission SEC Southeastern Europe SEE Single Euro Payments Area SEPA systemic expected shortfall SES securities financing transaction SFT Standard Industrial Classification SIC systemically important financial institution SIFI structured investment vehicle SIV SLR supplementary leverage ratio small to medium-sized enterprises SMEs Shared National Credit SNC subordinated notes and debentures SND state-owned commercial banks SOCBs state-owned enterprises SOEs SOP say-on-pay single point of entry SPOE special purpose vehicle SPV systemic risk SRISK SRF Single Resolution Fund Single Resolution Mechanism SRM Sharia Supervisory Board SSB Survey of Small Business Finance SSBF sequential servicing constraint SSC SSM Single Supervisory Mechanism Survey of Terms of Bank Lending STBL

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xxx   list of abbreviations STC SWF SWIFT

simple, transparent, and comparable sovereign wealth fund Society for Worldwide Interbank Financial Telecommunication, a message transfer network Term Auction Facility TAF TAGP Transaction Account Guarantee Program TALF Term Asset-Backed Securities Loan Facility TARGET 2 Europe’s RTGS network Troubled Assets Relief Program TARP TBTF too-big-to-fail TFP total factor productivity targeted investment program TIP TITF too-interconnected-to-fail total loss-absorbing capacity TLAC Temporary Liquidity Guarantee Program TLGP Targeted Longer-Term Refinancing Operations TLTRO TMTF too-many-to-fail trust preferred securities TruPS Term Securities Lending Facility TSLF Undertakings for Collective Investment in Transferable Securities UCITS unconventional monetary policies UMP Value at Risk VaR Vienna Initiative VI wealth management products WMP World Council of Credit Unions WOCCU World Trade Organization WTO ZLB zero lower bound

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List of Contributors The Editors Allen N. Berger is the H. Montague Osteen, Jr., Professor in Banking and Finance and Ph.D coordinator of the Finance Department, Darla Moore School of Business; Carolina Distinguished Professor, University of South Carolina; Senior Fellow, Wharton Financial Institutions Center; and Fellow, European Banking Center. He also currently serves on the editorial boards of seven professional finance and economics journals. He is co-author of Bank Liquidity Creation and Financial Crises (2016, Elsevier) and is currently co-authoring TARP and other Bank Bailouts and Bail-Ins around the World: Connecting Wall Street, Main Street, and the Financial System (2019, Elsevier). He has published well over 100 professional articles including papers in top finance journals. His research has been cited over 70,000 times according to Google Scholar, and he has given invited keynote addresses on five continents. He was Senior Economist from 1989 to 2008 and Economist from 1982–9 at the Board of Governors of the Federal Reserve System. He received a Ph.D in Economics from the University of California, Berkeley in 1983, and a B.A. in Economics from Northwestern University in 1976. Philip Molyneux is Dean of the College of Business Administration at the University of Sharjah (in the UAE). His main area of research is on the structure and efficiency of banking markets and he has published widely in this area. Recent publications appear in the Journal of Money, Credit and Banking, Journal of Financial Intermediation, Journal of Banking & Finance and the Review of Finance. He has co-written/edited over thirty-five books and is also the series editor of the Palgrave Macmillan Studies in Banking and Financial Institutions—with over 135 books in the series to date. In the past, Philip has acted as a consultant to the New York Federal Reserve Bank, World Bank, European Commission, UK Treasury, Citibank Private Bank, Barclays Wealth, McKinsey, Credit Suisse and various other international banks and consulting firms. John O.S. Wilson is Professor of Banking and Finance and Director of the Centre for Responsible Banking & Finance based at the University of St Andrews. He is also a Member of the Scientific Advisory Board of Chartered Association of Business Schools Academic Journal Guide. Previously, he was Treasurer and General Secretary of the British Accounting and Finance Association during the period 2009–11, and the founding Chair of the British Accounting and Finance Association Financial Markets and Institutions Special Interest Group over the period 2007–18. He has guest edited

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xxxii   list of contributors special issues for Journal of Corporate Finance, Journal of Banking & Finance, Journal of Economic Behaviour & Organization, European Journal of Finance, Public Money & Management, British Accounting Review and Managerial Finance. In the period June 2011 to April 2012, John served as a full member of a Commission on Credit Unions established by the Irish Government. The Commission delivered interim and final reports to the Minister for Finance in September 2011 and April 2012 respectively. In 2018, John delivered evidence on the impact of Brexit on UK small and medium-sized enterprises to the House of Lords EU Internal Markets Committee.

Contributors Tobias Adrian is the Financial Counsellor and Director of the Monetary and Capital Markets Department of the International Monetary Fund (IMF). In this capacity, he leads the IMF’s work on financial sector surveillance, monetary and macroprudential policies, financial regulation, debt management, and capital markets. He also oversees capacity-building activities in IMF member countries, particularly with regard to the supervision and regulation of financial systems, central banking, monetary and exchange rate regimes, and asset and liability management. Prior to joining the IMF, he was a Senior Vice President of the Federal Reserve Bank of New York and the Associate Director of the Research and Statistics Group. At the Federal Reserve, he contributed to  monetary policy, financial stability policies, and crisis management. He taught at Princeton University and New York University and has published extensively in economics and finance journals, including the American Economic Review, Journal of Finance, Journal of Financial Economics, and Review of Financial Studies. His research spans asset pricing, financial institutions, monetary policy, and financial stability, with a focus on aggregate consequences of capital markets developments. He holds a Ph.D from the Massachusetts Institute of Technology, an M.Sc. from the London School of Economics, a Diploma from Goethe University Frankfurt, and a Maîtrise from Dauphine University Paris. He received his Abitur in Literature and Mathematics from Humboldtschule Bad Homburg. Franklin Allen is Professor of Finance and Economics and Director of the Brevan Howard Centre at Imperial College London and has held these positions since July 2014. He was on the faculty of the Wharton School of the University of Pennsylvania from July 1980 to June 2016. He now has Emeritus status there. He was formerly Vice Dean and Director of Wharton Doctoral Programs, Co-Director of the Wharton Financial Institutions Center, Executive Editor of the Review of Financial Studies and Managing Editor of the Review of Finance. He is a past President of the American Finance Association, the Western Finance Association, the Society for Financial Studies, the Financial Intermediation Research Society and the Financial Management Association, and a Fellow of the Econometric Society and the British Academy. He received his doctorate from Oxford University. His main areas of interest are corporate

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list of contributors   xxxiii finance, asset pricing, financial innovation, comparative financial systems, and financial crises. He is a co-author with Richard Brealey and Stewart Myers of the eighth through twelfth editions of the textbook Principles of Corporate Finance. Linda Allen holds the William F. Aldinger Chair in Banking and Finance at Baruch College, City University of New York. Her broad areas of research are risk measurement and management, focusing on systemic risk, credit risk, and operational risk; the evolution of financial markets and bank regulation; and the organization of financial institutions. Her latest book Credit Risk Measurement In and Out of Crisis: New Approaches to Value at Risk and Other Paradigms, 3rd edition (Wiley, 2010), co-authored with Anthony Saunders, describes the global financial crisis that began in 2007, as well as deconstructs credit risk measurement models commonly used by bankers and other finance professionals. She is also the author of Capital Markets and Institutions: A Global View (Wiley, 1997) and co-author of Understanding Market, Credit and Operational Risk (Blackwell, 2004). She is an associate editor of many finance journals, and has published extensively in top academic journals in finance and economics. Along with her consulting in securities litigation, she has lectured and advised all over the world on topics of risk measurement and management, banking trends, and financial market development. Deniz Anginer is a financial economist in the Finance and Private Sector Development Team of the World Bank’s Research Group. He conducts research in the areas of financial intermediation and empirical asset pricing. His research work in systemic risk and financial stability has been widely cited by academics, media, and policymakers. He has a Ph.D in Finance from the Ross School of Business at the University of Michigan. Adam B. Ashcraft is currently a Managing Director in the Global Risk Analytics Group at Bank of America. Previously, he worked at the Federal Reserve Bank of New York for seventeen years where he held various roles including Co-Chair of the LISCC Liquidity Program, Head of Credit Risk Management, and Research Economist. He holds Bachelor’s degrees in Economics and Mathematics & Statistics from Miami University and a Doctorate in Economics from the Massachusetts Institute of Technology. Thorsten Beck is Professor of banking and finance at Cass Business School in London. He is also a research fellow of the Centre for Economic Policy Research (CEPR) and the CESifo. He was Professor of Economics from 2008 to 2014 at Tilburg University and the founding chair of the European Banking Center from 2008 to 2013. Previously he worked in the research department of the World Bank and has also worked as consultant for, among others, the European Central Bank, the Bank of England, the BIS, the IMF, the European Commission, and the German Development Corporation. His research, academic publications, and operational work have focused on two major questions: What is the relationship between finance and economic development? What policies are needed to build a sound and effective financial system? Recently, he has concentrated on access to financial services, including SME finance, as well as on the design of regulatory and bank resolution frameworks. He holds a Ph.D from the University of Virginia and an M.A. from the University of Tübingen in Germany.

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xxxiv   list of contributors Lamont  K.  Black is an Assistant Professor of Finance in the Driehaus College of Business at DePaul University in Chicago. He is also the Academic Director for DePaul’s Center for Financial Services and the Chair of the Banking Advisory Group for FinTEx. Prior to joining the faculty of DePaul, he was an economist at the Federal Reserve Board of Governors in Washington, DC. His research has been published in several journals, including Journal of Financial Intermediation, Journal of Money, Credit and Banking; and Journal of Banking and Finance. He serves as a referee for the Review of  Financial Studies and Management Science among other journals. In his work on banking policy, he contributed to issues including incentive compensation, bank liquidity requirements, and European financial stability. He is also a co-organizer of the annual Chicago Financial Institutions Conference. Michael Blank is a Ph.D candidate in Business Economics at Harvard Business School. Previously, he served as a senior research analyst at the Federal Reserve Bank of New York. Robert R. Bliss is Professor Emeritus of Finance at Wake Forest University, where he taught courses in derivatives, fixed income, and capital markets. Prior to returning to academia in 2014, he served as a senior financial economist at Federal Reserve Bank of Chicago and held research positions at the Bank of England and the Federal Reserve Bank of Atlanta. Previously, he taught finance at Indiana University. His research interests include fixed income securities and derivatives, structured finance, risk management, financial regulation, and the law and economics of insolvency. He earned his doctorate in finance from the University of Chicago. Arnoud  W.A.  Boot is Professor of Corporate Finance and Financial Markets at the University of Amsterdam and member of the Royal Netherlands Academy of Arts and Sciences (KNAW). He is chairman of the Bank Council of the Dutch Central Bank (DNB), member of the Dutch Scientific Council for Government Policy (WRR) and chairman of the European Finance Association (EFA). He is also a research fellow at the Centre for Economic Policy Research (CEPR) in London. He was member of the Advisory Committee of the European Systemic Risk Board (ESRB), and a faculty member at the Kellogg Graduate School of Management at Northwestern University in Chicago. He has written extensively in the areas of financial institutions and corporate finance, with publications in major academic journals, such as the Journal of Finance, American Economic Review, Review of Financial Studies, and the Journal of Financial Intermediation. Narjess Boubakri is the Bank of Sharjah Chair in Banking and Finance, Professor of Finance and Head of the Finance Department at the School of Business Administration of the American University of Sharjah. Her research interests include, among other things, privatization, corporate governance, political economy of reforms, institutional economics, and the impact of institutional infrastructure on corporations. Her papers have been published in the Journal of Finance, the Journal of Financial Economics, the Journal of International Business Studies, the Journal of Accounting Research, and the

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list of contributors   xxxv Journal of Financial and Quantitative Analysis, among others. She acts as Associate Editor for the Journal of Corporate Finance, as Editor in Chief for Finance Research Letters, co-editor for the Quarterly Review of Economics and Finance, and is on the editorial boards of Emerging Markets Review and the Journal of International Financial Markets Institutions and Money. Christa H.S. Bouwman is Associate Professor of Finance and Patricia & Bookman Peters Professor of Finance at Mays Business School at Texas A&M University; and Fellow of the Wharton Financial Institutions Center at the University of Pennsylvania. She was Associate Professor of Banking & Finance at Case Western Reserve University where she also held the Lewis-Progressive Chair; Visiting Assistant Professor of Finance at MIT’s Sloan School of Management; Research Associate at the Federal Reserve Bank of Cleveland; and Visiting Scholar at the Federal Reserve Bank of Boston and the Federal Reserve Board in Washington DC. Her research interests are in Financial Intermediation and Corporate Finance. She is Co-Editor-in-Chief of the Journal of Financial Intermediation. She is Associate Editor of the Journal of Banking & Finance; and former Associate Editor of the Journal of Financial Intermediation, the Review of Finance, and Corporate Governance: An International Review. Her research papers have been published in the American Economic Review, Journal of Financial Economics, Review of Financial Studies, Journal of Financial Intermediation, Journal of Financial Stability, Journal of Banking & Finance, and MIT/Sloan Management Review. She is a co-author of the book “Bank Liquidity Creation and Financial Crises” (Elsevier, 2015). She worked for five years at ABN AMRO Bank (in Venture Capital, Project Finance Advisory, and Capital Structure Advisory), and as a part-time litigation consultant for the US Department of Justice. She received a Ph.D in Finance from the University of Michigan, an M.B.A.  from Cornell University, and  a B.A./ M.A. in Economics and Business (cum laude) from the University of Groningen, the Netherlands. Peter Breuer is Deputy Chief of the Global Analysis Division at the International Monetary Fund. In this role he jointly manages a team that analyzes risks to global financial stability, monitors and assesses global market developments, and helps ensure that the Fund takes consistent and well-informed views about financial risks and policies, including in the Global Financial Stability Report. Previously, as Deputy Chief of the Debt and Capital Markets Instruments Division, he oversaw teams analyzing risks emanating from shadow banking and providing debt management advice. He also led the Financial Sector Stability Assessment for Luxembourg. He headed the IMF’s office in Ireland as Resident Representative during the EU–IMF program in 2011–14. In previous roles, he served as Assistant to the Director in the Monetary and Capital Markets Department, and worked in the IMF’s Asia-Pacific, European, International Capital Markets, Strategy and Policy Review, and Research Departments. Policy areas he has covered include capital markets and financial stability, as well as debt sustainability and restructuring issues. Previous country responsibilities include Argentina, Bulgaria, Finland, Hong Kong, Ireland, Luxembourg, Pakistan, Paraguay, Peru, Uganda, United

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xxxvi   list of contributors Arab Emirates, and Uruguay. He holds a Ph.D and an M.A. from Brown University, a M.Sc. from the London School of Economics, and a B.A. from Vassar College. Claudia M. Buch is the Vice-President of the Deutsche Bundesbank. She is responsible for Financial Stability, Statistics, and Internal Audit. She is the accompanying person of the President of the Bundesbank on the ECB Governing Council and a member of the German Financial Stability Committee (FSC). Prior to joining the Bundesbank in May 2014, she was the President of the Institute for Economic Research (IWH) in Halle (2013–14), Professor of Economics at the Otto von Guericke University Magdeburg (2013–14), and Professor of Economics for “International Finance and Macroeconomics” at the University of Tübingen (2004–13). From 2012 to 2014, she was a member of the German Council of Economic Experts. She was Scientific Director at the Institute for Applied Economic Research (IAW) in Tübingen (2005–13), and worked at the Institute for World Economics in Kiel (IfW) from 1992 until 2013. She habilitated at the University of Kiel (2002) after receiving her doctorate there in 1996. Between 1985 and 1991, she studied Economics at the University of Bonn and she graduated from the University of Wisconsin (Eau Claire) with a Master of Business Administration degree in 1988. Her fields of specialization are financial stability, international banking, international finance and macroeconomics, and financial integration. Erwin Bulte is Professor of Development Economics at Wageningen University, and Professor of Institutions and Development at Utrecht University. His main research interests include institutional change, health, insurance, and agricultural development in developing countries, and much of his research is based on field experiments in Africa. Erwin has published more than 100 papers in international journals, including papers in the American Economic Review, Economic Journal, European Economic Review, and Journal of Public Economics. He is one of the leaders of the Policies, Institutions and Market program of the CGIAR. Charles  W.  Calomiris is the Henry Kaufman Professor of Financial Institutions at Columbia Business School, a Professor at Columbia’s School of International and Public Affairs, and a Research Associate of the National Bureau of Economic Research. He is a member of the Shadow Open Market Committee and the Financial Economists Roundtable. He is a Distinguished Visiting Scholar at the Hoover Institution, where he co-directs the Initiative on Regulation and the Rule of Law, and a Fellow at the Manhattan Institute. He received a B.A. in Economics from Yale University in 1979 and a Ph.D in Economics from Stanford University in 1985. Gerard Caprio, Jr. is William Brough Professor of Economics at Williams College and Chair of the Center for Development Economics. Previously he was the Director for Policy in the World Bank’s Financial Sector Vice Presidency and head of the financial sector research group. His research included establishing the first databases on banking crises around the world and on bank regulation and supervision, and he worked on financial system reform and development issues around the world. He has consulted for the IMF, the World Bank, and various governments. He has authored numerous

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list of contributors   xxxvii articles, and co-authored The Guardians of Finance: Making Regulators Work for Us, with Jim Barth and Ross Levine (MIT Press, 2012), with whom he also wrote Rethinking Bank Regulation: Till Angels Govern (Cambridge University Press, 2006). Earlier positions include: Vice President and Head of Global Economics at JPMorgan, and economist positions at the Federal Reserve Board and the IMF. He has taught at Trinity College Dublin, where he was a Fulbright Scholar, and at George Washington University. Fernando J. Cardim de Carvalho was Emeritus Professor of Economics at the Institute of Economics, Federal University of Rio de Janeiro (Brazil). Former associate editor of the Journal of Post Keynesian Economics, he is author of the books Mr Keynes and the Post Keynesians (Edward Elgar, 1992) and Liquidity Preference and Monetary Economies (Routledge, 2015). His research interests were Keynesian macroeconomics, international monetary economics, and financial systems. Jacopo Carmassi is a Senior Financial Stability Expert in the Financial Regulation and Policy Division, DG Macroprudential Policy and Financial Stability, at the European Central Bank. He is a Fellow of CASMEF, the Arcelli Center for Monetary and Financial Studies, University LUISS Guido Carli, and a Fellow of the Wharton Financial Institutions Center, University of Pennsylvania. Previously, he worked as an economist at Assonime, the Association of Joint Stock Companies incorporated in Italy, and at the Italian Banking Association. He holds a Ph.D in Law and Economics from University LUISS Guido Carli of Rome. He is author of several publications on banking and financial regulation topics, including the 2007–9 Global Financial Crisis, bank capital rules, bank crisis resolution, deposit insurance, banking union in Europe, and the corporate complexity of Global Systemically Important Banks. Elena Carletti is Professor of Finance at Bocconi University and Scientific Director of the Florence School of Banking and Finance at the European University Institute (EUI). Previously she was Professor of Economics at the EUI, holding a joint chair in the Economics Department and the Robert Schuman Centre for Advanced Studies. She is a member of the Board of Directors of Unicredit SpA and of the Advisory Scientific Committee of the European Systemic Risk Board. Furthermore, she is Research Fellow at CEPR, Fellow of the Finance Theory Group, CESifo, IGIER, and the Wharton Financial Institutions Center. Among other appointments, she has worked as consultant for the OECD and the World Bank, has served in the review panel of the Irish Central Bank and of the Riskbank, and has been a board member of the Financial Intermediation Research Society and of the Fondazione della Cassa di Risparmio di La Spezia. Her main research areas are Financial Intermediation, Financial Crises and Regulation, Competition Policy, Corporate Governance, and Sovereign Debt. Barbara Casu is the Director of the Centre for Banking Research at Cass Business School, where she is Professor of Banking and Finance. Her main research interests are in empirical banking, although several of her research projects are cross-disciplinary and include aspects of financial regulation, structured finance, accounting and

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xxxviii   list of contributors corporate governance. She has published widely, with over forty publications in peer-reviewed journals. She has also written the popular textbook Introduction to Banking (Pearson FT, 2015), which is widely adopted for banking courses across the world. She has recently co-edited the Palgrave Handbook of European Banking. Nicola Cetorelli is a Vice President at the Federal Reserve Bank of New York and the Head of the Financial Intermediation Function in its Research Group. His research has focused on the industrial organization and the corporate finance characteristics of the banking industry and the relationships with real economic activity. More recently he has worked on themes of international banking and on the evolution of financial intermediation. He represents the New York Fed on various Financial Stability Boards’ international working groups. He has published in a number of scholarly journals, among which the Journal of Finance, Journal of Economic Theory, American Economic Review, and Journal of International Economics. He has also written many articles in various policy journals and book chapters. He received his Ph.D in Economics from Brown University and a B.A. from the University of Rome, Italy. Ruiyuan (Ryan) Chen is an Assistant Professor of Finance at the West Virginia University. His current research focuses on state ownership, corporate governance, and corporate cash holdings. His research has been published in Emerging Markets Review, the Journal of Corporate Finance, and the Journal of Financial and Quantitative Analysis. Robert Cull is acting research manager and Lead Economist in the Finance and Private Sector Development Team of the World Bank’s Development Research Group. His most recent research is on the performance of microfinance institutions, African financial development, Chinese financial development and firm performance, and the effects of the global financial crisis on foreign banks in developing economies. He has published numerous articles in peer-reviewed academic journals including the Economic Journal, Journal of Development Economics, Journal of Economic Perspectives, Journal of Financial Economics, Journal of Law and Economics, and the Journal of Money, Credit, and Banking. The author or editor of multiple books, his most recent co-edited book, Banking the World: Empirical Foundations of Financial Inclusion was published by MIT Press in January, 2013. He is also co-editor of the Interest Bearing Notes, a ­­bi-monthly newsletter reporting on financial and private sector research. Olivier de Bandt is director of International Economics and Cooperation at the Banque de France. He was previously head of the Directorate of Research and Risk Analysis at the ACPR, the French Prudential Supervision and Resolution Authority. He holds a Ph.D from the Department of Economics of the University of Chicago. He contributed many articles in peer-reviewed academic journals on stress-testing methods, the analysis of systemic risk, the impact of banking regulation, the economics of insurance. He is an Associate Editor of the Journal of Financial Stability. Luiz Fernando de Paula is Professor of Economics at the State University of Rio de Janeiro (Brazil), joint appointment between the Faculty of Economics (FCE) and

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list of contributors   xxxix Institute of Social and Political Studies (IESP), and CNPq Researcher. He is currently a co-editor of the Brazilian Keynesian Review. He is author of the book Financial Liberalization and Economic Performance: Brazil at the Crossroads (Routledge, 2011) and co-editor of the book Financial Liberalization and Economic Performance in Emerging Countries (Palgrave Macmillan, 2008). A former chairman of the Brazilian Keynesian Association, his research interests include banking, financial systems, Keynesian macroeconomics, and economic policies related to emerging economies. Hans Degryse is Professor of Finance at the Department of Accountancy, Finance and Insurance of the KU Leuven. He is a research fellow at the CEPR, CESIfo, the European Banking Center (EBC), and TILEC. He is a member of the Group of Economic Advisers of ESMA. Before joining Leuven in 2012, he was Professor of Finance at Tilburg University. His research focuses on financial intermediation, including theoretical and empirical banking as well as market microstructure. He has published in many journals including the American Economic Review, Journal of Finance, Journal of Financial Economics, Review of Financial Studies, Management Science, Review of Finance, Journal of Financial Intermediation, and the Economic Journal, and has been presented in leading international conferences such as the American Finance Association, the Western Finance Association, the European Finance Association, and the Financial Intermediation Research Society. He co-authored, with Moshe Kim and Steven Ongena, the graduate textbook Microeconometrics of Banking: Methods, Applications and Results (Oxford University Press, 2009). Gayle L. DeLong is an Associate Professor in the Economics and Finance Department of Baruch College in the City University of New York. She earned a Ph.D in International Business and Finance from New York University and a Masters in International Business Studies from the University of South Carolina. Her research interests include banking, public–private partnerships, and the implications of regulations. In 2012, she won the Abraham J. Briloff Prize in Ethics at Baruch College, New York. Asli Demirgüç-Kunt is the Director of Research at the World Bank. After joining the Bank in 1989 as a Young Economist, she has held different positions, including Director of Development Policy, Chief Economist of Financial and Private Sector Development Network, and Senior Research Manager, doing research and advising on financial sector and private sector development issues. She has published over 100 articles in the areas of banking crises, financial regulation, links between financial and economic development, access to financial services and financial inclusion. She has been the President of International Atlantic Economic Society (2013–14) and Director of Western Economic Association (2015–18). Prior to coming to the Bank, she was an Economist at the Federal Reserve Bank of Cleveland. She holds a Ph.D and an M.A. in economics from the Ohio State University. Robert DeYoung is the Koch Distinguished Professor of Business Economics and holds the Harold Otto Chair in Economics at the University of Kansas School of Business. He is also co-editor of the Journal of Money, Credit and Banking. Prior to joining the KU

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xl   list of contributors faculty, he was an Associate Director of Research at the Federal Deposit Insurance Corporation, an Economic Advisor at the Federal Reserve Bank of Chicago, a Senior Economist at the Office of the Comptroller of the Currency, and a Joyce Foundation Teaching Fellow at Beloit College. He worked his way to an undergraduate degree at Rutgers University-Camden, and holds a Ph.D in economics from the University of Wisconsin-Madison. Gregory Elliehausen is Principal Economist in the Consumer Finance Section of the Division of Research and Statistics at the Board of Governors of the Federal Reserve System. His current research focuses on consumer financial behavior, regulation of financial markets and services, and markets for high-rate credit products. His research has been published in numerous professional journals. Recent work includes Truth in Lending: Theory, History, and a Way Forward (co-authored with T.A. Durkin), which analyzes the purposes, strengths, and weaknesses of disclosures as consumer protections in financial transactions, and Consumer Credit and the American Economy (co-authored with T.A.  Durkin, M.S.  Staten, and T.J.  Zywicki), which examines the economics, psychology, law, and regulation of consumer credit in the United States. Previously, he held research positions at George Washington University (2006–9), Georgetown University (1998–2005), and the Board of Governors of the Federal Reserve System (1981–98). He has a Ph.D degree in business administration from the Pennsylvania State University. Mark  J.  Flannery has been the BankAmerica Eminent Scholar in Finance at the University of Florida since 1989. He previously held faculty positions at the University of North Carolina (Chapel Hill) and the University of Pennsylvania. He has published extensively, particularly in the areas of corporate finance and financial regulation. He holds economics degrees from Princeton (A.B.) and Yale (M.A., M.Phil, and Ph.D). He served as president of the Financial Intermediation Research Society (FIRS), president and board chairman of the Financial Management Association, and member of the board of directors of the American Finance Association. He was an editor of the Journal of Money, Credit and Banking from 2000–5. W. Scott Frame is a financial economist and senior advisor on the financial markets team in the research department of the Federal Reserve Bank of Atlanta. His major fields of study are financial institutions, credit markets, real estate, and public policy. He has been with the Bank since 2001, although he spent two years as the Belk Distinguished Professor of Finance at the University of North Carolina at Charlotte (2012–14). Before joining the Bank, he was a senior financial economist at the US Treasury Department from 1996 to 2000. He also worked at the Federal Reserve Bank of Atlanta as an economic analyst from 1993 to 1995 and as an instructor at the University of Georgia. He was promoted to financial economist and policy advisor in 2007 and assumed his current duties in 2012. Xavier Freixas is Chairman of the Department of Economics and Business and Professor at the Universitat Pompeu Fabra in Barcelona (Spain) after becoming full

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list of contributors   xli Professor at the Université de Toulouse. He is also affiliated Professor at Barcelona Graduate School of Economics as well as Research Fellow at CEPR. He has previously been president of the European Finance Association, Deutsche Bank Professor of European Financial Integration at Oxford University, Houblon Norman Senior Fellow of the Bank of England and chairman of the Risk Based Regulation program of the Global Association of Risk Professionals (GARP). He has been a consultant for the European Investment Bank, the New York Fed, the European Central Bank, the World Bank, the Inter-American Development Bank and the European Investment Bank. He is Associate Editor of the Journal of Financial Intermediation and of the Journal of Financial Services Research. He is well known for his MIT Press book, jointly with JeanCharles Rochet, Microeconomics of Banking. His research focuses on banking and regulation, and has been published in top international journals. Zuzana Fungáčová is a Senior Advisor at the Bank of Finland Institute for Economies in Transition in Helsinki. Her research interests are in banking, emerging markets and their financial sectors as well as financial stability. She has experience from the European Central Bank and was also a Visiting Economist at the Austrian Central Bank. She obtained her Ph.D in Economics from the Center for Economic Research and Graduate Education in Prague and served also as a research affiliate at the Institute of Economic Studies at Charles University in Prague. Her research has been published in academic journals including Journal of Banking and Finance, Journal of Financial Services Research, Journal of Economic Behavior & Organization, World Development, Journal of Macroeconomics, Economics of Transition, Regional Studies and China Economic Review. John Goddard is the Head of Aberystwyth Business School at Aberystwyth University, Wales. He is also Emeritus Professor of Financial Economics at Bangor University, and served as Deputy Head of Bangor Business School between 2007 and 2017. His previous academic appointments were at the University of Leeds, Abertay University and Swansea University. He has several years’ practitioner experience in the UK life insurance industry. His research interests are in industrial organization, financial markets and institutions, and the economics of professional sports. He is author or co-author of sixty-nine refereed journal articles. His co-authored book publications include The Economics of Football (2nd edition, Cambridge University Press, 2011), Banking: A Very Short Introduction (Oxford University Press, 2016) and the textbook Industrial Organization: Competition, Strategy, Policy (5th edition, Pearson, 2017). Xian Gu is an Assistant Professor of Finance at the Central University of Finance and Economics in Beijing. Previously she worked as a post-doctoral research fellow at Wharton Financial Institutions Center and an economist at CITIC Securities in Beijing. She was also a Visiting Researcher at central banks including Bank of Finland and Hong Kong Monetary Authority. She earned her Ph.D from Beijing Normal University. Her main research interests are banking, corporate finance, and China’s economy. Omrane Guedhami is the C. Russell Hill Professor of Economics and Professor of International Finance at the Moore School of Business at the University of South

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xlii   list of contributors Carolina. His current research focuses on corporate governance, privatization, corporate social responsibility, and formal and informal institutions and their effects on corporate policies and firm performance. His research has been published in the Journal of Financial Economics, the Journal of Accounting Research, the Journal of Accounting and Economics, the Journal of Financial and Quantitative Analysis, the Journal of International Business Studies, and Management Science, and the Review of Finance, among others. He is a member of the editorial boards of major journals, such as Contemporary Accounting Research and the Journal of International Business Studies, and is currently serving as a Section Editor at the Journal of Business Ethics and Associate Editor of the Journal of Corporate Finance and the Journal of Financial Stability. Jens Hagendorff is Professor of Finance at the University of Edinburgh. Professor Hagendorff previously worked at Cardiff University, the Financial Stability Department of the Bank of Spain and as a lecturer at the University of Leeds. He held Visiting positions in the US, Italy, and Spain, most recently as a Visiting Fellow at The Federal Reserve Bank of Atlanta and the Bank of Spain in Madrid. He publishes and lectures on a range of topics in finance, banking, and investments, in particular the risk and return implications of corporate governance in the banking industry. His work has been published in leading international journals, including the Review of Financial Studies, Journal of Quantitative and Financial Analysis, and Review of Finance. He is one of the authors of Size, Risk and Governance in European Banking (Oxford University Press, 2013). Philipp Hartmann is Deputy Director General of the research department at the European Central Bank, which he helped build up from its beginning. He also coordinates the ECB’s work on financial integration and is a Fellow of the Centre for Economic Policy Research. Previously, he held positions at the London School of Economics, the European Monetary Institute and Erasmus University Rotterdam. He published research on financial, monetary, and international issues in numerous journal articles and several books. He serves as an associate editor of the Journal of Financial Stability. His policy work has been published in many official reports and discussed in fora including the ECOFIN Council, the ECB Governing Council, the Basel Committee on Banking Supervision and the United Nations Economic Commission for Europe. He holds a Doctorat en Sciences Economiques (Paris) earned in the European Doctoral Program in Quantitative Economics. Iftekhar Hasan is the E. Gerald Corrigan Chair in International Business and Finance at Gabelli School of Business, New York, USA. He serves as the scientific advisor at the Bank of Finland and is affiliated with the University of Sydney as a fractional Professor. He is the managing editor of the Journal of Financial Stability and serves as an associate editor for several other academic journals. His research interests are in the areas of  financial institutions, corporate finance, and emerging economies. Professor Hasan has numerous publications in print, including books and edited volumes, and

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list of contributors   xliii peer-reviewed journal articles in finance, economics, accounting, information systems, and management journals. Richard J. Herring is Jacob Safra Professor of International Banking and Professor of Finance at The Wharton School, University of Pennsylvania, where he is also Director of The Wharton Financial Institutions Center. Outside the University he serves on the FDIC Systemic Risk Advisory Committee and the Systemic Risk Council. His research focuses on banking and financial market regulation and supervision. Patrick Honohan is Honorary Professor of Economics at Trinity College Dublin, a Non-resident Senior Fellow at the Peterson Institute for International Economics and a Research Fellow of CEPR. From 2009–15 he was Governor of the Central Bank of Ireland. Previously, he was a Senior Advisor at the World Bank and his career has also included periods on the staffs of the IMF, the Economic and Social Research Institute, Dublin, and as Economic Advisor to the Taoiseach. Joseph P. Hughes is Professor of Economics at Rutgers University. He has been a Fellow of the Wharton Financial Institutions Center and a Visiting Scholar at the Federal Reserve Bank of Cleveland, the Federal Reserve Bank of Philadelphia, the Federal Reserve Bank of New York, and the Office of the Comptroller of the Currency. His research has been published in such journals as the American Economic Review, the Journal of Banking and Finance, the Journal of Economic Theory, the Journal of Financial Intermediation, the Journal of Financial Services Research, the Journal of Money, Credit, and Banking, and the Review of Economics and Statistics. He received his Ph.D from the University of North Carolina at Chapel Hill. David Humphrey is the F.W.  Smith Eminent Scholar in Banking at Florida State University and is a Visiting Scholar at the Payments Cards Center at the Federal Reserve Bank of Philadelphia. He has taught at three universities and previously worked at the Federal Reserve for sixteen years. His publications have focused on banking and payment system issues. He received his Ph.D from the University of California (Berkeley). Dasol Kim is a Senior Economist at the Office of Financial Research, US Department of the Treasury. He previously served as an Assistant Professor in Banking and Finance at Weatherhead School of Management, Case Western Reserve University. He has published papers in journals such as the Journal of Financial Economics, the Review of Financial Studies, and European Financial Management, and his research has been featured in various media outlets, including the Wall Street Journal, Barron’s, the Atlantic, and Forbes. He holds a doctorate in financial economics from the Yale School of Management, Yale University. In addition, he holds a master’s degree in statistics from Columbia University and a bachelor’s degree in mathematics and economics from the University of California, Los Angeles. Leora Klapper is a Lead Economist in the Finance and Private Sector Research Team of the Development Research Group at the World Bank. Her publications focus on corporate and household finance, banking, entrepreneurship, and risk management.

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xliv   list of contributors Her current research studies the impact of digital financial services, especially for women. She is a founder of the Global Findex database, which measures how adults around the world save, borrow, make payments, and manage risk. Previously, she worked at the Board of Governors of the Federal Reserve System and Salomon Smith Barney. She holds a Ph.D in Financial Economics from New York University Stern School of Business. Andreas Lehnert is the director of the Division of Financial Stability at the Federal Reserve Board in Washington, DC. He joined the Fed after earning his Ph.D in economics from the University of Chicago. He started in the household finance research group where he worked on a variety of topics in consumer and mortgage credit. During the financial crisis, he contributed to several projects including various mortgage modification initiatives, the TARP, the 2009 bank stress tests, and the TALF. In November 2010, he moved to the Board’s newly created financial stability group where he participates in a variety of ongoing initiatives to promote financial stability, including regulatory reform, the periodic assessment of financial vulnerabilities, the development of macroprudential tools, and the design and oversight of the bank stress tests; in addition, he supports the Federal Reserve’s role on the Financial Stability Oversight Council and the Financial Stability Board. His research focuses on financial stability, macroprudential policy, banking, and finance. Robert Lensink is a Professor of Finance at the University of Groningen, and a Professor of Finance and Development (part-time) at Wageningen University. He is a development economist with extensive experience in field studies, including impact evaluations, with a focus on microfinance in the broadest sense. He was the chair of the International Review Panel of the 1st and 2nd round of the International Initiative of Impact Evaluation (3ie) Open Window to select proposals for impact evaluation in developing countries. He has published more than 100 articles in international journals, among which include the American Economic Review, Economic Journal, Management Science, Public Economics, and World Development. In 2011, he won the SOM Outstanding Researcher Award (Best Researcher of the Faculty of Economics and Business, University of Groningen). Robert Lensink has been appointed Officer of the Order of Orange-Nassau. Xinming Li is an Associate Professor of Finance at the School of Finance at Nankai University and a consultant at the World Bank Group. He is also the holder of the Emerging Scholars Award by the Federal Reserve and the Conference of State Bank Supervisors. His research areas include a variety of topics related to banking and financial institutions, corporate finance, and international finance. Alex Martin is a Senior Research Assistant at the Federal Reserve Board of Governors in the Division of Financial Stability. Previously, she served as a Research Intern at the US Department of the Treasury in the Office of Economic Policy. She is a graduate of the University of Mississippi with a B.A. in International Studies and Mathematics.

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list of contributors   xlv María Soledad Martínez Pería is Chief of the Macro-Financial Division in the IMF Research Department. She manages a team of economists responsible for conducting research and policy work on macroeconomic and financial issues critical to fund surveillance activities, with a focus on macro-financial linkages, financial flows, and financial systems. Her published research addresses questions related to financial crises, market discipline, foreign bank participation, bank competition, bank regulation, SME financing, financial inclusion, and remittances. Prior to joining the IMF, she worked at the World Bank, the Brookings Institution, the Central Bank of Argentina, and the Federal Reserve Board. She holds a Ph.D in economics from the University of California, Berkeley and a B.A. from Stanford University. Donal McKillop is Professor of Financial Services at Queen’s University Belfast. He has written five books and has published papers in journals such as the European Economic Review, Journal of Applied Econometrics, Journal of Banking and Finance, and the Journal of Economic Perspectives. He has recently completed research for the European Commission on “Integrating Residential Property and Private Pensions” and for the Economic and Social Research Council on “The Development of Web-based Tools to Improve the Financial Capability of the Over-Indebted.” Outside of his academic role at Queen’s, he was Chair of the Credit Union Advisory Committee, Ireland (2012–18). He was appointed by Minister of Finance (Ireland) to advise the Minister and the Central Bank on matters relating to credit unions. He has also advised the Office of the  First Minister and Deputy First Minister (Northern Ireland) on intervention measures to help mitigate financial hardship due to the introduction of Welfare Reform in Northern Ireland. Loretta J. Mester is president and chief executive officer of the Federal Reserve Bank of Cleveland. In addition, she is an Adjunct Professor of Finance at the Wharton School, University of Pennsylvania, and a fellow at the Wharton Financial Institutions Center. She is the managing editor of the International Journal of Central Banking and a­ co-editor of the Journal of Financial Services Research. In addition, she is an associate editor of several other academic journals and serves on the management committee of the International Journal of Central Banking. Her publications include research on the organizational structure and production efficiency of financial institutions, the theory and regulation of financial intermediation, agency problems in credit markets, credit card pricing, central bank governance, and inflation. Her research has been published in the Journal of Finance, the American Economic Review, the Review of Financial Studies, and the Review of Economics and Statistics, among other journals. She received her Ph.D in economics from Princeton University. Frederic  S.  Mishkin is the Alfred Lerner Professor of Banking and Financial Institutions at the Graduate School of Business, Columbia University. He is also a Research Associate at the National Bureau of Economic Research, and the co-director of the US Monetary Policy Forum. From September 2006 to August 2008 he was a member (governor) of the Board of Governors of the Federal Reserve System. He has

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xlvi   list of contributors also been a Senior Fellow at the FDIC Center for Banking Research, and past President of the Eastern Economic Association. Since receiving his Ph.D from the Massachusetts Institute of Technology in 1976, he has taught at the University of Chicago, Northwestern University, Princeton University, and Columbia. He has also received an honorary professorship from the Peoples (Renmin) University of China. From 1994 to 1997 he was Executive Vice President and Director of Research at the Federal Reserve Bank of New York and an associate economist of the Federal Open Market Committee of the Federal Reserve System. Paola Morales-Acevedo is a Researcher at the Central Bank of Colombia, Banco de la República. Prior to that, she was an Economist at the Applied Research and Modelling Division of the Sveriges Riksbank. Her research focuses on empirical banking, financial intermediation, monetary policy, behavioral finance and corporate finance. She holds a Ph.D in Finance from the CentER graduate school of Tilburg University (Netherlands). During her Ph.D studies, she has been a Visiting Scholar at the Department of Banking and Finance of the University of Zurich, as well as an intern at the Research Department of the Sveriges Riksbank and at the Monetary Capital Markets Department (Financial Crisis) of the International Monetary Fund. She has also been a Junior Fellow of the European Banking Center. Paola received a M. Phil. in Finance from Tilburg University in 2011, an M.Sc. in Industrial Engineering in 2009, a B.A. in Economics in 2009 and a B.Sc. in Industrial Engineering in 2007 from Universidad de los Andes (Colombia). After finishing her first bachelor degree, she worked for three years at the Financial Stability Department of the Central Bank of Colombia. Fariborz Moshirian is the Director of the Institute of Global Finance (IGF) in the UNSW Business School, Sydney. The IGF conducts collaborative research on Systemic risk, Financial innovation and Global financial stability with NYU, UCLA and has had joint work with the Asian Development Bank, the International Monetary Fund, the World Bank, PwC and a number of world-class research centers. He was the Bertil Danielsson Professor of Finance for 2006 (sponsored by the Stockholm School of Economics and Nordea Bank). He is a consultant to the Asian Development Bank. He served as the Head of School of Banking and Finance at UNSW for over four years. He has published a number of influential research works on global financial stability, interconnectedness, governance, systemic risk, and the financial and social challenges of the twenty-first century in leading finance journals including the Journal of Finance, Journal of Financial Economics, Journal of Financial and Quantitative Analysis, Journal of Financial Markets, and the Journal of Banking and Finance. Steven Ongena is a Professor of Banking at the University of Zurich, a senior chair at the Swiss Finance Institute, a research Professor at KU Leuven, and a research fellow in financial economics of CEPR. He is also a research Professor at Deutsche Bundesbank. He has published more than sixty-five papers in refereed journals, including in the American Economic Review, Econometrica, Journal of Finance, Journal of Financial Economics, Journal of International Economics, Journal of Political Economy, Management

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list of contributors   xlvii Science, and Review of Finance. In 2017, he received an ERC Advanced Grant and in 2012 a NYU-Fordham-RPI Rising Star in Finance Award. Bruno M. Parigi is Professor of Economics, University of Padova, Italy. His research interests are in banking and financial economics. He has published in various journals among including Journal of Money Credit and Banking, Journal Banking & Finance, Journal of Financial Intermediation, and Journal of Economic Theory. He has been consultant for New York Fed, ECB, BIS, and he has held visiting positions at the Universities of Munich, Toulouse, Zurich, and the European University Institute. He received his Ph.D in Economics from Rutgers University. Raluca  A.  Roman is Senior Financial Economist at the Federal Reserve Bank of Philadelphia since July 2018. From 2015–18, she was Research Economist at Federal Reserve Bank of Kansas City. She holds a Ph.D in Finance from University of South Carolina. She also holds an M.B.A. with concentration in Finance from University of Bridgeport, and a B.A. in Economics from Alexandru Ioan Cuza University (Romania). Her research areas include a variety of topics related to banking and financial institutions (including bank government bailouts, internationalization, and corporate governance) and corporate finance. She has published two articles in the Journal of Financial and Quantitative Analysis, one in Management Science, two in the Journal of Financial Intermediation, one in Financial Management, and a book chapter in the Handbook of Finance and Development and has received four awards for her papers at conferences. She also is currently co-authoring the book TARP and other Bank Bailouts and Bail-Ins around the World: Connecting Wall Street, Main Street, and the Financial System (2019, Elsevier). She has presented her research and discussed the research of others at numerous finance and regulatory conferences. She has over seven years of professional experience in banking and corporate finance, and worked for top international organizations like UBS Investment Bank and MasterCard International, where she won various awards. Anna Sarkisyan is a Lecturer in Banking and Finance at Essex Business School, University of Essex (UK). Her research focuses on securitization, corporate governance, and performance in banking. She holds a Ph.D in Finance from Cass Business School, City, and University of London. In 2010, she was awarded a Lamfalussy Fellowship from the European Central Bank. Anthony Saunders is the John M. Schiff Professor of Finance and former Chair of the Department of Finance at the Stern School of Business at New York University. He received his Ph.D from the London School of Economics, and has taught at NYU since 1978. He has served as Visiting Professor all over the world including INSEAD, the Stockholm School of Economics, and the University of Melbourne. He has held positions on the Board of Academic Consultants of the Federal Reserve Board of Governors as well as the Council of Research Advisors at the Federal National Mortgage Association. He is Editor of Financial Markets, Instruments and Institutions. His research has been published in all the major banking and finance journals.

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xlviii   list of contributors Laura Solanko is Senior Advisor at the Bank of Finland Institute for Economies in Transition (BOFIT), specializing in Russian economic developments. She received her doctoral degree from the University of Helsinki in 2007, majoring in economics. She was the Editor of BOFIT Discussion Papers and responsible for BOFIT Visiting Researchers Programme for 2011–15, and continues to regularly contribute to BOFIT Weekly Review on Russia. Her current research interests include banking and financial markets in Russia and China, Russia–EU energy relations, and political economy in Russia. Her research has been published in, for example, the Journal of Banking and Finance, Public Choice, and Review of International Economics. Anjan V. Thakor holds the John E. Simon Professorship of Finance and is Director of  the Olin Business School’s Ph.D program, and Director of the WFA Center for Finance and Accounting Research. He has also served as Senior Associate Dean at the Olin Business School at Washington University in St Louis. Until July 2003, he held the Edward J. Frey Professorship of Banking and Finance and was Chairman of the Finance Group (2000–3) at the University of Michigan Business School. Prior to joining Michigan, he served as the NBD Professor of Finance and Chairman of the Finance Department at the School of Business at Indiana University. He has also served on the faculties of Northwestern University and UCLA as a Visiting Professor. He received his Ph.D in Finance from Northwestern University. He is a research associate of the European Corporate Governance Institute and a Fellow of The Financial Theory Group. He has served as managing editor of Journal of Financial Intermediation from 1996–2005 and currently serves as an associate editor. He is past-President and a founder of the Financial Intermediation Research Society. Hirofumi Uchida is Professor of Banking and Finance at the Graduate School of Business Administration at Kobe University. His research interests focus on financial institutions and financial system architecture. He was a Visiting Scholar at the Kelley School of Business at Indiana University as a 2003 Fulbright Scholar, a Visiting Scholar at the Shorenstein Asia Pacific Research Center at Stanford University as a  2016 Abe Fellow, and is an associate editor of the Journal of Money, Credit and Banking. Gregory F. Udell is the Chase Chair of Banking and Finance at the Kelley School of Business, Indiana University. He is, or has been, a Visiting Economist, Scholar and/or Consultant to the Board of Governors of the Federal Reserve System, the Bank of Japan, the Bank of Italy, the European Central Bank, the Federal Reserve Banks of Chicago and San Francisco, the International Finance Corporation, the OECD, the Peoples Bank of China, the Riksbank and the World Bank. Before joining the Kelley School of Business in 1998, he was Professor of Finance and Director of the William R. Berkley Center for Entrepreneurial Studies at the Stern School of Business at New York University. Prior to his academic career he was a commercial loan officer in Chicago. He has nearly 100 publications mostly focused on financial contracting, credit availability, and financial intermediation. These have appeared in leading accounting, economics, and finance journals. He is the author of a textbook on asset-based lending,

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list of contributors   xlix Asset-Based Finance (2004), a co-author (with L. Ritter and W. Silber) of Principles of Money, Banking and Financial Markets, 12th edition (2009), and is, or has been, an associate editor/editorial board member of seven academic journals including the Journal of Money, Credit and Banking, Journal of Banking and Finance, Journal of Financial Services Research and Small Business Economics. Patricio Valenzuela is an assistant Professor of Finance and Economics at University of Chile and a research fellow at the Millennium Institute for Research in Market Imperfections and Public Policy (MIPP). His primary areas of research are corporate finance, financial economics, international finance, and development economics. He has published in several peer-reviewed academic journals, including the Review of Finance, Journal of International Money and Finance, Journal of Banking and Finance and Economic Inquiry. He has also contributed chapters of several books on developing financial systems, including Handbook of the Economics of Finance, Towards a Better Global Economy: Policy Implications for Citizens in the 21st Century, and African Successes: Modernization and Development. Paul Wachtel is a Professor of Economics at New York University Stern School of Business. He has been with Stern for over forty years and has served as department chair and Vice Dean. He is currently the Academic Director for the BS in the Business and Political Economy Program. He has been a research associate at the National Bureau of Economic Research, a senior economic advisor to the East West Institute, and a consultant to the Bank of Israel, the IMF, and the World Bank. He received his B.A.  from Queens College in 1966, his M.A.  in Economics from the University of Rochester, and his D.Phil from the University of Rochester in 1971. His primary areas of research include the relationship of financial development to economic growth, monetary policy, central banking in the post-crisis world, and financial sector reform in economies in transition. He has published widely in these areas. Larry Wall is the research center executive director of the Center for Financial Innovation and Stability (CenFIS) in the research department of the Federal Reserve Bank of Atlanta. He is part of the financial markets team. CenFIS was created to improve knowledge of financial innovation and financial stability and the connection between the two. He joined the financial structure team of the Bank’s research department in 1982 and was promoted to executive director of the CenFIS in 2013. In addition to pursuing his research agenda, he leads CenFIS’s activities, including its newsletter, Notes from the Vault, and conferences. He has served on the editorial boards of various academic journals. He is also on the Academic Advisory Panel for the International Association of Deposit Insurers. He is currently on the boards of Financial Management Association International and the International Banking, Economics and Finance Association. He has also been an adjunct faculty member of Emory University and the Georgia Institute of Technology. A native of Grand Forks, North Dakota, he earned a bachelor’s degree in business administration from the University of North Dakota and a doctoral degree in business administration from the University of North Carolina at Chapel Hill.

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l   list of contributors Mark E. Van Der Weide has been the General Counsel of the Board of Governors of the Federal Reserve System in Washington, DC, since August 2017. From 2010 until August 2017, he worked in the Division of Supervision and Regulation of the Federal Reserve Board. In this capacity, he advised the Division Director and Board members on financial regulatory policy issues and helped coordinate the development of Federal Reserve positions on international and domestic regulatory policy. Mr. Van Der Weide served as a member of the Basel Committee on Banking Supervision from 2015–17 and represented the Federal Reserve on the Financial Stability Board’s Standing Committee on Supervisory and Regulatory Cooperation from 2010–17. Mr. Van Der Weide was detailed to the US Treasury Department during 2009–10, where he provided assistance to the Administration in its efforts to design the financial reform legislation that ultimately became the Dodd–Frank Act. Prior to joining the Federal Reserve Board in 1998, he worked as an associate in the Washington, DC, office of Cleary, Gottlieb, Steen & Hamilton. He received a J.D. degree from Yale Law School in 1995 and a B.A. degree in history and philosophy from the University of Iowa in 1992. Lawrence J. White is Robert Kavesh Professor of Economics at New York University’s Stern School of Business. During 1986–9 he served as a Board Member for the Federal Home Loan Bank Board, in which capacity he also served as Board Member for Freddie Mac. In the period 1982–3, he was on leave to serve as Director of the Economic Policy Office, Antitrust Division, US Department of Justice. He is the General Editor of the Review of Industrial Organization and was Secretary-Treasurer of the Western Economic Association International (2006–9). He received the B.A.  from Harvard University (1964), the M.Sc. from the London School of Economics (1965), and the Ph.D from Harvard University (1969). Jonathan Williams is a Professor of Banking and Finance at Bangor University, Wales, where he is Head of Bangor Business School and Co-Director of the Institute of European Finance. His early research focused on the performance of European banks under their organizational models. Subsequently, he has examined on banking sector developments in emerging market economies, such as bank privatization and competition. His most recent research is concentrated on executive compensation in banking, the characteristics of bank directors, and their effects on firm performance outcomes, including the impact of corporate culture in banking. Eliza Wu is an Associate Professor in Finance at the University of Sydney Business School. She has a joint honours degree in Economics and Econometrics and a Ph.D in Finance from the University of New South Wales (UNSW). Her research is focused on financial integration, the impact of financial regulations, credit risk and corporate governance. She has published over fifty international academic journal articles and book chapters. She was an Associate Editor of the Journal of Banking and Finance from 2013–2019 and serves as an Associate Editor for the Journal of Financial Stability amongst other journals. Outside of academia, she has worked at the Reserve Bank of Australia and at the Bank for International Settlements’ (BIS) Representative Office for

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list of contributors   li Asia and the Pacific. She has also worked as a teaching fellow at the University of Cambridge in Banking and Finance, a research fellow at the Hong Kong Institute for Monetary Research, and undertaken consulting and policy work for the BIS. Jeffrey  Y.  Zhang has been an Economist at the Board of Governors of the Federal Reserve System in Washington, DC, since April 2017. He works in the Special Projects Unit of the Division of Supervision and Regulation, where he focuses on domestic rulemakings, international regulatory coordination, and policy research. Prior to his current role, he served as a Staff Economist at the White House Council of Economic Advisers from 2012 to 2013, focusing on energy policy and macroeconomics. He has also worked at the Federal Reserve Bank of Boston and the Appeals Unit of the Criminal Division at the US Attorney’s Office in Boston. He received a J.D. degree from Harvard Law School in 2017, a Ph.D degree in economics from Yale University in 2017, and a B.A. degree in economics and mathematics from Boston College in 2010. Bilal Zia is a Senior Economist in the Finance and Private Sector Development Team of the Development Research Group at the World Bank in Washington, DC. His research focuses on financial development at the household, firm, and bank levels, and has appeared in top academic journals such as the Journal of Finance, Journal of Financial Economics, American Economic Journal: Applied Economics, Management Science, and Journal of Development Economics. He uses both experimental and nonexperimental methods and some of his recent work includes rigorous impact evaluations of financial and business education programs, testing innovative methods to improve financial access for households and firms, alternative credit scoring and digital financial engagement, and applying insights from behavioral economics to development finance.

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chapter 1

Ba n k i ng A Decade on from the Global Financial Crisis Allen N. Berger, Philip Molyneux, and John O. S. Wilson

1.1 Introduction It has been a decade since the worst financial crisis faced since the Great Depression. The banking industry is a very different place to the liberalized environment of the early 2000s. Banks have significantly de-risked and now hold more liquidity and capital than in the past. Capital rules continue to be modified and updated. Tougher capital rules for large banks were agreed in December 2017, but these will not be fully implemented until 2022. Basel III and its European counterpart (Capital Requirements Directive IV) were supposed to be implemented by 2019, but continuous updates mean that full implementation will not occur until the following decade. The full array of international banking regulatory reform proposals will not be fully implemented until 2027.1 The ongoing regulatory process does appear to have been successful in creating a safer global banking system with banks in a sounder financial position to weather large economic shocks compared with a decade earlier. Banks are managed in a more conservative manner. Big banks have retrenched to focus on domestic markets as well as a handful of key overseas areas. Most commercial banks are less reliant on wholesale funding, and less exposed to higher risk trading and investment banking activities. Banks are also embracing new financial and digital technologies in order to offer innovative services and reduce costs. However, overall performance remains somewhat subdued. US commercial banks are performing better than European counterparts that struggle to generate returns exceeding their cost of capital. Moreover, recent developments including a potential trade war, the possible end of the equity bull run, heightened global interest rates, and political 1  Financial Times (2017) “New Basel rules on capital hit European banks,” December 7.

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2   Banking polarization have increased economic and financial market uncertainty, making it difficult to predict future bank performance.2 In the light of this rapidly changing operating environment, section 1.2 of this chapter discusses the major changes that have occurred in banking over the last ten years. Section 1.3 covers recent research areas in the banking literature, discussing research on: real effects; capital, liquidity and taxation; systemic risk; monetary policy; FinTech; corporate governance; consumer protection and financial literacy; and financial inclusion. Section 1.4 presents details of the Handbook structure and provides a summary of the constituent chapters.

1.2  Banking: A Decade After The Financial Crisis Ten years on from the Global Financial Crisis, the banking industry has changed dramatically. Prior to the crisis, banking was liberalized, shareholder value-driven, and highly profitable. These trends were halted when governments had to intervene to support and bail out troubled banks, and inject liquidity into markets that had “frozen.” Banks in the US and Europe were most affected as securitized mortgage-backed asset values collapsed in response to declining real estate prices. The banking systems of Japan, Australia, South Korea, and other developed countries were less affected. Emerging market banks in China and India were also relatively unaffected. The policy responses of US and European governments to the Global Financial Crisis were similar, but not identical. These governments introduced: a broad range of guarantees aimed at preventing runs on banks and money market funds; aggressive recapitalization of banks and the wider financial system with expanded deposit insurance coverage; liquidity injections to various markets and institutions; and accommodative fiscal and monetary policy aimed at boosting domestic economic growth. In an important difference, the lender of last resort facility in the US was expanded beyond the commercial banking system to investment banks and funding markets. In order to preserve the domestic housing market, government conservatorship of the government-sponsored enterprises (GSEs) and other policies were put in place to slow the decline in house prices and aid re-financing. In general, the policy actions on both sides of the Atlantic are considered successes in terms of preserving the stability of banking systems and averting a more severe macroeconomic downturn. However, just when financial commentators believed that the Global Financial Crisis was subsiding, several countries in Europe experienced a sovereign debt crisis. Government deficits and debt, exacerbated by the bailouts of troubled banks, triggered a 2  Research suggests that economic policy uncertainty results in increased bank liquidity hoarding in the form of greater bank demand for liquid assets, reduced supply of bank credit, and increased bank demand for deposits (Berger, Guedhami et al., 2018).

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Banking   3 crisis of confidence in certain Eurozone economies, including Greece, Italy, Ireland, Portugal, and Spain (also known as the GIIPS countries). This was reflected in a widening of bond yields and credit default swap spreads for these countries (compared with the benchmark German Bund). The first crisis hit country was Greece in May 2010 when the Eurozone authorities and the International Monetary Fund (IMF) agreed to a €110 billion loan conditional on the implementation of tough austerity measures. Later in the same month, the European Financial Stability Facility (comprising a broad rescue package amounting to $1 trillion) was established with the aim of ensuring financial stability in the Eurozone. Following the Greek bailout, other programs were approved for Ireland (November 2010), Portugal (May 2011) and Cyprus (March 2013). Support provided to the aforementioned countries was relatively successful, with Ireland and Portugal being the first to exit their bailout programs in the summer of 2014. Greece and Cyprus both managed to gain market access to sovereign bond financing over 2014–15. Spain never formally had a bailout package, but did rely on funding from the European Central Bank (ECB) for the establishment of a bank recapitalization fund. The combination of a banking and sovereign debt crisis led to European banks recovering more slowly than US counterparts. Another factor that facilitated a faster banking sector bounce-back in the US is that the legislative process to deal with the crisis and the general de-risking of banks was initiated earlier. The Dodd–Frank Wall Street Reform and Consumer Protection Act of 2010 set a blueprint as to how banks should be re-regulated, such that taxpayers are not liable for future bailouts. However, by late 2018 many of the recommendations of DoddFrank had not been implemented fully.3 A bill passed by Congress in May 2018 rolled back various features of the legislation, especially in areas that impacted small to medium-sized banks. In Europe, the structural reforms proposed in the 2012 Liikanen Report were finalized by the ECOFIN Council in the summer of 2015, and are being introduced in a phased manner. By early 2018, a ban on proprietary trading came into force (the similar US Volker rule was in place in 2015), and national regulators across the EU enforced the legal separation of high-risk trading from core deposit-taking and lending for Global Systemically Important Banks (GSIBs). As in the US, a new bank resolution regime was created in the shape of the Bank Recovery and Resolution Directive (BRRD) of 2015, albeit this has not been fully introduced in all member states. There also remains discussion as to the way in which the new European deposit insurance arrangements, as part of plans for a Banking Union, will be implemented. Big banks in both the US and Europe are also now subject to stress tests to evaluate capital strength resilience to adverse economic shocks. The implementation of Basel III continues as major banks focus on increasing their risk-weighted capital-to-assets ratios. A proposal agreed between central bankers in December 2017 set out tougher Basel III rules relating to capital charges (particularly on trading activities and mortgage assets). These rules will not be implemented until 2022. 3  Crump and Santos (2018) provide a selective review of studies on the effects of the Dodd–Frank Act on the banking industry.

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4   Banking Overall, the new operating environment has forced banks, particularly those deemed systemically important, to reduce risks in order to meet more demanding capital and liquidity requirements, and pass stress test requirements set by regulatory agencies (such as the US Federal Reserve and the European Banking Authority). Exposure to higherrisk (higher regulatory capital) areas (such as investment banking and securities trading) has been reduced. There has been a shift toward lower risk-asset weighted activities such as retail banking and wealth management. Wholesale funding has also reduced in prominence. Bank de-risking has hit revenues, while increased spending on regulatory compliance and organizational restructuring has increased costs. Large banks have also reduced international operations in order to focus on core domestic markets and key overseas activities. Many of the aforementioned pressures continue to have a similar influence on banking business globally. The slowdown in economic growth, the low (and in some cases negative) interest rate environment, coupled with regulatory measures designed to improve safety and soundness have acted as a drag on bank performance. Many European banks do not earn returns sufficient to cover their cost of capital, implying a destruction of shareholder value. Markets continue to be volatile and both banks and regulators still grapple with the complexities of measuring and managing a host of risks. In particular, there is significant interest in the measurement and management of credit, market, liquidity, and operational risks, all of which contribute to systemic risk.4 Of particular recent interest has been the accounting treatment of credit risk indicators such as loan loss provisions and reserves, the fair valuation of financial instruments, as well as issues related to the transparency of off-balance sheet activities. Uncertainty continues to heighten through 2018. Trade wars, Brexit, Italian indebtedness, the possible end of the bull run in equity markets, political polarization (both domestic and international), Middle East pressures, and other factors all add to uncertainty and a less favorable operating environment for banks.

1.3  Emerging Research Themes 1.3.1  Real Effects A substantial body of literature has emerged analyzing the extent to which banks benefit or hinder the development of the real economy (Berger and Roman, 2018). This work has been brought into focus since the Global Financial Crisis. In the US, particular attention is on the Troubled Assets Relief Program (TARP) and its impact on bank lending, real economic outcomes. and systemic risk. Most studies find a positive effect of TARP on 4  While operational risk is usually considered idiosyncratic and without systemic implications, research suggests that operational risk tail events do contribute significantly to systemic risk (Berger, Curti et al., 2018).

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Banking   5 bank lending, particularly for credit to small businesses and risky borrowers, although some find no change in credit, particularly for larger borrowers (Berrospide and Edge, 2010; Black and Hazelwood, 2013; Li, 2013; Duchin and Sosyura, 2014; Montgomery and Takahashi, 2014; Puddu and Waelchli, 2015; Wu, 2015; Berger and Roman, 2017; Bassett, Demiralp, and Lloyd, forthcoming; Berger, Makaew, and Roman, forthcoming; Chu, Zhang, and Zhao, forthcoming). Moreover, evidence suggests that TARP had a positive impact on job creation and reduced bankruptcies (Berger and Roman, 2017), as well as systemic risk (Berger, Roman, and Sedunov, 2018). It also found that banks that received TARP funding received competitive advantages (Berger and Roman, 2015). A sizable quantity of literature has also emerged to augment earlier literature, and this examines the real effects linked to banking sector deregulation in the US.5 For instance, Krishnan, Nandy, and Puri (2015) find that interstate banking deregulation results in improved firm total factor productivity (TFP), while Cornaggia et al. (2015) find that deregulation increased the innovation of private firms that were dependent on external finance. In contrast, Hombert and Matray (2017) find that intrastate deregulation decreased overall innovation. Other studies examine how bank deregulation impacts US households, for instance Kozak and Sosyura (2015) show that interstate banking deregulation encouraged households to participate in the stock market and reduce cash holdings. Celerier and Matray (2016) show that an increase in US bank branch density resulting from deregulation reduced the share of unbanked households among lowincome populations. The non-US literature that investigates linkages between banks and the real economy tends to focus on the impact of credit shocks (resulting from the Global Financial Crisis or the later Euro sovereign debt crisis) on macroeconomic variables such as investment and employment. Carvalho, Ferreira, and Matos (2015) find that bank shocks are reflected in equity valuation losses and investment cuts by firms reliant on external finance (especially those with strong bank-lending relationships). Similarly, Buca and Vermeulen (2017) discover that credit tightening resulted in larger declines in investment in industries more dependent on bank financing. Other studies focus on credit supply shocks in individual countries namely: Germany (Dwenger, Fossen, and Simmler, forthcoming; Huber, 2018); Belgium (Degryse et al., 2018); Spain (Alfaro, García-Santana, and MoralBenito, 2018); Portugal (Amador and Nagengast, 2016); Italy (Cingano, Manaresi, and Sette, 2016) and Japan (Amiti and Weinstein, 2018). In general, the findings of these studies suggest that non-financial firms that are dependent on bank funding exhibit slower growth, investment, and employment after a negative credit shock. Interestingly, Huber (2018) finds that lending reductions influence firms, independent of their banking relationships, and while productivity falls, output and employment remains low even after lending returns to pre-shock levels.

5 Notable examples include Jayaratne and Strahan (1996), Morgan, Rime, and Strahan (2004), Demyanyk (2008), Huang (2008), Beck, Levine, and Levkov (2010), and Rice and Strahan (2010). Kroszner and Strahan (2013) provide an extensive review.

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6   Banking Other related literature focuses on the employment effects of credit supply shocks. A number of papers focus on Spain. Rapid increases in bank lending prior to the financial crisis are found to explain the build-up in employment (and investment) over the same period (Moral-Benito, 2018). Jiménez et al. (2018) examine the influence of dynamic provisioning on bank credit supply, and how this feeds through to employment. They find that dynamic provisioning smooths credit supply, and in bad economic times tends to enhance company performance. Laeven, McAdam, and Popov (2018) examine credit shocks and employment laws in Spain (and Germany), and show that labor market flexibility reduces the negative effect of credit shocks by allowing firms to grow by substituting labor for capital. Bentolila, Jansen, and Jiménez (2018) investigate changes in employment between 2006 and 2010 at Spanish firms with relationships to bailed-out banks (compared to firms that were not exposed to the aforementioned weak institutions). They find that bailed-out banks cut back lending before the bailout, and this adverse credit shock accounts for around 24 percent of job losses at firms linked to weak banks. Other studies that analyze credit shocks and employment focus on: the UK (Franklin, Rostom, and Thwaites, 2015); Italy (Berton et al., 2018) and Germany (Popov and Rocholl, 2018). Franklin, Rostom, and Thwaites (2015) find that a fall in credit supply reduces labor productivity, wages and capital intensity (at the firm level). In their study of Italian firms, Berton et al. (2018) show that a contraction in credit explains about 25 percent of the overall decline in employment (especially for less educated and less skilled workers), and this is concentrated in more levered and less productive firms. Popov and Rocholl (2018) use a sample of German savings banks and their respective links to over 30,000 firms during the financial crisis. They find that firms with relationships with healthy banks were less affected by an adverse credit shock. Following on from the Global Financial Crisis, between 2009 and 2012, the Eurozone faced a sovereign debt crisis. Concerns about the break-up of the Eurozone led Mario Draghi (president of the ECB) to state (in July 2012) that the ECB would do “whatever it takes” to preserve the single currency and Eurozone. Following on from the Draghi statement, the ECB engaged in unconventional monetary policies aimed at reducing yield spreads and strengthening government finances. Acharya, Eisert et al. (2017) investigate the impact of the major Outright Monetary Transactions (OMT) program conducted by the ECB from July 2012 onwards and find that the bond purchase scheme led to a significant decline in the sovereign yields of periphery countries (Greece, Italy, Ireland, Portugal, and Spain). However, they find no impact on employment or investment. Acharya et al. (2018) investigate how the Global Financial Crisis affected the syndicated loan market, and whether this fed through into real economic activity. They find that banks that were more heavily exposed to sovereign debt were less likely to initiate new syndicated loans. This lending reduction reduced investment, employment, and the sales growth of firms linked to the affected banks. De Marco (2018) investigates whether bank exposures to sovereign debt during the crisis affected the real economy. Overall, he finds that realized losses on sovereign debt led to

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Banking   7 a reduction in bank lending. This, in turn, had negative real effects on small and young firms (even in countries that were not under stress). Several studies use Italian data to investigate the real effects of sovereign debt crises. Bottero, Lenzu, and Mezzanotti (2017) use the Greek bailout in 2010, while Bofondi, Carpinelli, and Sette (2018) use the European sovereign debt crisis of 2011. In both cases, these shocks led to a reduction in credit for Italian firms. Bottero, Lenzu, and Mezzanotti (2017) show that the contraction in credit was similar for small and large firms, albeit the investment and employment of small firms only was affected. Bofondi, Carpinelli, and Sette (2018) find that domestic banks were more affected than foreign counterparts, and the credit contraction was mainly determined by an increase in funding costs for Italian banks. Farinha, Spaliarab, and Tsoukas (2018) use Portuguese data (covering the period 2005–14) to investigate how bank shocks (resulting from the Eurozone debt crisis) are transmitted to firms. They find that bank shocks are transmitted to younger, riskier, and generally financially constrained firms. Berthou, Horny, and Mésonnier (2018) use a matched sample of French banks and exporters to investigate how the increase in US dollar funding costs (in the summer of 2011 brought on by the Eurozone debt crisis) affected exporting firms. They find strong evidence that exposed firms (those with larger US dollar liabilities) reduced their exports proportionately more to the US in the twelve months that followed the shock. When there is a credit supply shock, the question arises as to whether firms that have strong relationships with their banks are more “protected” than others. Having a  dependence on bank finance, however, may exacerbate credit shocks (Carvalho, Ferreira, and Matos,  2015). One would expect stronger bank–firm relationships to mitigate (to some extent at least) aggregate credit supply shocks. Beck et al. (2018), in a large cross-country study, find that relationship lending is not linked to credit constraints during a credit boom, and such constraints are alleviated during a downturn. Relationship lending appears to have a stronger influence on small opaque firms operating in regions suffering from more severe economic downturn. Gobbi and Sette (2014) investigate bank-lending relationships in Italy after the Global Financial Crisis, and find that firms that borrow from fewer banks face a lower probability of being credit-rationed. Other evidence examines how shocks to banks affect credit supply. Nakashima and Takahashi (2017) investigate the impact on credit supply when Japanese banks terminate relationships with firms. Bank-driven terminations significantly decrease investment and this is especially the case for firms that find it difficult to establish new relationships. Termination effects are larger than those due to negative credit supply shocks. Cortes and Strahan (2017) identify a pattern whereby US multi-market banks increase lending in response to increased local demand for credit following natural disasters and reduce lending in markets in which they do not operate branches. Koetter, Noth, and Rehbein (2018) examine the influence of a natural disaster (the flooding of the river Elbe in 2013) and conclude that local banks appear to be an effective mechanism to mitigate rare disaster shocks (especially for small and medium-sized firms).

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8   Banking

1.3.2  Capital, Liquidity, and Tax Regulation Since the Global Financial Crisis and the European Sovereign Debt Crisis, policy reforms have focused on bank capital. These reforms include the Dodd Frank Wall Street Reform and Consumer Protection Act (2010) in the US; the Fourth Capital Requirement Directive (2013) in the EU; and Basel III (Basel Committee on Banking Sup ervision, 2010a, 2010b, 2013, 2014, and 2017) internationally. Banks hold capital as a buffer to help prevent distress and failure after losses are incurred. It also serves to mitigate the ex ante moral hazard incentives to take on excessive risks created by deposit insurance, too-big-to-fail policies, and other government safety net protections. Capital can be increased via retained earnings, and the issuance of equity and quasi-equity instruments. If losses occur, they are absorbed from capital, so the more capital the greater bank safety. The role of capital in regulating banks has been extensively studied. There is also extensive evidence related to changes in capital and the resulting impact on bank risktaking. Typically, the level of bank equity (the highest quality type of capital) has largely been indicated as having a negative link with risk (Delis and Staikouras, 2011; Abedifar, Molyneux, and Tarazi, 2013). Furthermore, there is strong corroborating evidence that capital reduces the probability of bank failure and increases the chances of surviving financial crises for banks of all sizes (Cole and White, 2012; Berger and Bouwman, 2013). Demirgüç-Kunt, Detragiache, and Merrouche (2013) and Beltratti and Stulz (2012) find evidence that better-capitalized banks had better stock performance during the crisis. Regulators set minimum capital requirements according to the riskiness of various bank assets and off-balance items. The regulatory classification of the riskiness of bank assets and off-balance sheet activities should accurately reflect individual and combined risks, and thus be sensitive to the portfolio risks faced by banks. Mariathasan and Merrouche (2014) find that reported risk levels were lower following the introduction of new Basel II capital rules. Vallascas and Hagendorff (2013) demonstrate that risk weights assigned to bank assets do not reflect overall bank portfolio risks, while Acharya, Engle, and Pierret (2014) also show that risk-weighted assets have a low correlation with market measures of risk. Banks often hold capital buffers well in excess of regulatory minimum requirements (Berger et al., 2008; Flannery and Rangan, 2008). However, in many cases this excess capital failed to prevent bank failure during the Global Financial Crisis. Flannery and Giaconimi (2015) and Hasan, Siddique, and Sun (2015) identify that, compared with capital market indicators, accounting-based indicators in banking often understate the risks being taken. Another strand of bank capital research examines capital targets and adjustment speeds. Evidence suggests the existence of an optimal (target) capital ratio (Allen, Carletti, and Marquez, 2011), which is theoretically determined by the trade-off between the various costs and benefits of holding capital (including the costs of bank failure due to under-capitalization, tax savings from deposits or debt financing, and so on.) Empirical work has focused on the determinants of target capital ratios (Berger et al., 2008; Fonseca and Gonzalez, 2010; Gropp and Heider, 2010) and the adjustment

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Banking   9 speeds from short- to long-term capital equilibria (Berger et al., 2008; Memmel and Raupach, 2010; Öztekin and Flannery, 2012). Capital adjustment speeds tend to vary country by country and are faster in markets where regulations are tougher. De Jonghe and Öztekin (2015) find in their study of sixty-four countries between 1994 and 2010 that capital adjustment speeds are faster in countries where capital regulations are tougher, have better supervisory monitoring, more developed capital markets, and high inflation. A number of studies investigate how changes in bank capital impact borrowing firms. Laeven and Valencia (2013) study the influence of bank recapitalizations across fifty countries, and find that the growth of more financially dependent firms is linked positively to bank recapitalizations. Aiyar et al. (2014) analyze how changing capital requirements influence the cross-border lending activities of UK banks. They find that increases in bank capital requirements reduce cross-border lending, but this impacts more on lending to other banks rather than credit provided to firms and households. In a similar manner, Fraisse, Lé, and Thesmar (2017) use French loan-level data over 2008–11 to investigate how capital requirements impact corporate borrowing and investment. They find that an increase in capital requirements reduces lending, which in turn leads to a  decline in firm-level investment. Gropp et al. (2019) use the European Banking Authority’s (EBA) capital exercise to investigate how a regulatory request for large banks to boost Tier 1 equity impacted bank lending and real economic activity.6 They find that banks reduced their risk-weighted assets in order to boost Tier 1 capital, which in turn led to a reduction in lending to corporate and retail customers. It also led to lower firm investment and sales growth. Blattner, Farihan, and Rebelo (2017) also use the same EBA event to investigate the impact on Portuguese banks. They find that the increased capital requirements led to a reduction in credit supply to firms, and that this adversely impacts employment and investment. Even if banks have relatively high capital during crisis times, they may not be able to liquidate assets or borrow rapidly if they are faced with extreme short-term financial pressures. A short-term liquidity crisis, such as the inability of banks to pay depositors on demand or rollover other debt, can rapidly turn into a solvency (capital) crisis at an individual bank level, and ultimately turn into a systemic problem (Acharya, Shin, and Yorulmazer, 2011). Therefore, together with capital regulations, regulators have sought to strengthen liquidity standards under Basel III. There is extensive theoretical and empirical literature related to bank liquidity issues (Gertler and Kiyotaki, 2015; Adrian and Boyarchenko, 2018). Other research by Berger and Bouwman (2009) and Berger et al. (2016) has focused on bank liquidity creation, and how this varies over cycles and with regulatory shocks. Iyer et al. (2014) investigate the impact on Portuguese lenders of the interbank freeze during the financial crisis. They find that banks more dependent on interbank funding reduced their lending the most. The impact of this lending cut was greater for small firms

6  The EBA exercise, announced in October 2011, required large European banking groups to meet a higher Tier 1 capital ratio by June 2012.

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10   Banking with weak banking relationships. De Jonghe et al. (2018) also investigate the influence of a liquidity shock on over 160,000 bank–firm relationships in Belgium. The authors find that a negative funding shock led banks to reallocate credit toward lower-risk firms, and to industries in which they were more specialized. Other studies investigate the influence of central bank liquidity injections on credit supply and the real economy. Berger et al. (2017) find that the Federal Reserve’s supply of bank liquidity through the expanded Discount Window and Term Auction Facilities (TAF) resulted in very large increases in bank lending. Daetz et al. (2018) investigate the impact of the ECB’s Long-Term Refinancing Operations (LTROs, where the ECB lent to Eurozone banks at low interest rates) on firm-level investments. They find that Eurozone firms did not increase investments, even when their banks held LTRO funds for a long period. The authors argue, however, that the liquidity injections enabled firms to maintain investments. Carpinelli and Crosignani (2017) investigate the same ECB financing activity and its impact on Italian banks. They find that credit supply is maintained as a result of the liquidity injection, and this positively impacts firms. Compared to the literature on the impact of capital and liquidity regulation, evidence relating to the effect of taxation on bank behavior is relatively scarce. Available evidence appears to suggest that bank taxation can change bank behavior such that depositors and borrowers are affected as banks seek to shift any burden of additional costs by reducing credit supply, lowering deposit rates, or increasing loan rates. Furthermore, changes in the overall tax treatment of debt can have consequences for banks’ capital structure and the extent of reported profitability and losses. Early evidence suggests that taxes on domestic and foreign banks alike are, to some extent, passed on to banks’ customers, leading to higher pre-tax profitability (DemirgüçKunt and Huizinga, 2001). Other evidence—for example, Chiorazzo and Milani (2011) for large samples of European banks, and Capelle-Blancard and Havrylchyk (2014) for Hungary—also find that banks are able to shift most of their respective tax burdens onto customers. Banerji et al. (2018) investigate the impact of taxes on the behavior and performance of Japanese banks following an unexpected and significant introduction of a tax on the gross profits of large banks operating in Tokyo. The authors find that this tax caused affected banks to increase both net interest and fee margins. Further analysis reveals that depositors were most affected by adjustments to interest and fee rates at banks following the imposition of the tax. The imposition of the Tokyo bank tax reduced the lending of affected banks relative to their non-affected counterparts. Contrary to the findings of the aforementioned studies, other studies find no evidence of a change in banks’ loan or deposit rates following the introduction of taxes (Capelle-Blancard and Havrylchyk, 2014; Buch, Hilberg, and Tonzer, 2016). Instead, it is the banks that absorb the tax burden. Lin and Pennachi (2018) find that the burden of bank taxation is passed through to retail depositors in markets where there is excess retail savings relative to retail lending opportunities. In contrast, the burden is passed onto retail borrowers in a market where retail lending exceeds retail savings. Han, Park, and Pennacchi (2015) and Gong, Hu, and Ligthart (2015) find that corporate income taxes create incentives for banks to securitize loans.

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Banking   11 Taxes can also influence bank capital structure as these lead banks to prefer borrowing over financing by equity. The deductibility against corporate income tax of interest on debt, but not on equity, creates a tax preference for debt over equity finance. There is strong evidence that this leads to higher leverage for non-financial companies (Claessens, Keen, and Pazarbasioglu, 2010). Keen and de Mooij (2016) investigate the relationship between corporate income tax and bank leverage decisions, and find evidence of tax distortions on bank financing. Results point to a tax sensitivity of banks that is comparable to that of non-financial firms. In other words, favorable tax treatment of debt causes banks to become more highly leveraged. Schepens (2016) provides evidence that suggests that tax shields on equity can have a significant impact on bank stability. A reduction in tax discrimination between debt and equity funding leads to better-capitalized financial institutions. Consequently, the removal of tax shields on debt may contribute to better bank capital regulation.

1.3.3  Systemic Risk The fact that the Global Financial Crisis was system wide has encouraged researchers to look at “new” ways to measure systemic risk. The Conditional Value at Risk, CoVaR, proposed by Adrian and Brunnermeier (2016), measures a financial institution’s contribution to systemic risk and its contribution to the risk of other financial institutions using a VaR (Value at Risk) methodology. The latter looks at extreme losses over certain time horizons using various probability distributions. CoVaR uses this methodology to examine relations between financial institution stock price and credit risk indicators and for the system overall. The measure can therefore be used to identify systemically important institutions. Because measuring CoVaR does not rely on contemporaneous price movements, it can also be used as an indicator to help identify the build-up of systemic risk. Brownlees and Engle (2017) develop SRISK, which measures the capital shortfall of an institution conditional on a severe market decline, and is estimated as a function of bank size, leverage, and risk. The SRISK measure provides a good indication of the systemic importance of institutions in the US. Acharya, Pedersen et al. (2017) model risk based on financial sector undercapitalization. Each financial institution’s contribution to systemic risk is measured as its systemic expected shortfall (SES), namely, the propensity of a bank to be undercapitalized when the system as a whole is undercapitalized. SES is a weighted sum of market leverage (LVG) and the bank’s marginal expected shortfall (MES), namely losses in the tail of the system’s loss distribution (for instance, one indicator of MES is the average return of a bank’s equity during the 5 percent worst days of the overall market return).7

7 Other systemic risk measures have been developed by Kritzman et al. (2010), Kritzman and Li (2010), Billio et al. (2012), Allen, Bali, and Tang (2012), and Giglio, Kelly, and Pruitt (2016).

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12   Banking

1.3.4  Monetary Policy Since the Global Financial Crisis, policymakers have faced a challenging economic situation characterized by economic stagnation and deflation. As a first monetary policy response, central banks cut interest rates aggressively through conventional accommodative monetary policies. However, when interest rates approached the zero lower bound (ZLB) without producing the hoped-for effects on nominal spending and inflation, many central banks implemented a range of unconventional monetary policies (UMP) including Large Scale Asset Purchases (LSAPs), in the form of Quantitative Easing (QE) as well as policy rate forward guidance (Borio and Zabai, 2016). UMP took a step further from 2012 onwards when several countries/regions (Denmark, the Eurozone, Hungary, Norway, Sweden, Switzerland, and Japan) implemented negative interest rate policy (NIRP) in order to provide further economic stimulus to weakened economies (see Bech and Malkhozov, 2016; Bräuning and Wu, 2017; Demiralp, Eisenschmidt, and Vlassopoulos, 2017). Heider, Saidi, and Schepens (2017) find that when policy rates remain positive, deposit rates closely track official rates. However, when policy rates turn negative, banks that rely on deposits are reluctant to reduce deposit rates fearing a loss of their funding base. In cases in which sticky deposit rates compress lending margins, banks tend to shift activities toward fee-based services. Claessens, Coleman, and Donnelly (2018) find that in environments with persistently low interest rates, both margins and profits are depressed. Ball et al. (2016) survey recent developments of monetary policy transmission in NIRP-adopter countries. They argue that policy rate cuts below zero are generally transmitted to bank lending rates, although sluggishly. They also conclude that there is no clear relationship between NIRP and bank credit expansion. Arteta et al. (2016) suggest that lending rates generally decline under NIRP, particularly in countries with greater bank competition, but pass-through is only partial due to downward rigidities in retail deposit rates (reflecting the importance of retail deposits as a source of bank funding). Fiordelisi and Ricci (2016) examine the influence of monetary policy announcements on the stock price of globally systemically important banks (G-SIBs) between June 2007 and June 2012. The authors find that monetary policy interventions (whether restrictive or expansionary) have a positive impact on returns. In contrast, bank failures and bailouts generate strong negative returns. Alcaraz et al. (2018) find that ECB monetary policy interventions led to the improved lending standards of European banks.

1.3.5 FinTech There has been an explosion in commercial interest in technology firms providing financial services. Both independent and bank-based FinTech developments have been growing rapidly. A recent survey by the EBA (2017) finds that there are over 1,500 firms operating in the EU that can be regarded as FinTech operators. The aforementioned survey defines firms as operating in the FinTech space if they have: only online distribution

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Banking   13 channels; only mobile distribution (mobile or digital wallets); are value transfer networks; employed technology to enable trading on a high frequency basis; copy trading (technology used to emulate investors behavior); venture capital activities (whereby technology is used to enable buying/holding/selling venture capital, and technology enables exchanging venture capital into fiat currency); biometric technology (for instance, authentication); data analytics; electronic personal financial management tools; robo-advice; online platforms (for example, to enable crowdfunding or peer-to-peer transfers); cloud computing; data aggregation services; distributed ledger technology (for example, blockchain); customer digital identification; smart contracts; and RegTech (using new technology to enhance regulatory processes). The EBA (2017) survey notes that the most popular area where FinTech firms operate is in the payments, clearing, and settlements area. Deloitte (2017) report than in the US there are around 4,500 FinTech firms, of which 2,040 operate in banking and capital markets areas (the most popular areas being in payments, and deposit and lending businesses) as well as 1,500 in InsurTech. Most of these have been set up since 2015. Much of the interest around the FinTech business is driven by the emergence of cryptocurrencies that have the underlying distributed ledger (updated by each participant across a large network) mainly based on a Blockchain system. Bitcoin is the largest and most famous cryptocurrency. As of October 21, 2018 Coinmarketcap.com listed 2,112 cryptocurrencies of which 1,710 had details of the circulating supply. Total market capitalization of all these currencies stood at $211 billion. The three largest are Bitcoin (54 percent of total market capitalization); Ethereum (10 percent) and XRP (9 percent). The underlying Blockchain (or related) technology has the advantage of providing a distributed ledger and strong cryptographic security features that enable users to access and validate data and undertake transactions and clear them rapidly. This means that the new technology could revolutionize any area that involves the tracking and processing of transactions and payments. Many banks see this new technology as a way of redesigning their business models, thus improving the efficiency of their systems. Legacy systems are likely to be gradually replaced with technology based on distributed ledger technology and Blockchain. Efficiency and the speed of their transactional capabilities are also likely to be enhanced. This is all good for banks and their customers, although the new independent operators pose a potential competitive threat to incumbent banks. KPMG (2018) estimate that in the three years up to the end of 2017, some $122 billion was invested in global FinTech developments. During 2017, the report notes that both InsurTech (technology firms offering insurance services) and Blockchain saw record ­levels of investment and deal volume, with InsurTech accounting for US$2.1 billion across 247 deals and Blockchain generating $512 million of investment across 92 deals. The US accounted for almost half of the full-year 2017 global total invested in the FinTech sector. Catalini and Gans (2018) find that distributed ledger technologies like Blockchain are likely to help create new markets. Others such as Cong and He (2018) suggest that Blockchains could also be used to facilitate collusion. There is a modest amount of literature that looks at the volatility of cryptocurrencies that trade on unregulated markets

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14   Banking that may be more susceptible to manipulation (Griffin and Shams, 2018). However, these currencies do provide an innovative mechanism for start-up financing through initial coin offerings (ICOs) (Howell, Niessner, and Yermack, 2018).8

1.3.6  Corporate Governance and Culture Misaligned managerial incentives in the financial sector, including excessive compensation practices, are viewed by many as a key contributor to the Global Financial Crisis (Bebchuk, Cohen, and Spamann, 2010). Evidence before and during the crisis does find that bank CEOs who followed strategies more aligned to shareholder wealth creation did appear to fare worse when the crisis hit (Fahlenbrach and Stulz,  2011; Mehran, Morrison, and Shapiro, 2012). Other empirical evidence also finds that banks that took on greater risk led to more volatility in earnings but not necessarily higher performance (DeYoung, Peng, and Yan, 2013). Various regulations have been introduced to limit compensation excesses. Strict rules are those introduced in Europe under the Fourth Capital Requirement Directive (2013). This states that the variable part of total compensation cannot exceed 100 percent of the fixed component. The UK introduced a Remuneration Code in 2009 (FSA, 2009). The main element was to force executives to defer a larger proportion of their bonuses with the stipulation that at least 50 percent of their bonus must be deferred for three years. The aim of the UK rules is to encourage bank executives to have a longer-term perspective. The Dodd–Frank Wall Street Reform and Consumer Protection Act (2010) in the US introduced an advisory vote on executive compensation (Say-on-Pay, SOP). Assessments of these regulations are now emerging. Kleymenova and Tuna (2016) examine the influence of the UK and EU regulations and find that the market reacted positively to the UK Remuneration Code, but negatively to the EU bonus cap. UK banks also deferred more bonuses and reduced risks. Evidence on Europe is further confirmed by Díaz Díaz, García-Ramos, and García Olalla (2017), who also find that investors negatively perceived the EU bonus cap legislation. Another area that has interested bank researchers relates to the monitoring capabilities of boards (and in particular their characteristics such as board size, the proportion of independent directors, director experience, and gender). There is evidence in banking that board size is positively linked to performance (Adams and Mehran, 2012) and that banks with more independent directors incurred bigger losses during the Global Financial Crisis (Adams, 2012; Erkens, Hung, and Matos, 2012). Minton, Taillard, and Williamson (2014) for instance, find no link between board expertise and the performance of US banks over the crisis. Another area discusses gender issues. Palvia, Vähämaa, and Vähämaa (2015) find that US banks with female CEOs hold more capital 8  Academic evidence on FinTech-related issues to date is rather limited. Useful discussions can be found in Berg et al. (2018) who examine the use of digital footprints for credit scoring; Franks, SerranoVelarde, and Sussman (2018) who examine marketplace lending; and Fuster et al. (2018) who examine the effects of machine learning in credit markets. A review of other selected studies can be found in Chapter 9, this volume.

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Banking   15 after controlling for asset risk and other features. They also find that smaller banks with female CEOs and board Chairs were less likely to fail during the crisis. In contrast to this, Berger, Kick, and Schaeck (2014) study German savings banks and find that those with a higher proportion of female board members tended to be riskier, possibly because females tend to have less experience and/or are appointed to the boards of more problematic banks. The aforementioned evidence suggests that existing governance arrangements in some cases appear to create a culture where excessive risk-taking and even fraud are condoned (Thakor, 2019). This is evidenced by the large number of cases of fraud and misconduct following the financial crisis (Cohn, Fehr, and Maréchal, 2014, 2017; Nguyen, Nguyen, and Sila, forthcoming).

1.3.7  Consumer Protection There is growing interest in how the legal environment influences bank behavior. For consumers of retail financial services, this relates to customer protection legislation, which typically has been slow to develop compared to legislation covering non-financial industries. The Dodd–Frank Act (2010) set up the Consumer Financial Protection Bureau in 2010 to strengthen consumer protection in the US financial sector. Similar moves have also been made in Europe, although consumer protection issues tend to be national and not harmonized across EU countries. The growing interest in this area is very much related to concern that some banks mis-sell products and services to their clients or engage in other bad practice that takes advantage particularly of uninformed customers. Key recent cases include the Wells Fargo fraudulent account opening (1.4 million cases), the mis-selling of payment protection insurance (PPI) in the UK, and other retail investment products elsewhere in the EU. The literature on the effects of consumer protection in the banking sector is somewhat scarce. Pasiouras (2018) uses an extensive cross-country sample from the World Bank and finds that consumer protection laws tend to reduce the cost of intermediation for banks located in developed economies. In contrast, in developing countries such legislation tends to increase intermediation costs. Lumpkin (2010) suggests that for consumer protection to be effective, financial institutions need to develop appropriate systems and regulators should impose tougher penalties to address mis-selling, fraud, or misconduct. Wehinger (2012) points out that financial consumer protection has not received appropriate attention from regulators, and that it is as important as enhancing efficiency and competition.

1.3.8  Financial Inclusion Financial inclusion plays a critical role in reducing poverty and boosting prosperity (Demirgüç-Kunt and Klapper, 2013; World Bank, 2014). Access to finance provides individuals with resources to meet their financial needs, such as saving for retirement,

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16   Banking investing in education, and purchasing a house. Financial exclusion, in contrast, can exacerbate economic disadvantages that may lead to social exclusion. Globally, there are around 2 billion working-age individuals without access to basic financial services. The IMF and World Bank have taken the lead by reporting on survey data. The IMF has built the Financial Access Survey database (FAS) that includes more than 150 series relating to financial inclusion for up to 189 economies spanning the period 2004–15. This information is obtained from banks, microfinance institutions, and other financial firms so can be considered supply-side information. In contrast, the World Bank has built the Global Financial Inclusion Database (FINDEX), which provides 100 indicators (shown by gender, income, and age) of financial inclusion for more than 140 countries, most recently for 2014—this information is obtained from individual survey data so is demand-side based. Several studies use these two databases to examine financial inclusion (Beck, Demirgüç-Kunt, and Pería, 2008; Demirgüç-Kunt and Klapper, 2013; Naceur, Barajas, and Massara, 2015). These studies generally tend to find that those most likely to be excluded tend to be poor, have low levels of education, and are more likely to be women. More recent studies use indexes of inclusion to take account of its multidimensional nature (Cámara and Tuesta, 2014).

1.4  Book Structure and Chapter Summaries 1.4.1  The Theory of Banking Part I of this Handbook comprises six chapters and examines why banks exist, how they function, the risks to which they are exposed and how these are managed, and their legal, organizational, and governance structures. In Chapter 2, Franklin Allen, Elena Carletti, and Xian Gu examine the role of banks in ameliorating informational asymmetries that can arise between lenders and borrowers, providing intertemporal smoothing of risk, and contributing to economic growth. The authors note that banks play a crucial role as delegated monitors in order to ensure that firms make effective use of loans made to them. Furthermore, banks play a central role in diversification of risks and smoothing consumption. However, banks are by their very nature fragile, and small shocks can have large effects on the financial system and the real economy. Nations around the globe have very different degrees of development of their stock and bond markets, and therefore rely on their banks to greater or lesser extents. In general, Eurozone countries have small but rapidly developing stock markets. Bank lending relative to GDP is substantial, and bond markets play an important role in the financial system. The UK has a large stock market and a large banking sector, but the UK bond

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Banking   17 market is relatively small. The US banking sector is small in relation to the size of the US economy, but both the stock market and the bond market are relatively large. Japan has a relatively large banking sector and highly developed capital markets. Competition among banks, non-banking financial institutions, and financial markets has intensified in recent years. This competition has led to the transformation of banks, and the growing complementarities between banks and capital markets. In Chapter 3, Arnoud Boot and Anjan Thakor examine the implications of these changes for the recent evolution of financial institutions and markets, and for regulatory design. The authors illustrate how banks depend on the capital market for sources of revenue, for raising equity capital and for risk management, while capital market participants rely increasingly on banks’ skills in financial innovation and portfolio management. The increased integration of banks with financial markets raises domestic and cross-border financial stability concerns, which in turn has implications for the design of domestic and international financial system regulation. As commercial banks have diversified into investment banking, a number of large systemically important financial institutions (SIFIs) have emerged. In Chapter 4, Jacopo Carmassi and Richard Herring examine the phenomenon of global systemically important banks (G-SIBs) and examine how their complexity has changed since the onset of the financial crisis. The authors note that taxation and regulation have increased corporate complexity, and this continues to hinder efforts to supervise G-SIBs. Some G-SIBs have simplified their organizational structures and reduced their size in recent years. However, many others have grown more complex and larger. Higher capital requirements, improved bank resolution schemes, and living wills may help in supervising G-SIBs, but there is an additional need for enhanced transparency and market discipline. In order to reflect differences in capital structure, opacity, and complexity as well as their importance to the wider economy, the corporate governance of banks should be different from that of non-financial firms. In Chapter 5, Jens Hagendorff focuses on aspects of corporate governance and culture in which banks should differ from nonfinancial firms. He provides an extensive overview of literature related to executive compensation, board composition, ownership, and risk management. The main observation from his chapter is that bank governance structures geared to aligning the interests of shareholders and managers lead to higher risk-taking. The chapter posits various ways to address this problem and argues that the Global Financial Crisis provides an opportunity for academics and policymakers alike to rethink the corporate governance of banks. Banks are exposed to credit risk, liquidity risk, interest rate risk, market risk, and operational risk. For any bank, the measurement and management of these risks is of the utmost importance. In Chapter 6, Linda Allen and Anthony Saunders describe the widely used Value at Risk (VaR) method of risk measurement. Accurate risk measurement enables banks to develop risk management strategies, using derivative instruments such as futures, forwards, options, and swaps. The recent financial crisis shows that we still have a lot to learn about risk measurement and risk management. A greater understanding of how to measure and manage systemic risk is required.

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18   Banking One of the key functions of the banking sector is to create liquidity. In Chapter 7, Christa Bouwman provides a review and synthesis of the theoretical and empirical literature on bank liquidity creation. The author provides a discussion of the impact on liquidity creation of new approaches that combine originate-to-hold with originate-todistribute business models, and how this has implications for regulation and supervision. The analysis raises interesting research questions concerning the design of both liquidity and capital requirements for traditional and shadow banks. It is also important to investigate how liquidity and capital interact, as inefficient bank bailouts may occur because regulators cannot easily distinguish between insolvency and illiquidity.

1.4.2  Activities and Performance Part II of the book comprises ten chapters dealing with bank performance and operations. A number of issues are assessed, including efficiency, technological change, globalization, and the ability to deliver small business, consumer, and mortgage lending services. Securitization and shadow banking are also examined. The crucial roles that banks play in operating the retail and wholesale payments systems are also discussed. In Chapter 8, Joseph Hughes and Loretta Mester outline the different approaches used to examine the efficiency and overall performance of banks. The authors discuss various structural and non-structural approaches to efficiency measurement. The structural approach requires a choice of the underlying production features of banking (intermediation, production, value-added, or other) and the specification of cost, profit, or revenue functions, from which (using various optimization techniques) one can derive relative performance measures. The role of risk is important in banks’ production features and therefore should be included in evaluations of bank performance. The authors show that research which does not incorporate risk reports little evidence of scale economies at very large banks, while the results of other studies that control for differing levels of risk across banks tend to find that there are scale economies at the largest banks. Technological advances and financial innovation have led to fundamental changes in the nature of banking over the last 25 years. In Chapter 9, W. Scott Frame, Larry Wall, and Lawrence White focus on innovations in banking products (subprime mortgages, retail services including the growth of debit cards, online banking, and the use of prepaid cards) and processes (automated clearing houses, small businesses credit scoring, asset securitization, and risk management). In addition, various new organizational forms, such as Internet-only banks and the establishment of Section 20 securities subsidiaries are discussed. They discuss features of recent FinTech developments including the distributed ledger technology and Blockchain. Financial and technological innovations have affected bank performance and the wider economy. However, the authors note that there is still scant research on why financial innovations take place, and suggest that this is an area future research could focus on.

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Banking   19 Payment systems were relatively unaffected during the recent financial crisis. In Chapter 10, David Humphrey analyzes the use of retail payments systems (cash, checks, debit cards, credit cards, automated clearing houses), and wholesale payment systems (wire transfer networks) across countries. The costs and benefits of different systems to the banking system are highlighted, and policy avenues are explored with respect to both retail (privacy issues, card interchange fees) and wholesale payment systems (integration of back-office systems and uses of large value payment systems, systemic risk). Banking organizations are characterized by different ownership and operational features. In many countries, large private banks (typically publicly listed) compete with different types of banks. The role and features of community and mutual banks are discussed in detail by Dasol Kim and Donal McKillop in Chapter 11. They note that changes in the regulatory environment and technological advances have dramatically changed the competitive landscape for community banking institutions. While only accounting for a fraction of the overall size of the banking industry’s assets, community banks are dominant, in terms of numbers around the world, for a broad range of depository institution types, including commercial banks, savings banks, cooperative banks, and credit unions. The steep decline in the number of community banks in recent times has raised questions on the potential consequences associated with the gradual disappearance of these institutions. The authors consider factors that contributed to the growth and decline of these types of banks and how they can maintain competitiveness in the current economic climate. The last two decades have witnessed rapid growth in Islamic finance and banking around the world. Global Islamic financial assets in the banking, capital markets, and insurance sectors have reached over $2 trillion and more than 350 Islamic banks are operating worldwide. In Chapter 12, Narjess Boubakri, Ruiyuan (Ryan) Chen, Omrane Guedhami, and Xinming Li discuss the development of Islamic banking and its main features. Islamic banking refers to banking operations constrained by Sharia law. Their chapter provides a brief review of the growth of Islamic banking along with its key characteristics and common financial products. They also review the extensive empirical literature that analyzes the differences between Islamic and conventional banking. In Chapter 13, Robert Lensink and Erwin Bulte examine ways in which microfinance programs can be made more effective. The authors discuss features of the microfinance industry and point to two important reasons why the impact of several microcredit programs is lower than expected: (1) the rigidity of credit contracts; and (2) the human capital of end users. As reforming contract terms and building human capital through business training and technical assistance are costly, the authors argue that perhaps subsidies are needed. The chapter focuses on studies dealing with end users, and the authors pay specific attention to the evolving discussion on group lending and the role of joint liability to reduce asymmetric information problems and improve repayment rates. They also discuss the literature focusing on the recent shift of several microfinance institutions to individual lending, and the related trend toward commercialization of microfinance.

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20   Banking Banks are the single largest provider of external finance to small businesses. In lending to such firms, banks use a number of different lending technologies to overcome a lack of publicly available financial information. In Chapter 14, Allen Berger and Lamont Black discuss bank small business lending. In particular, they cover how some of the technologies used to make lending decisions to small business have evolved over time from relationship-based models relying on qualitative soft information to more sophisticated models based on different combinations of quantitative hard and qualitative soft information. They also examine the effects of banking industry consolidation and technological progress on the use of the lending technologies and their effects on small business credit. They find that consolidation and technological progress and their interactions appear to have resulted in banks placing a greater reliance on hard information to make lending decisions. This is reflected in greater distances between banks and their small business clients. Mortgage lending is an important part of the banking industry. In Chapter 15, Andreas Lehnert and Alex Martin note that deregulation and process and product innovations allowed banks to separate origination, funding, and servicing functions. This enabled small-scale financial institutions to originate mortgages, and securitize them and sell securities backed by them to other financial institutions and investors. This unbundling process introduced tensions among borrowers, mortgage funders, investors, and regulators. Since the Global Financial Crisis, underwriting standards have increased. The chapter also assesses recent changes in regulation aimed at promoting financial stability in mortgage markets. Securitization has become an integral part of modern financial systems by alleviating credit constraints and allowing transfer of certain risks. However, since the Global Financial Crisis, securitization activities have diminished. In Chapter 16, Barbara Casu and Anna Sarkisyan provide an extensive review of the theoretical and empirical research that has been conducted to explain why banks securitize, and what the effects of such activities are on consumers, financial institutions, and the wider economy. The authors point to a number of imperfections, including misaligned incentives and opacity. Recent measures to tackle misaligned incentives and information asymmetries to improve the quality of the credit rating process are also discussed in detail. In Chapter 17, Tobias Adrian, Adam Ashcraft, Peter Breuer, and Nicola Cetorelli examine shadow banking. The official definition of shadow banking as formulated by the Financial Stability Board (FSB) is “the system of credit intermediation that involves entities and activities outside the regular banking system.” This chapter notes that the transformation of the credit intermediation process from a single to multiple financial institutions not only resulted in a reduction in the costs of intermediation, but also boosted the growth of shadow-banking activities that take place outside the confines of the traditional banking system. The authors explore the underlying causes for the emergence of the shadow-banking industry, and how connections to the traditional financial system can increase systemic risk. Recent developments, including agency mortgage real estate investment trusts (REITs), reinsurance, tri-party Repos, money market mutual funds, and developments in Chinese shadow banking are also discussed.

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Banking   21

1.4.3  Regulatory and Policy Perspectives Part III of this Handbook comprises eight chapters that examine the various roles of central banks, regulatory and supervisory authorities, and other government agencies which directly impact the banking industry. Central banks execute monetary policy, which operates to a large degree through the banking system; act as a lender of last resort; and perform various other functions such as operating parts of the payments system. The scale and scope of central bank activities has increased dramatically since the onset of the recent financial crisis. In order to prevent widespread or systemic bank failure, government agencies provide safety-net protection such as explicit or implicit deposit insurance, unconditional payment system guarantees, and takeovers of troubled institutions. In part to protect against systemic failure, and in part to offset some of the perverse incentive effects of government safety net protection, government authorities also engage in prudential regulation and supervision, and set policies concerning bank closure. Competition policy aimed at preventing abuses of market power also directly affect the banking industry. So, too, does explicit and implicit government policy on foreign entry into domestic markets and foreign ownership of domestic industry. The role of central banks within the financial system has been influenced by successive monetary and financial crises. In Chapter 18, Frederic Mishkin examines issues related to modern central banking. The chapter examines how central banking has evolved in recent decades, covering central bank governance, monetary policy, and financial ­stability policy. The chapter discusses the academic literature on how central banks should operate, which the author refers to as “the science of central banking.” This is then used to provide a framework for understanding how modern central banks conduct monetary and financial stability policies. The author notes that central banks now focus far more on establishing a strong nominal anchor, which has resulted in changes in central bank governance so they are more insulated from short-term political considerations. Central banks are also now far more transparent than they were in the past, requiring that they communicate far more clearly to the public and the markets. The Global Financial Crisis and the recognition of the constraints posed by the zero lower bound on the policy rate has led central banks to increase their focus on financial stability and to develop new tools to promote financial stability and to conduct unconventional monetary policy. The author concludes that central banking has entered a brave new world in which challenges have become greater and the conduct of policy has become more complex. Central banks also play an important role as lender of last resort to banks experiencing liquidity problems. Lending of last resort provides troubled banks with liquidity and allows them to escape market discipline. In Chapter 19, Xavier Freixas and Bruno Parigi examine this lender of last resort function and its relationship with bank closure policy. The difficulties in distinguishing liquidity and solvency shocks are highlighted. The lender of last resort function is usually handled by the central bank, while scrutiny of bank closure is commonly the responsibility of a separate agency, often the deposit insurer.

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22   Banking The financial crisis highlights the complexity of the lender of last resort function, which encompasses issues relating to monetary policy, bank supervision and regulation, and the operation of the interbank market. The authors posit that the lender of last resort function should be an integral and interdependent part of an overall banking safety net, which encompasses a deposit insurance system, a system of capital regulation, and a set of legal procedures to bail out or liquidate troubled banks. During the Global Financial Crisis, many governments used taxpayer funds to bail out distressed banks and stabilize the banking system. Such actions led to increased government deficits and debt, and reduced market discipline. In Chapter 20, Raluca Roman investigates the benefits and cost of bank bailouts, and discusses developments in bank resolution since the Global Financial Crisis, including bail-ins. She notes that new bailin tools appear to improve market discipline and lead to financial stability without the need to use taxpayer funds. However, bail-ins are not without limitations, and can lead to undesirable outcomes, including deteriorations in conditions facing bank borrowers and other stakeholders, and resultant declines in investment and employment. Deposit insurance is intended to prevent “runs” on individual banks by depositors. It also limits losses to depositors in the event of bank failure, and reduces the risk that a run on one bank might undermine confidence in others through contagion effects. The authors argue that a flawed deposit insurance system might cause more harm than good if moral hazard created by the insurance results in excessive risk-taking or recklessness on the part of banks. In Chapter 21, Deniz Anginer and Asli Demirgüç-Kunt provide a detailed analysis of deposit insurance guarantee systems. They note that deposit insurance is now an accepted and widely adopted policy to promote stability in the banking sector. It has long been part of the International Monetary Fund’s best practice recommendations to developing countries. The Global Financial Crisis increased the focus on deposit insurance, with many countries either introducing or significantly increasing existing deposit insurance coverage. The crisis also highlights both the strengths as well as some of the shortcomings of deposit insurance schemes. All in all, the authors suggest that (apart from a few exceptions) there have not been contagious runs by retail depositors, despite the devastating impact of the crisis on major economies. The empirical evidence points out the importance of design features and shows that poorly designed schemes can increase the likelihood that a country will experience a banking crisis. To absorb unforeseen risks and reduce moral hazard, regulators require banks to hold capital. Standards developed by the Basel Committee on Banking Supervision have gone some way to aligning such capital requirements with banks’ risk profiles. In Chapter 22, Mark Van Der Weide and Jeffery Zhang examine the rationale for capital regulation, and describe the key features of the Basel Accords. The authors focus on the theoretical and empirical underpinnings of capital regulation, and the challenges in rating the riskiness of assets contained in bank portfolios. In the final parts of the chapter, the authors describe the development and implementation of Basel III and discuss ongoing Basel Committee initiatives. As banking has become increasingly complex, the usefulness of the traditional tools of supervision in monitoring risk-taking by banks has been called into question.

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Banking   23 The efficient markets hypothesis suggests that private investors can identify the risks associated with investing in shares of banks and other complex financial institutions, and thus exert market discipline. However, the recent financial crisis led some commentators to assert that market participants failed to exert discipline. In Chapter 23, Mark Flannery and Rob Bliss define the concept of market discipline and explain its importance. Particular attention is paid to the theory and practice of both direct and indirect channels of market discipline and especially the role of equity and bond markets. Since the recent financial crisis, regulators have sought to realign incentives in order to restore market discipline in the banking and financial sector. The authors note that proponents of market discipline still argue that sophisticated market participants are best placed to assess complex risks being undertaken by banks and other firms, and may provide the ultimate sanction against such firms taking on excessive risk. However, this traditional view is based on weak theoretical and empirical foundations and the authors contend that behavioral factors influence market participants, particularly during crisis times, making market discipline substantially less effective. Competition in banking is important, because any form of market failure or anticompetitive behavior on the part of banks has far-reaching implications for productive efficiency, consumer welfare, and economic growth. In Chapter 24, Hans Degryse, Paola Morales-Acevedo, and Steven Ongena review the methods used by researchers and policymakers to assess the form and intensity of competition in the banking industry. The relative merits of market structure and “non-market structure” indicators such as the Panzar-Rosse H-statistic, the Lerner index, and the Boone indicator are discussed. The chapter notes how the literature has developed along two main themes. First, this relates to studies that model market structure as endogenous. A second development looks to capture the special nature of banking competition by also looking at non-price dimensions of banking products. The authors also illustrate how regulation and information sharing between banks impacts on bank competition. The effects of competition on bank performance, credit availability, and risk are also examined. Increased competition in liberalized banking markets can have a positive impact by driving down prices and fees for financial services, but excessive competition can potentially lead to excessive risk-taking as well as aggressive selling and other bad practice. Uninformed consumers are likely to be poorly placed to learn rapidly about such bad practice because of various behavioral biases that can distort financial decision-making. Many consumers have low levels of financial literacy and this makes it difficult for them to make informed decisions. In Chapter 25, Gregory Elliehausen discusses financial ­literacy and consumer protection issues in financial services. The chapter reviews research in behavioral economics and financial literacy that raises concerns that consumers lack competence to make complex financial decisions. Given evidence from behavioral economics and studies on financial literacy, the author concludes that ­neither existing behavioral evidence nor conventional economic evidence supports a general conclusion that consumers’ financial decisions are not rational or that markets do not work reasonably well.

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24   Banking

1.4.4  Macroeconomic Perspectives Part IV of the book comprises five chapters discussing the interactions among banks, firms, and the macroeconomy. This part of the book includes a discussion of the determinants of bank failures and crises, and the impact on financial stability, institutional development, and economic growth. In Chapter 26, Olivier de Bandt and Philipp Hartmann present a comprehensive review of systemic risk in banking in order to understand how extreme financial crises cause severe negative effects to the macroeconomy. A clearer understanding of the causes and consequences of systemic risk also helps policymakers formulate better banking regulation, prudential supervision, and more effective crisis management tools. The first part of the chapter outlines key analytical elements of systemic risk and brings them together as a coherent working concept that can be used as a benchmark for policies, ensuring the ­stability of financial systems. Three important sources of systemic risk are identified as contagion effects, aggregate shocks exogenous to the financial system, and the endogenous build-up and unraveling of widespread financial imbalances. The authors then go on to discuss aspects of public policy designed to contain such risks—both from ex ante (preventative) and ex post (crisis-management) perspectives. The second part of the chapter presents an extensive theoretical and empirical literature review on a wide range of issues relating to systemic risk that aims to identify fruitful areas for future research. There has been a substantial increase in interest in analyzing systemic risk and banking/ financial crises, although the authors caution that much more work is needed on identifying the effects of macro prudential policies and the role of bank business models. In Chapter 27, Gerard Caprio and Patrick Honohan chart the frequency and severity of banking crises. A combination of factors is attributed to causing banking crises including: low real interest rates; unsound macroeconomic policies; the expansion of deposit insurance schemes; the accumulation of official foreign exchange reserves; and the over-expansion of derivatives and securitization. The authors point out that the Global Financial Crisis illustrates information problems in the financial system, which lead investors to take excessive risks on products they do not understand. The chapter notes that the most damaging of systemic banking crises, including but not limited to the Global Financial Crisis, have ultimately involved, or were significantly exacerbated by, what the authors refer to as “bad banking and bad policies” that permitted or encouraged excessive risk-taking. The authors call for more dynamic and accountable regulation to help mitigate future crises. In Chapter 28, Charles Calomiris reviews the theory and historical evidence related to the prevalence of bank failures, panics, and contagion. He argues that banking system panics are neither random events nor inherent to the function of banks or the structure of bank balance sheets, but are caused by temporary confusion about the incidence of shocks within the banking system. Several policies have come into existence to deal with such shocks, including mechanisms intended to protect banks from unwarranted withdrawals of deposits (central bank lending during crises, deposit insurance, and

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Banking   25 government-sponsored bank bailouts), and a host of prudential regulatory policies (intended to promote banking system stability, and especially to prevent banks from taking advantage of government protection by increasing their riskiness—the so-called moral-hazard problem of protection). Drawing on empirical evidence, Calomiris argues that government safety nets have led to increased banking instability by lessening market discipline, in turn leading to excessive risk-taking. International bank mergers increased rapidly up to the onset of the financial crisis, but have since declined. In Chapter 29, Claudia Buch and Gayle DeLong examine the causes and effects of international bank mergers. The authors examine the determinants of, and barriers to, cross-border bank mergers, and their impact on the efficiency, competitiveness, and riskiness of financial institutions and systems. Mergers tend to take place mostly between banks from large and developed countries, between institutions based in countries in close regional proximity, and between banks from countries that share a common cultural background. The authors also note that literature has emerged looking at the link between cross-border entry and bank risk. This also covers the bank risk-shifting incentives faced by domestic and foreign regulators. Assessing the importance of these effects empirically has been difficult and relatively few empirical studies analyze the risk effects of bank acquisitions, including effects on financial stability. At the bank level, studies find little evidence for a systematic change in risk following bank acquisitions. In Chapter 30, Nicola Cetorelli and Michael Blank examine the links between financial development and the real economy, focusing on the specific mechanisms, such as competition, which link banks to real economic activity. Evidence suggests that bank concentration is inversely related to economic growth due to lower credit availability, although this effect varies across industries. For instance, concentration allows for the development of long-lasting lending relationships and this seems to enhance growth in industries where young firms are more dependent on external finance. The authors note that after two decades of rigorous research we now know that banking does matter for real economic activity. Banking can have a large impact on various measures of output growth and there is now a much better understanding of the channels through which bank activity feeds through to the real economy.

1.4.5  Banking Systems Around the World Part V of the Handbook focuses on the features of banking systems in different parts of the world. Eight chapters highlight the main structural and institutional features of various systems. The chapters cover banking in the US, the EU, Japan, Africa, China, Russia and Central Europe, Latin America, and Australia and New Zealand. The US banking system has undergone dramatic changes in recent years. In Chapter 31, Robert DeYoung discusses in detail the evolution of the US banking industry over the past 40 years. He examines how deregulation, technological change, and financial innovation have affected industry structure and the strategies banks pursue. The author

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26   Banking presents persuasive evidence that suggests that small and large banks can coexist and pursue very different strategies in long-run equilibrium. In such equilibrium, large banks use advantages afforded by scale to pursue a transaction-based banking business model that is reliant on technology and hard information, while small banks maintain a geographically focused strategy to build and maintain long-term lending relationships. Large banks can thus produce high-volume standardized products at low cost, while small banks can produce lower volumes of more tailored products at a higher price. DeYoung notes that while this new equilibrium brought substantial benefits to the banking industry and the wider economy, it also delivered the instability evidenced by the losses and government bailouts during the Global Financial Crisis. Banking in the European Union has experienced marked changes in recent years. In Chapter 32, John Goddard, Philip Molyneux, and John Wilson explain that the structural and conduct deregulation, which took place up to the Global Financial Crisis, reduced or eliminated many of the lines of demarcation between banks and other financial service providers, and helped to facilitate both domestic and cross-border competition. The Global Financial Crisis and the later European sovereign debt crisis have led to large losses and the failure and closure of many banks, and forced the intervention of both central banks and governments in domestic banking systems. This has necessitated regulatory change aimed at ensuring the stability of the financial system, including a wide range of reforms, such as new capital and liquidity requirements (in line with those set out under Basel III) as well as new governance rules for banks. The EU also set-out a roadmap for the establishment of a European Banking Union in 2012 that has two (of its three) pillars already in place, namely, the Single Supervisory Mechanism (SSM) and the Single Resolution Mechanism (SRM). The third pillar—a Single European Deposit Insurance Scheme—will not be in place until 2024. Japan has a banking system with a wide array of different types of private, cooperative, and government-owned banks, all undertaking a range of business. The system has undergone dramatic changes over recent decades as a result of the country’s major financial crisis that started in the early 1990s and peaked in 1997–8. This was caused to some extent by the bursting of an asset price bubble in real estate, which was amplified by excessive bank lending to the sector. This resulted in the failure of a number of banks and a massive build-up of non-performing loans in the banking system. The perilous state of the banking system in the late 1990s resulted in a wide range of reforms aimed at improving financial sector soundness and bank credit expansion including substantial industry restructuring as well as the use of quantitative easing from 1997–8 onwards. In Chapter 33, Hirofumi Uchida and Gregory Udell analyze the segmented nature of the Japanese banking system and market structure, competition, and bank efficiency. The authors also explore the Japanese main bank system, lending technologies, the banking crisis in the 1990s, and developments in the post-crisis period. The authors also note that there is a relative scarcity of research on Japanese banking. Banking in Africa has experienced rapid development over the past 20 years. Globalization, technological change, and financial liberalization have led to more open, stable, and deeper financial systems. However, in most countries, there remains a lack of

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Banking   27 bank competition and relatively high levels of financial exclusion. In Chapter  34, Thorsten Beck, Robert Cull, and Patricio Valenzuela use a range of different data sources to document various dimensions of the development of African banking systems, highlighting variation within the region and changes over time. The chapter compares Africa’s banking systems to those of comparable low- and lower-middle income countries outside the region, and gauges whether there is an “Africa-specific” element to banking development. The chapter also discusses progress in policies and institutions underpinning financial deepening and the results of specific innovations, including innovative branch expansion programs, mobile banking, and other new financial products aimed at reaching out to previously unbanked populations. In Chapter 35, Leora Klapper, María Soledad Martínez Pería, and Bilal Zia examine banking in China. The sector has grown at a rapid pace over the last decade, and the top five banks are now the largest (by assets size) in the world. China has also experienced a credit boom, which makes the need to better understand how the Chinese financial sector functions even more important. This chapter describes the structure and performance of the financial sector in China, focusing largely on banks. Next, the chapter discusses how regulators’ efforts to slow the growth of bank intermediation have been accompanied by rapid growth in shadow-banking products, as banks try to circumvent limits on their ability to grow. Finally, the authors document China’s progress in expanding consumer access to formal financial services and track the recent expansion of FinTech, especially digital payment products. The chapter concludes by noting that the regulators’ attempts to restrict shadow banking are a welcome development. In Chapter 36, Zuzana Fungáčová, Iftekhar Hasan, Laura Solanko, and Paul Wachtel examine banking in the transition countries of Central, Southern, and Eastern Europe and the former Soviet Union. The authors note that 30 years since the break-up of the Soviet bloc many advanced transition countries have replaced state-owned mono-banking structures with market-oriented banking systems. Much of the transformation has been brought about by improvements in banking technologies arising from the entry of foreign banks. However, there are many aspects of the industry that reflect the legacy of the transition experience. For instance, persistent structural problems in some countries have led to equally persistent bad loan problems. The development of a business lending culture, particularly to SMEs has been slow and firms complain about the difficulty in finding funding. Finally, the slow pace of institutional reform in many countries and government interference in the banking sector in some countries inhibits development. Extensive deregulation has taken place in the banking systems of Latin America in recent years. In Chapter 37, Fernando Carvalho, Luiz de Paula, and Jonathan Williams assess the extent to which interest rate deregulation, bank privatization, and the removal of barriers to foreign banking led to banking crises in Brazil, Chile, Argentina, and Mexico. The authors note that banking crises in the 1980s and 1990s did not lead to reversals in the financial liberalization process. Instead, most countries in the area invested in building regulatory and supervisory infrastructures to ensure the future stability of the banking system. Banking systems in Latin America were left relatively unscathed by the Global Financial Crisis. Over the last thirty years the banking systems in the region have

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28   Banking been transformed from predominantly state-owned to market-oriented with modern institutional arrangements and updated regulatory structures. In Chapter 38, Fariborz Moshirian and Eliza Wu discuss banking in Australia and New Zealand. Australian banks weathered the Global Financial Crisis and still recorded strong profits and minimal losses while other global banks failed internationally. To understand why this was the case, the authors examine the composition of the closely integrated banking sectors in Australia and New Zealand, their respective performance, capital levels and some defining regulatory reforms that have particularly shaped the Australian banking system. The Australian and New Zealand banking systems are highly integrated with all “top four” Australian banks having significant investments and operations within the relatively smaller New Zealand banking sector. The features of these systems are discussed and attention is also paid to the ongoing regulatory concerns over the competitiveness of their respective banking systems.

References Abedifar, P., Molyneux, P., and Tarazi, A. (2013). “Risk in Islamic Banking,” Review of Finance, 17, 2035–96. Acharya, V., Eisert, T., Eufinger, C., and Hirsch, C. (2017). “Whatever It Takes: The Real Effects of Unconventional Monetary Policy,” SAFE Working Paper Series No. 152, SAFE— Sustainable Architecture for Finance in Europe, Goethe University Frankfurt, House of Finance (HoF), Frankfurt. Acharya, V. V., Eisert, T., Eufinger, C., and Hirsch, C. (2018). “Real Effects of the Sovereign Debt Crisis in Europe: Evidence from Syndicated Loans,” Review of Financial Studies, 31, 2855–96. Acharya, V. V., Engle, R. H., and Pierret, D. (2014). “Testing Macro Prudential Stress Tests: The Risk of Regulatory Risk Weights,” Journal of Monetary Economics, 65, 36–53. Acharya, V. V., Pedersen, L. H., Philippon, T., and Richardson, M. (2017). “Measuring Systemic Risk,” The Review of Financial Studies, 30, 2–47. Acharya, V. V., Shin, H. S., and Yorulmazer, T. (2011). “Crisis Resolution and Bank Liquidity,” The Review of Financial Studies, 24, 2166–22. Adams, R. B. (2012). “Governance and the Financial Crisis,” International Review of Finance, 12, 7–38. Adams, R. B. and Mehran, H. (2012). “Bank Board Structure and Performance: Evidence for Large Bank Holding Companies,” Journal of Financial Intermediation, 21, 243–67. Adrian, T. and Boyarchenko, N. (2018). “Liquidity Policies and Systemic Risk,” Journal of Financial Intermediation, 38(Part B), 45–60. Adrian, T. and Brunnermeier, M. K. (2016). “CoVaR,” American Economic Review, 106, 1705–41. Aiyar, S., Calomiris, C.  W., Hooley, J., Korniyenko, Y., and Wieladek, T. (2014). “The International Transmission of Bank Capital Requirements: Evidence from the UK,” Journal of Financial Economics, 113, 368–82. Alcaraz, C., Claessens, S., Cuadra, G., Marques-Ibanez, D., and Sapriza, H. (2018). “Whatever It Takes: What’s the Impact of a Major Nonconventional Monetary Policy Intervention?” Bank of International Settlements Working Paper No. 749.

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Banking   29 Alfaro, L., García-Santana, M., and Moral-Benito, E. (2018). “On the Direct and Indirect Real Effects of Credit Supply Shocks,” CEPR Discussion Paper 12794, London, CEPR. Allen, F., Carletti, E., and Marquez, R. (2011). “Credit Market Competition and Capital Regulation,” The Review of Financial Studies, 24, 983–1018. Allen, L., Bali, T. G., and Tang, Y. (2012). “Does Systemic Risk in the Financial Sector Predict Future Economic Downturns?” The Review of Financial Studies, 25, 3000–36. Amador, J. and Nagengast, A.  J. (2016). “The Effect of Bank Shocks on Firm-Level and Aggregate Investment,” ECB Frankfurt Working Paper No. 1914. Amiti, M. and Weinstein, D.  E. (2018). “How Much do Idiosyncratic Bank Shocks Affect Investment? Evidence from Matched Bank–Firm Loan Data,” Journal of Political Economy, 126, 525–87. Arteta, C., Kose, M. A., Stocker, M., and Taskin, T. (2016). “Negative Interest Rate Policies: Sources and Implications,” World Bank Policy Research Paper 7791, August, Washington, DC. Ball, L., Gagnon, J., Honohan, P., and Krogstrup, S. (2016). “What Else can Central Banks Do?” Geneva Reports on the World Economy 18, The International Center for Monetary and Banking Studies (ICMB) and the Centre for Economic Policy Research (CEPR). ICMB, Zurich and CEPR, London. Banerji, S., Chronopoulos, D., Sobiech, A.  L., and Wilson, J.  O.  S. (2018). “Taxation and  Financial Intermediation: Evidence from a Quasi-Natural Experiment,” Centre for Responsible Banking & Finance, Working Paper No. 18–001, 1st Quarter, University of St. Andrews, Scotland. Basel Committee on Banking Supervision (2010a). “Basel III: A Global Regulatory Framework for more Resilient Banks and Banking Systems,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel. Basel Committee on Banking Supervision (2010b). “Basel III: International Framework for Liquidity Risk Measurement, Standards and Monitoring,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel. Basel Committee on Banking Supervision (2013). “Basel III: The Liquidity Coverage Ratio and Liquidity Risk Monitoring Tools,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel. Basel Committee on Banking Supervision (2014). “Basel III: The Net Stable Funding Ratio,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel. Basel Committee on Banking Supervision (2017). “Basel III: Finalising Post-Crisis Reforms,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel. Bassett, W., Demiralp, S., and Lloyd, N. (forthcoming). “Government Support of Banks and Bank Lending,” Journal of Banking & Finance. Bebchuk, L.  A., Cohen, A., and Spamann, H. (2010). “The Wages of Failure: Executive Compensation at Bear Stearns and Lehman 2000–2008,” Yale Journal on Regulation, 27, 257–82. Bech, M.  L. and Malkhozov, A. (2016). “How have Central Banks Implemented Negative Policy Rates?” Bank for International Settlements (BIS) Quarterly Review, (March), 31–44. Beck, T., Degryse, H., De Haas, R., and van Horen, N. (2018). “When Arm’s Length is Too Far: Relationship Banking over the Business Cycle,” Journal of Financial Economics, 127, 174–96. Beck, T., Demirgüç-Kunt, A., and Pería, M. S. M. (2008). “Banking Services for Everyone? Barriers to Bank Access and Use Around the World,” World Bank Economic Review, 22, 397–430.

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30   Banking Beck, T., Levine, R., and Levkov, A. (2010). “Big Bad Banks? The Winners and Losers from Bank Deregulation in the United States,” Journal of Finance, 65, 1637–67. Beltratti, A. and Stulz, R.  M. (2012). “The Credit Crisis around the Globe: Why did some Banks Perform Better?” Journal of Financial Economics, 105, 1–17. Bentolila, S., Jansen, M., and Jiménez, G. (2018). “When Credit Dries Up: Job Losses in the Great Recession,” Journal of the European Economic Association, 16, 650–95. Berg, T., Burg, V., Gombovic, A., and Puri, M. (2018). “On the Rise of FinTechs: Credit Scoring using Digital Footprints,” Duke University Working Paper. Berger, A.  N. and Bouwman, C.  H.  S. (2009). “Bank Liquidity Creation,” The Review of Financial Studies, 22, 3779–837. Berger, A.  N. and Bouwman, C.  H.  S. (2013). “How does Capital affect Bank Performance During Financial Crises?” Journal of Financial Economics, 109, 146–76. Berger, A.  N. and Roman, R.  A. (2015). “Did TARP Banks Get Competitive Advantages?” Journal of Financial and Quantitative Analysis, 50, 1199–236. Berger, A. N. and Roman, R. A. (2017). “Did Saving Wall Street Really Save the Main Street? The Real Effects of TARP on Local Business Conditions,” Journal of Financial and Quantitative Analysis, 52, 1827–67. Berger, A. N. and Roman, R. A. (2018). “Finance and the Real Economy: Evidence from the US,” in T. Beck and R. Levine (eds.), The Handbook of Finance and Development. (Cheltenham: Edward Elgar), 261–88. Berger, A. N., Black, L. K., Bouwman, C. H. S., and Dlugosz, J. L. (2017). “Bank Loan Supply Responses to Federal Reserve Emergency Liquidity Facilities,” Journal of Financial Intermediation, 32, 1–15. Berger, A. N., Bouwman, C. H. S., Kick, T., and Schaeck, K. (2016). “Bank Liquidity Creation Following Regulatory Interventions and Capital Support,” Journal of Financial Intermediation, 26, 115–41. Berger, A. N., Curti, F., Mihov, A., and Sedunov, L. (2018). “Operational Risk is More Systemic Than You Think: Evidence from U.S. Bank Holding Companies,” Federal Reserve Bank of Richmond Working Paper. Berger, A. N., DeYoung, R., Flannery, M. J., Lee, D., and Öztekin, Ö. (2008). “How Do Large Banking Organizations Manage Their Capital Ratios?” Journal of Financial Services Research, 34, 123–49. Berger, A. N., Guedhami, O., Kim, H. H., and Li, X. (2018). “Economic Policy Uncertainty and Bank Liquidity Hoarding,” University of South Carolina Working Paper. Berger, A. N., Kick, T., and Schaeck, K. (2014). “Executive Board Composition and Bank Risk Taking,” Journal of Corporate Finance, 28, 48–65. Berger, A.  N., Makaew, T., and Roman, R.  A. (forthcoming). “Do Borrowers Benefit from Bank Bailouts During Financial Crises? The Effects of TARP on Loan Contract Terms,” Financial Management. Berger, A. N., Roman, R. A., and Sedunov, J. (2018). “Did TARP Reduce or Increase Systemic Risk? The Effects of Government Aid on Financial System Stability,” University of South Carolina Working Paper. Berrospide, J. M. and Edge, R. M. (2010). “The Effects of Bank Capital on Lending: What Do We Know, and What Does It Mean?” FEDS Working Paper No. 2010–44. Berthou, A., Horny, G., and Mésonnier, J.-S. (2018). “Dollar Funding and Firm-Level Exports,” Banque de France Working Paper No. 666, available at SSRN: https://ssrn.com/abstract= 3135724 or http://dx.doi.org/10.2139/ssrn.3135724.

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Banking   31 Berton, F., Mocetti, S., Presbitero, A. F., and Richiardi, M. (2018). “Banks, Firms and Jobs,” Review of Financial Studies, 31, 2113–56. Billio, M., Getmansky, M., Lo, A.  W., and Pelizzon, L. (2012). “Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors,” Journal of Financial Economics, 104, 535–59. Black, L., and Hazelwood, L. (2013). “The Effect of TARP on Bank Risk-Taking,” Journal of Financial Stability, 9, 790–803. Blattner, L., Farihan, L., and Rebelo, F. (2017). “When Losses Turn into Loans: The Cost of Undercapitalized Banks,” mimeo. Bofondi, M., Carpinelli, L., and Sette, E. (2018). “Credit Supply During a Sovereign Debt Crisis,” Journal of the European Economic Association, 16, 696–729. Borio, C. and Zabai, A. (2016). “Unconventional Monetary Policies: A Re-appraisal,” Bank for International Settlements, Basel BIS Working Paper No. 570 (July). Bottero, M., Lenzu, S., and Mezzanotti, F. (2017). “Sovereign Debt Exposure and the Bank Lending Channel: Impact on Credit Supply and the Real Economy,” Bank of Italy Working Paper No. 1032, Bank of Italy, Rome. Bräuning, F. and Wu, B. (2017). “ECB Monetary Policy Transmission During Normal and Negative Interest Rate Periods,” available at: doi: http://dx.doi.org/10.2139/ssrn.2940553. Brownlees, C. and Engle, R.  F. (2017). “SRISK: A Conditional Capital Shortfall Measure of Systemic Risk,” The Review of Financial Studies, 30, 48–79. Buca, A. and Vermeulen, P. (2017). “Corporate Investment and Bank-Dependent Borrowers During the Recent Financial Crisis,” Journal of Banking & Finance, 78, 164–80. Buch, C. M., Hilberg, B., and Tonzer, L. (2016). “Taxing Banks: An Evaluation of the German Bank Levy,” Journal of Banking & Finance, 72, 52–66. Cámara, N.  T. and Tuesta, D. (2014). “Measuring Financial Inclusion: A Multidimensional Index,”, BBVA Madrid, BBVA Working Paper No. 14/26, September. Capelle-Blancard, G. and Havrylchyk, O. (2014). “The Ability of Banks to Shift Corporate Income Taxes to Customers,” in R.  de Mooij and G.  Nicodème (eds.), Taxation and Regulation of the Financial Sector (Cambridge, MA: MIT Press), 253–78. Carpinelli, L. and Crosignani, M. (2017). “The Effect of Central Bank Liquidity Injections on Bank Credit Supply,” Finance and Economics Discussion Series 2017–038, Board of Governors of the Federal Reserve System, Federal Reserve, Washington, DC. Carvalho, D., Ferreira, M., and Matos, P. (2015). “Lending Relationships and the Effect of Bank Distress: Evidence from the 2007–2008 Financial Crisis,” Journal of Financial and Quantitative Analysis, 6, 1165–97. Catalini, C. and Gans, J. S. (2018). “Initial Coin Offerings and the Value of Crypto Tokens,” available at SSRN: https://ssrn.com/abstract=3137213 or http://dx.doi.org/10.2139/ssrn. 3137213. Célérier, C. and Matray, A. (2016). “Unbanked Households: Evidence of Supply-Side Factors,” Working Paper. Chiorazzo, V. and Milani, C. (2011). “The Impact of Taxation on Bank Profits: Evidence from EU Banks,” Journal of Banking & Finance, 35, 3202–12. Chu, Y., Zhang, D., and Zhao, Y. (forthcoming). “Bank Capital and Lending: Evidence From Syndicated Loans,” Journal of Financial and Quantitative Analysis. Cingano, F., Manaresi, F., and Sette, E. (2016). “Does Credit Crunch Investments Down? New Evidence on the Real Effects of the Bank-Lending Channel,” Review of Financial Studies, 29, 2737–73.

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32   Banking Claessens, S., Coleman, N.  S., and Donnelly, M. (2018). “Low-for-Long Interest Rates and Banks’ Interest Margin and Profitability: Cross-Country Evidence,” Journal of Financial Intermediation, 35(Part A), 1–16. Claessens, S., Keen, M., and Pazarbasioglu, C. (2010). “Financial Sector Taxation. IMF’s Report to the G-20 and Background Material,” IMF Staff Report, September, International Monetary Fund, Washington, DC. Cohn, A., Fehr, E., and Maréchal, M. (2014). “Business Culture and Dishonesty in the Banking Industry,” Nature, 516, 86–9. Cohn, A., Fehr, E., and Maréchal, M. (2017). “Do Professional Norms in the Banking Industry Favor Risk-Taking?” Review of Financial Studies, 30, 3801–23. Cole, R. A. and White, L. J. (2012). “Deja Vu All Over Again: The Causes of US Commercial Bank Failures This Time Around,” Journal of Financial Services Research, 42, 5–29. Cong, L.  W. and He, Z. (2018). “Blockchain Disruption and Smart Contracts,” NBER Working Paper No. W24399, available at SSRN: https://ssrn.com/abstract=3138382, NBER, Cambridge, MA. Cornaggia, J., Mao, Y., Tian, X., and Wolfe, B. (2015). “Does Banking Competition Affect Innovation?” Journal of Financial Economics, 115, 189–209. Cortés, K. R. and Strahan, P. E. (2017). “Tracing Out Capital Flows: How Financially Integrated Banks Respond to Natural Disasters,” Journal of Financial Economics, 125, 182–99. Crump, R. K. and Santos, J. A. C. (2018). “Review of New York Fed Studies on the Effects of Post-Crisis Banking Reforms,” New York Economic Policy Review, 24, 71–90. Daetz, S.  L., Subrahmanyam, M. G., Tang, D.  Y., and Wang, S. (2018). “Did ECB Liquidity Injections Help the Real Economy?” mimeo. Degryse, H., de Jonghe, O., Jakovljevic, S., Mulier, K., and Schepens, G. (2018). “The Impact of Bank Shocks on Firm-Level Outcomes and Bank Risk-Taking,” available at SSRN: https:// ssrn.com/abstract=2788512. De Jonghe, O., and Öztekin, Ö. (2015). “Bank Capital Management: International Evidence,” Journal of Financial Intermediation, 24, 154–77. De Jonghe, O., Dewachter, H., Mulier, K., Ongena, S., and Schepens, G. (2018). “Some Borrowers are more Equal than Others: Bank Funding Shocks and Credit Reallocation,” available at SSRN: https://ssrn.com/abstract=2774441. Delis, M. D. and Staikouras, P. K. (2011). “Supervisory Effectiveness and Bank Risk,” Review of Finance, 15, 511–43. Deloitte (2017). Fintech by the Numbers. Incumbents, Startups, Investors Adapt to Maturing Ecosystem (San Francisco, CA: Deloitte). De Marco, F. (2018). “Bank Lending and the European Sovereign Debt Crisis,” Austrian Central Bank Working Paper No. 213, Austrian Central Bank, Vienna. Demiralp, S., Eisenschmidt, J., and Vlassopoulos, T. (2017). “Negative Interest Rates, Excess Liquidity and Bank Business Models: Banks’ Reaction to Unconventional Monetary Policy in the Euro Area,” Koç University-TUSIAD Economic Research Forum Working Paper No. 1708, Istanbul, Koç University-TUSIAD Economic Research Forum. Demirgüç-Kunt, A. and Huizinga, H. (2001). “The Taxation of Domestic and Foreign Banking,” Journal of Public Economics, 79, 429–53. Demirgüç-Kunt, A. and Klapper, L. (2013). “Measuring Financial Inclusion: Explaining Variation in Use of Financial Services across and within Countries,” Brookings Papers on Economic Activity, (Spring), 279–340.

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Banking   33 Demirgüç-Kunt, A., Detragiache, E., and Merrouche, O. (2013). “Bank Capital: Lessons from the Financial Crisis,” Journal of Money, Credit and Banking, 45, 1147–64. Demyanyk, Y. (2008). “U.S.  Banking Deregulation and Self-Employment: A Differential Impact on Those in Need,” Journal of Economics and Business, 60, 165–78. Deyoung, R., Peng, E. Y., and Yan, M. (2013). “Executive Compensation and Business Policy Choices at US Commercial Banks,” Journal of Financial and Quantitative Analysis, 48, 165–96. Díaz Díaz, B., García-Ramos, R., and García Olalla, M. (2017). “Shareholder Wealth Responses to European Legislation on Bank Executive Compensation,” Journal of Economic Policy Reform, 20, 1–21. Dodd–Frank Wall Street Reform and Consumer Protection Act (2010). (Known As The Dodd–Frank Act), Pub L. 111–203, H.R.4173, 21 July. Duchin, R. and Sosyura, D. (2014). “Safer Ratios, Riskier Portfolios: Banks’ Response to Government Aid,” Journal of Financial Economics, 113, 1–28. Dwenger, N., Fossen, F.  M., and Simmler, M. (forthcoming). “Firms’ Financial and Real Responses to Credit Supply Shocks: Evidence from Firm–Bank Relationships in Germany,” Journal of Financial Intermediation. European Banking Authority (EBA) (2017). “The EBA’s Approach to Financial Technology (FinTech),” Discussion Paper No. 2, 4 August, European Banking Authority, London. Erkens, D.  H., Hung, M., and Matos, P. (2012). “Corporate Governance in the 2007–2008 Financial Crisis: Evidence from Financial Institutions Worldwide,” Journal of Corporate Finance, 18, 389–411. Fahlenbrach, R. and Stulz, R. M. (2011). “Bank CEO Incentives and the Credit Crisis,” Journal of Financial Economics, 99, 11–26. Farinha, L., Spaliarab, M.  L., and Tsoukas, S. (2018). “Bank Funding Shocks and Firm Performance: New Evidence from the Sovereign Debt Crisis,” mimeo. Financial Times (2017). “New Basel Rules on Capital Hit European Banks,” December 7. Fiordelisi, F. and Ricci, O. (2016). “‘Whatever It Takes’: An Empirical Assessment of the Value of Policy Actions in Banking,” Review of Finance, 20, 2321–47. Flannery, M. J. and Giaconimi, E. (2015). “Maintaining Adequate Bank Capital: An Empirical Analysis of the Supervision of European Banks,” Journal of Banking & Finance, 59, 236–49. Flannery, M. J. and Rangan, K. P. (2008). “What Caused the Bank Capital Build-Up of the 1990s?” Review of Finance, 12, 391–429. Fonseca, A. R. and Gonzalez, F. (2010). “How Bank Capital Buffers Vary Across Countries: The Influence of Cost of Deposits, Market Power and Bank Regulation,” Journal of Banking & Finance, 34, 892–902. Fourth Capital Requirement Directive (2013). (Known as CRD 1V), European Union, 2013/36/ EU, 23 June, EU, Brussels. Fraisse, H., Lé, M., and Thesmar, D. (2017). “The Real Effects of Bank Capital Requirements,” ESRB Working Paper No. 47, European Systemic Risk Board, Frankfurt. Franklin, J., Rostom, M., and Thwaites, G. (2015). “The Banks That Said No: Banking Relationships, Credit Supply and Productivity in the UK,” Bank of England Working Paper No. 557. Franks, J., Serrano-Velarde, N., and Sussman, O. (2018). “Marketplace Lending, Information Aggregation, and Liquidity,” London Business School Working Paper. Financial Services Authority (FSA) (2009). “Reforming Remuneration Practices in Financial Services,” Policy Statement 9/15, August, Financial Services Authority, London.

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34   Banking Fuster, A., Goldsmith-Pinkham, P., Ramadorai, T., and Walther, A. (2018). “Predictably Unequal? The Effects of Machine Learning on Credit Markets,” available at SSRN: https:// ssrn.com/abstract=3072038. Gertler, M. and Kiyotaki, N. (2015). “Banking, Liquidity, and Bank Runs in an Infinite Horizon Economy,” The American Economic Review, 105, 2011–43. Giglio, S., Kelly, B., and Pruitt, S. (2016). “Systemic Risk and the Macroeconomy: An Empirical Evaluation,” Journal of Financial Economics, 119, 457–71. Gobbi, G. and Sette, E. (2014). “Do Firms Benefit from Concentrating Their Borrowing? Evidence from the Great Recession,” Review of Finance, 18, 527–60. Gong, D., Hu, S., and Ligthart, J. (2015). “Does Corporate Income Taxation Affect Securitization? Evidence from OECD Banks,” Journal of Financial Services Research, 48, 193–213. Griffin, J. M. and Shams, A. (2018). “Is Bitcoin Really Un-Tethered?” Social Science Research Network, available at: https://ssrn.com/abstract=3195066. Gropp, R. and Heider, F. (2010). “The Determinants of Bank Capital Structure,” Review of Finance, 14, 587–622. Gropp, R., Mosk, T., Ongena, S., and Wix, C. (2019). “Bank Response to Higher Capital Requirements: Evidence from a Natural Experiment,” Review of Financial Studies, 32 (January), 266–99. Han, J., Park, K., and Pennacchi, G. (2015). “Corporate Taxes and Securitization,” Journal of Finance, 70, 1287–321. Hasan, I., Siddique, A., and Sun, X. (2015). “Monitoring the ‘Invisible’ Hand of Market Discipline: Capital Adequacy Revisited,” Journal of Banking & Finance, 50, 475–92. Heider, F., Saidi, F., and Schepens, G. (2017). “Life Below Zero: Bank Lending Under Negative Policy Rates,” available at SSRN: https://ssrn.com/abstract=2788204. Hombert, J. and Matray, A. (2017). “The Real Effects of Lending Relationships on Innovative Firms and Inventor Mobility,” Review of Financial Studies, 30, 2413–45. Howell, S., Niessner, M., and Yermack, D. (2018). “Initial Coin Offerings: Financing Growth with Cryptocurrency Token Sales,” NBER Working Paper No. 24774, NBER, Cambridge, MA. Huang, R. R. (2008). “Evaluating the Real Effect of Bank Branching Deregulation: Comparing Contiguous Counties across US State Borders,” Journal of Financial Economics, 87, 678–705. Huber, K. (2018). “Disentangling the Effects of a Banking Crisis: Evidence from German Firms and Counties,” American Economic Review, 108, 868–98. Iyer, R., Lopes, S., Peydro, J.-L., and Schoar, A. (2014). “Interbank Liquidity Crunch and the Firm Credit Crunch: Evidence from the 2007–2009 Crisis,” Review of Financial Studies, 27, 347–72. Jayaratne, J. and Strahan, P.  E. (1996). “The Finance–Growth Nexus: Evidence from Bank Branch Deregulation,” Quarterly Journal of Economics, 111, 639–70. Jiménez, G., Ongena, S., Peydro, J.  L., and Saurina, J. (2018). “Macroprudential Policy, Countercyclical Bank Capital Buffers, and Credit Supply: Evidence from the Spanish Dynamic Provisioning Experiments,” Journal of Political Economy, 126, 2126–77. Keen, M. and De Mooij, R. A. (2016). “Debt, Taxes, and Banks,” Journal of Money Credit and Banking, 48, 5–33. Kleymenova, A. and Tuna, A. (2016). “Regulation of Compensation,” Chicago Booth Research Paper 16–07, available at SSRN: https://ssrn.com/abstract=2755621. Koetter, M., Noth, F., and Rehbein, O. (2018). “Borrowers Under Water! Rare Disasters, Regional Banks and Recovery Lending,” mimeo.

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Banking   35 Kozak, S. and Sosyura, D. (2015). “Access to Credit and Stock Market Participation,” Working Paper. KPMG (2018). “The Pulse of Fintech,” Q4 2017, February, KPMG International, Zug, Switzerland. Krishnan, K., Nandy, D., and Puri, M. (2015). “Does Financing Spur Small Business Productivity? Evidence from a Natural Experiment,” Review of Financial Studies, 28, 1768–809. Kritzman, M. and Li, Y. (2010). “Skulls, Financial Turbulence, and Risk Management,” Financial Analysts Journal, 66, 30–41. Kritzman, M., Li, Y., Page, S., and Rigobon, R. (2010). “Principal Components as a Measure of Systemic Risk,” MIT Sloan Research Paper 4785–10, available at SSRN: https://ssrn.com/ abstract=1633027. Kroszner, R. S. and Strahan, P. E. (2013). “Regulation and Deregulation of the US Banking Industry: Causes, Consequences and Implications for the Future,” in N.  L.  Rose (ed.), Economic Regulation and its Reform: What Have We Learned? (Chicaco, IL: University of Chicago Press), 485–543. Laeven, L. and Valencia, F. (2013). “The Real Effects of Financial Sector Interventions During Crises,” Journal of Money, Credit and Banking, 45, 147–77. Laeven, L., McAdam, P., and Popov, A. A. (2018). “Credit Shocks, Employment Protection, and Growth: Firm-Level Evidence from Spain,” ECB Working Paper No. 2166, ECB Frankfurt. Li, L. (2013). “TARP Funds Distribution and Bank Loan Supply,” Journal of Banking and Finance, 37, 4777–92. Lin, L. and Pennachi, G. (2018). “Who Bears the Burden of Banks’ Corporate Taxes?” mimeo. Lumpkin, S. (2010). “Consumer Protection and Financial Innovation: A Few Basic Propositions,” OECD Journal: Financial Market Trends, 1, 117–39. Mariathasan, M. and Merrouche, O. (2014). “The Manipulation of Basel Risk-Weights,” Journal of Financial Intermediation, 23, 300–21. Mehran, H., Morrison, A., and Shapiro, J. (2012). “Corporate Governance and Banks: What Have We Learned from the Financial Crisis?” in M. Dewatripont and X. Freixas (eds.), The Crisis Aftermath: New Regulatory Paradigms (London: Centre For Economic Policy Research), 11–44. Memmel, C. and Raupach, P. (2010). “How Do Banks Adjust Their Capital Ratios?” Journal of Financial Intermediation, 19, 509–28. Minton, B. A., Taillard, J. P., and Williamson, R. (2014). “Financial Expertise of the Board, Risk Taking, and Performance: Evidence from Bank Holding Companies,” Journal of Financial and Quantitative Analysis, 49, 351–80. Montgomery, H. and Takahashi, Y. (2014). “The Economic Consequences of the TARP: The Effectiveness of Bank Recapitalization Policies in the US,” Japan and The World Economy, 32, 49–64. Moral-Benito, E. (2018). “The Microeconomic Origins of the Spanish Boom,” Bank of Spain Working Paper No. 1805, Bank of Spain, Madrid. Morgan, D., Rime, B., and Strahan, P. E. (2004). “Bank Integration and State Business Cycles,” Quarterly Journal of Economics, 119, 1555–85. Naceur, S.  B., Barajas, A., and Massara, A. (2015). “Can Islamic Banking Increase Financial  Inclusion?” IMF Working Paper No. WP/15/31, International Monetary Fund, Washington, DC. Nakashima, K. and Takahashi, K. (2017). “The Real Effects of Bank-Driven Termination of Relationships: Evidence from Loan-Level Matched Data,” mimeo.

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36   Banking Nguyen, D.  D., Nguyen, H.  L., and Sila, V. (forthcoming). “Does Corporate Culture Affect Bank Risk-Taking? Evidence from Loan-Level Data,” British Journal of Management. Öztekin, Ö. and Flannery, M.  J. (2012). “Institutional Determinants of Capital Structure Adjustment Speeds,” Journal of Financial Economics, 103, 88–112. Palvia, A., Vähämaa, E., and Vähämaa, S. (2015). “Are Female CEOs and Chairwomen More Conservative and Risk Averse? Evidence from the Banking Industry During the Financial Crisis,” Journal of Business Ethics, 131, 577–94. Pasiouras, F. (2018). “Financial Consumer Protection and the Cost of Financial Intermediation: Evidence from Advanced and Developing Economies,” Management Science, 64, 902–24. Popov, A. and Rocholl, J. (2018). “Do Credit Shocks Affect Labour Demand? Evidence for Employment and Wages during the Financial Crisis,” Journal of Financial Intermediation, 36, 16–27. Puddu, S. and Waelchli, A. (2015). “TARP Effect on Bank Lending Behaviour: Evidence from the Last Financial Crisis,” University of Neuchatel Institute of Economic Research Working Paper No. 15–06, University of Neuchatel, Neuchatel, Switzerland. Rice, T. and Strahan, P.  E. (2010). “Does Credit Competition Affect Small-Firm Finance?” Journal of Finance, 65, 861–89. Schepens, G. (2016). “Taxes and Bank Capital Structure,” Journal of Financial Economics, 120, 585–600. Thakor, A. (2019). The Purpose of Banking (New York: Oxford University Press). Vallascas, F. and Hagendorff, J. (2013). “The Risk Sensitivity of Capital Requirements: Evidence from an International Sample of Large Banks,” Review of Finance, 17, 1947–88. Wehinger, G. (2012). “Banking in a Challenging Environment: Business Models, Ethics and Approaches towards Risks,” OECD Journal: Financial Market Trends, 2, 79–88. World Bank (2014). Global Financial Development Report (Washington, DC: World Bank). Wu, D. (2015). “The Effects of Government Capital and Liquidity Support Programs on Bank Lending: Evidence from the Syndicated Corporate Credit Market,” Journal of Financial Stability, 21, 13–25.

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PA RT I

T H E T H E ORY OF BA N K I NG

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chapter 2

The Roles of Ba n ks i n Fi na nci a l Systems Franklin Allen, Elena Carletti, and Xian Gu

2.1 Introduction Understanding the many roles that banks play in the financial system is one of the fundamental issues in theoretical economics and finance. The crisis of 2007–9 underlines just how important banks are to the economy. The efficiency of the process through which savings are channeled into productive activities is crucial for growth and general welfare. Banks are one part of this process. Lenders of funds are primarily households and firms. These lenders can supply funds to the ultimate borrowers, who are mainly firms, governments, and households, in two ways. The first is through financial markets, which consist of money markets, bond markets, and equity markets. The second is through banks and other financial intermediaries such as money market funds, mutual funds, insurance companies, and pension funds. Despite the trend of globalization in recent years, the importance of banks in different economies varies significantly. Figure 2.1 shows a comparison of the long-term financing structure of the Euro Area, the UK, the US, and Japan in 2001 and 2016. The figures are given as a percentage of GDP. Bank assets consist of domestic credit to the private sector. The figures in the stock market column are the total market capitalization. The bond market figures are divided into public and private sector bonds. It can be seen from Figure 2.1a that in 2001 the Euro Area had small stock markets but large bank loans and in that sense could be considered as bank-based. However, it also had a more significant bond market, both in terms of public and private sector debt, than a stock market. The UK was significantly different with a large stock market and bank loans but a small bond market, particularly in terms of public sector debt. It is both market-based and bank-based. The main features of the US financial structure are a smaller amount of bank assets, a more significant stock market and a much larger bond market than any of the other areas in relative terms. It is the most market-based

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40   The Theory of Banking a. 2001

b. 2016

500

500

400

400

300

300

200

200

100

100

0

Euro area

UK

US

Japan

Bank assets Stock market capitalization Private bond market capitalization Public bond market capitalization

0

Euro area

UK

US

Japan

Bank assets Stock market capitalization Private bond market capitalization Public bond market capitalization

Figure 2.1  Size of the Financial Markets by Country/Region 2001 and 2016, Percentage of GDP. Source: IMF, World Bank and national authorities.

e­ conomy. Japan has significant amounts of finance in all categories. It is very much a bank- and market-based economy. Emerging Asia is more similar to the Euro Area, bank assets are important but the market is not. Figure 2.1b shows the situation in 2016, several years after the 2008 global financial ­crisis. It can be seen that the structure is similar but with a few important differences. While bank assets in Japan have increased relative to GDP, they have decreased everywhere else. This is particularly true for the US. Figure 2.2 focuses on the claims that are issued by borrowers. Another way of considering the importance of banks is to look at household assets. These are shown in Figure 2.2a. This shows that all the economies are distinctly different. Households in the Euro Area own significantly fewer financial assets than in the other economies with a total of 205 percent of GDP compared with 289 percent, 347 percent, and 296 percent for the UK, the US, and Japan, respectively. In terms of the composition of assets there are also large differences. In the Euro Area, assets held in insurance and pension funds and in banks are the most important two, with direct holdings of shares after that. One striking thing is that household portfolios in the UK are very similar to those in the Euro Area with one significant difference: the investment in insurance and pension funds is dramatically higher. This is presumably a result of the difference in public sector p ­ ension schemes. In the UK, the basic pension from the state is minimal, while in the Euro Area state pensions are usually generous. The US is an outlier in terms of the direct holdings of shares and other equity. Also, households hold relatively little in banks. Meanwhile, Japan is an outlier in terms of the amount of assets held in banks where households hold much more in this form than households in other countries. In fact, the Japanese post office bank is the largest deposit-taker in the world. Japanese households also have ­significant amounts in insurance and pension funds. This is, to a large extent, in ­insurance companies that offer debt-like contracts. Given the small holdings of shares

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The Roles of Banks in Financial Systems   41 a. Households 200

b. Non-financial corporations 75

150

50

100 25

50 0

Euro area (205%)

UK (289%)

US (347%)

Japan (296%)

Banks Shares and other equity Securities other than shares Insurance and Funds Other

0

Euro area (149%)

UK (111%)

US (91%)

Japan (167%)

Banks Loans and trade credit Shares and other equity Securities other than shares Other

Figure 2.2  Portfolio Allocation of Households and Non-financial Corporations (Average 1997–2016), Percentage of GDP. Source: Bank of Japan, ECB, EUROSTAT, Federal Reserve Board, Bank of England and the UK Office for National Statistics.

and other equity, the Japanese bear significantly less financial risk than the households in the US and UK. Uchida and Udell, in Chapter 33 of this volume, examine the structure and characteristics of the Japanese banking system. The US has somewhat less intermediation than the other economies, although the total amount of intermediation is significant in all economies. Figure 2.2b shows the assets of non-financial corporations. These again underline significant differences across the economies. The Euro Area and the UK are quite similar except for the amount of shares and other equity, which is larger in the Euro Area. The US has much less investment than the other countries except for the “other” category. This includes holdings of other assets, which are not identified explicitly in the flow of funds data.1 Japan is perhaps the most different. It has significantly more assets in banks and more trade credit than other countries. The implication of Figures 2.1 and 2.2 is that the importance of banks and their roles is significantly different in different economies. We start by considering the basic rationales for the existence of banks. Section 2.2 considers the monitoring role of banks while section  2.3 considers their risk-sharing role. The bearing of risks by banks can have important implications for financial stability. Section 2.4 considers various aspects of banking crises, including how they occur and how they disrupt the economy. The role 1  The column representing “other” assets is unidentified miscellaneous assets. It is a residual item, arising after accounting for all asset or liability items reported by classified flow of funds sectors. In other words, accounting items that do not represent claims on another party are all classified as “other”. One example would be the accounting value of goodwill after M&A activities.

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42   The Theory of Banking of banks in spurring growth is considered in section 2.5. Section 2.6 is concerned with the corporate governance role of banks, section 2.7 with relationship banking, and ­ section 2.8 contains concluding remarks.

2.2  Delegated Monitoring and Banks An argument that is often put forward in favor of bank-based systems is that banks allow various informational problems to be solved. One important problem is whether borrowers must take some action to make proper use of the funds they have borrowed. This action could be the level of effort or the choice of project from among various different risky alternatives. The borrower can always claim that a low outcome is due to bad luck rather than from not taking the correct action. Lenders cannot observe the borrower’s action unless they pay a fixed cost to monitor the borrower. In a financial market with many lenders, there is a free-rider problem. Each lender is small, so it is not worth paying the fixed cost. Everybody would like to free ride, leaving it to someone else to bear the monitoring cost. As a result, no monitoring would be done. A possible solution is to hire a single monitor to check what the borrower is doing. The problem then becomes one of monitoring the monitor, to make sure that she actually monitors the borrowers. Diamond (1984) develops a model of delegated monitoring to solve this problem. Intermediaries have a diversified portfolio of projects for which they provide finance. They pre-commit to monitor borrowers by promising lenders a fixed return. If the intermediary does not monitor, then it will be unable to pay the promised return to lenders. Diamond’s model thus illustrates how banks have an incentive to act as a delegated monitor and produce the information necessary for an efficient allocation of resources. Boot and Thakor (1997) develop a model of financial system architecture that builds on this view of banks as delegated monitors. They assume there are three types of information problem. The first is that there is incomplete information about the future projects a firm has available to it. Outside investors can gather information about these possibilities. The second problem is that lenders cannot observe whether borrowers invest the funds in a risky or a safe project. The third problem is the likelihood that borrowers will have the opportunity to invest in a risky project. Boot and Thakor are able to show that the first problem can best be solved by a financial market, and the second and third problems can best be solved by intermediaries. They argue that banks will ­predominate in an emerging financial system, while the informational advantages of markets may allow them to develop in a mature financial system.

2.3  The Risk-Sharing Role of Banks One of the most important functions of the financial system is to share risk and it is often argued that financial markets are well suited to achieve this aim. As shown in

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The Roles of Banks in Financial Systems   43 Figure 2.2 and discussed in the Introduction, if both direct holdings of equities and ­indirect holdings in insurance companies and mutual funds are taken account of, a large amount of household assets are held in equity and only a small amount in banks in the US and UK. In both countries, households are exposed to substantial amounts of risk through their holdings of equities. At the other extreme, households in Japan are shielded from risk because they ultimately hold a majority of their assets in banks and very little in equities. Although not as safe as in Japan, the asset holdings of households in the Euro Area are much safer than those in the US and UK. Although the proportions of risky assets held by households in the US and UK are much higher than in Japan, and the Euro Area, this does not necessarily mean that the absolute amount of risk borne by households is greater because the amount invested in financial assets could be higher in the latter countries. However, it can be seen from Figure 2.1 that the Euro Area has a significantly lower amount of financial assets relative to GDP. Thus, taking into account the amount of wealth held in financial assets increases the differences in the amount of risk borne by households in the different countries, rather than reducing it. Not only do households hold much higher proportions in risky securities in the US and UK, they also hold more financial assets. How can one explain these differences in the amount of risk that households are apparently exposed to in different financial systems? Standard financial theory suggests that the main purpose of financial markets is to improve risk sharing. Financial markets in the US and UK are more developed by most measures than in Japan and the Euro Area. How can it be that households are exposed to much more risk in the US and UK than in Japan and the Euro Area? Allen and Gale (1997, and  2000a, chapter 6) have provided a resolution to this ­paradox. They point out that traditional financial theory has little to say about hedging non-diversifiable risks. It assumes that the set of assets is given and focuses on the efficient sharing of these risks through exchange. For example, the standard diversification argument requires individuals to exchange assets so that each investor holds a relatively small amount of any one risk. Risks will also be traded so that more risk-averse people bear less risk than people who are more risk tolerant. This kind of risk sharing is termed cross-sectional risk sharing, because it is achieved through exchanges of risk among individuals at a given point in time. However, importantly, these strategies do not eliminate macroeconomic shocks that affect all assets in a similar way. Departing from the traditional approach, Allen and Gale focus on the intertemporal smoothing of risks that cannot be diversified at a given point in time. They argue that such risks can be averaged over time in a way that reduces their impact on individual welfare through intertemporal smoothing by banks. This involves banks building up reserves when the returns on the banks’ assets are high and running them down when they are low. The banks can thus pay a relatively constant amount each period and do not impose very much risk on depositors. The authors show that the incentives for engaging in intertemporal smoothing are very different in market-based financial systems. Incomplete financial markets, on the one hand, may not allow effective intertemporal smoothing. The problem is that the long-lived asset “crowds out” the storage technology because it can be bought and sold for the same price and in addition it pays a

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44   The Theory of Banking dividend. Long-lived banks, on the other hand, can achieve intertemporal smoothing as explained above. However, for this result to hold it is necessary that the banks are not subject to substantial competition from financial markets. In fact, competition from financial markets can lead to disintermediation and the unraveling of intertemporal smoothing provided by long-lived institutions.

2.4  Banking Crises Banks perform an important role in terms of maturity transformation. They collect demandable deposits and raise funds in short-term capital markets and invest them in long-term assets. This maturity mismatch allows them to offer risk sharing to depositors but also exposes them to the possibility that all depositors withdraw their money early. Runs can involve the withdrawal of funds by depositors (retail runs) or the drying up of liquidity in the short-term capital markets (wholesale runs). In the case of the run on Northern Rock in the UK in late 2007, both occurred. Caprio and Honohan (Chapter 27, this volume) give a review of the aspects of the historical and recent banking crises and further discuss the importance of prevention and corrective policies. There were traditionally two theories to explain the origins of banking crises. One line of argument maintains that they are undesirable events caused by random deposit withdrawals unrelated to changes in the real economy. In this case they occur spontaneously as a panic resulting from “mob psychology” or “mass hysteria” (e.g., Kindleberger, 1978). Alternatively they may arise from fundamental causes that are part of the business cycle (see, e.g., Mitchell, 1941). Depositors use leading economic indicators to identify when the economy may be going into a recession, where banks will be unable to meet their liabilities and they withdraw as a result. The panic view suggests that crises are random events, unrelated to changes in the real economy. In the influential work of Bryant (1980) and Diamond and Dybvig (1983) bank runs are sunspot phenomena as documented in Cass and Shell (1983). Given the assumption of first-come, first-served and the costly liquidation of some assets there are multiple equilibria. If everybody believes no panic will occur only those with genuine liquidity needs will withdraw their funds and these demands can be met without costly liquidation of assets. However, if everybody believes a crisis will occur then it becomes a self-fulfilling prophecy as people rush to avoid being last in line. Which of these two equilibria occurs depends on extraneous variables or “sunspots.” Although sunspots have no effect on the real data of the economy, they affect depositors’ beliefs in a way that turns out to be self-fulfilling. The second view is that banking crises are a natural outgrowth of the business cycle. An economic downturn will reduce the value of bank assets, raising the possibility that banks are unable to meet their commitments. Jacklin and Bhattacharya (1988) develop a theoretical model where, if depositors receive information about an impending downturn in the cycle, they will anticipate financial difficulties in the banking sector and try

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The Roles of Banks in Financial Systems   45 to withdraw their funds. This attempt will precipitate the crisis. According to this ­interpretation, crises are not random events but a response of depositors to the arrival of sufficiently negative information on the unfolding economic circumstances. Gorton (1988) provides evidence that in the US in the late nineteenth and early twentieth centuries, a leading economic indicator based on the liabilities of failed businesses could accurately predict the occurrence of banking crises. A number of authors have developed models of banking crises caused by aggregate risk. For example, Chari and Jagannathan (1988) focus on a signal extraction problem where part of the population observes a signal about future returns. Others must then try to deduce from observed withdrawals whether an unfavorable signal was received by this group or whether liquidity needs happen to be high. Chari and Jagannathan are able to show that crises occur not only when the outlook is poor but also when liquidity needs turn out to be high. Building on the empirical work of Gorton (1988) that nineteenth century banking crises were predicted by leading economic indicators, Allen and Gale (1998) develop a model that is consistent with the business cycle view of the origins of banking crises. They assume that depositors can observe a leading economic indicator that provides public information about future bank asset returns. If there are high returns then depositors are quite willing to keep their funds in the bank. However, if the returns are sufficiently low they will withdraw their money in anticipation of low returns. There is thus a crisis. Allen and Gale (2004) develop a general equilibrium framework for understanding the normative aspects of crises. This framework is used to investigate the welfare properties of financial systems and to discover conditions under which regulation might improve the allocation of resources. An interesting feature of the Allen–Gale framework is that it explicitly models the interaction of banks and markets. Financial institutions are the main players in financial markets, which allow banks and intermediaries to share risks and liquidity. Individuals do not have direct access to markets; instead, they access markets indirectly by investing in intermediaries. Financial intermediaries and markets play important but distinct roles in the model. Intermediaries provide consumers with insurance against idiosyncratic liquidity shocks. Markets allow financial intermediaries and their depositors to share risks from aggregate liquidity and asset return shocks. Financial markets are said to be complete if it is possible for intermediaries to hedge all aggregate risks in the financial markets. This would be possible if securities contingent on all the possible combinations of aggregate liquidity and asset return shocks, or in other words all the states of nature, were available. Similarly, the risk-sharing contracts between intermediaries and consumers are said to be complete if the payoffs can be explicitly conditioned on all the possible combinations of aggregate liquidity and asset return shocks. An example of an incomplete contract would be something like debt, where the payoff on the contract does not depend explicitly on the aggregate state of liquidity demand and asset returns. Allen and Gale (2004) show that the laissez-faire allocation of resources is efficient provided markets are complete. This is the case even if contracts are incomplete. However, crises are inefficient if markets are incomplete. In this case financial fragility and contagion can occur.

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46   The Theory of Banking While the multiple equilibria theory of bank runs explains how panics may occur, it is silent on which of the two equilibria will be selected. Depositors’ beliefs are self-fulfilling and are coordinated by “sunspots.” Sunspots are convenient pedagogically but they do not have much predictive power. Since there is no real account of what triggers a ­crisis, it is difficult to use the theory for any policy analysis. The business cycle theory also has panic runs as well as fundamental runs. Again, there is no natural way to choose the equilibria. Carlsson and van Damme (1993) showed how the introduction of a small amount of asymmetric information could eliminate the multiplicity of equilibria in coordination games. They called the games with asymmetric information about fundamentals “global games.” Their work showed that the existence of multiple equilibria depends on the players having common knowledge about the fundamentals of the game. Introducing noise ensures that the fundamentals are no longer common knowledge and thus prevents the coordination that is essential to multiplicity. Morris and Shin (1998) applied this approach to models of currency crises. Rochet and Vives (2004) and Goldstein and Pauzner (2005) have applied the same technique to banking crises. Using a global games approach to ensure the uniqueness of equilibrium is theoretically appealing. However, what is really needed in addition to logical consistency is empirical evidence that such an approach is valid. In an important contribution, Chen, Goldstein, and Jiang (2010) develop a global games model of mutual fund withdrawals. Using a detailed data set they find evidence consistent with their model. This represents significant evidence supporting the global games approach. A number of subsequent papers have contributed significantly to the banking crisis literature. One example is He and Xiong (2012). They depart from the static framework and develop a dynamic model of bank runs. The model highlights the dynamic coordination problem between creditors who make rollover decisions at different times. There exists a unique equilibrium in which preemptive debt runs occur through a “rat race” among the creditors based on the publicly observable time-varying firm fundamental. He and Krishnamurthy (2011) offer an account of a financial crisis in which intermediaries play a central role as the marginal investors. They show that the crisis occurs because shocks to the capital of intermediaries reduce their risk-bearing capacity, leading to the dynamic patterns during crises in Sharpe ratios, conditional volatility, correlation in price movements, as well as riskless interest rates. Gennaioli, Shleifer, and Vishny (2013) present a model in which banks originate and trade loans, assemble them into diversified portfolios, and then get financed through external riskless debt, and show that this process of securitization allows banks to diversify idiosyncratic risk and become more interconnected through markets while concentrating their exposure to systemic risk. When tail risks are neglected, the increase in the total amount of risk-taking that securitization facilitates makes the whole system extremely fragile (see also, Shleifer and Vishny, 2010; Gennaioli, Shleifer, and Vishny, 2015). Martin, Skeie, and von Thadden (2014) develop an infinite horizon model of shadowbank runs. The non-banks engage in maturity transformation that involves borrowing short term to invest in long-term assets. An important difference with standard banking

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The Roles of Banks in Financial Systems   47 models is that the long-term assets can be traded in a market. It is shown that net asset sales in the form of securitization weakens a borrower’s balance sheet and makes the non-bank more fragile. It is also shown that if there is a shock to asset values that is s­ ufficiently strong then a run on all the non-banks is possible as a self-fulfilling expectation. Carletti and Leonello (forthcoming) develop a model where banks invest in reserves and loans, and trade loans on the interbank market to deal with liquidity shock. In one equilibrium, all banks keep enough reserves and remain solvent; while in the other, when competition is not too intense and the probability of large liquidity shocks is small enough, a group of banks hold few reserves and go bankrupt when a large liquidity shock realizes. Besides the theoretical literature, Reinhart and Rogoff (2009) provide a comprehensive empirical investigation of bank runs and bank failures in Europe from the Napoleonic Wars to the recent global financial crises that began with the US subprime crisis of 2007. They show that banking crises are an equal-opportunity menace affecting rich and poor countries alike and remain a recurring problem everywhere. Their identification of banking crises is based on narrative information about events such as bank runs or large-scale government intervention. More recently, Romer and Romer (2017) construct a quantitative, real-time, and systematic measure of financial distress for 25 OECD economies from 1967 to 2012 and find that the average decline in output following a crisis is statistically significant and persistent. Baron, Verner, and Xiong (2018) use bank equity returns and re-identify historical banking crises in forty-six countries from 1870 to 2016. Through comparing their revised chronology to previous ones based on narrative information, the aftermath of banking crises appears more severe. The prevalence of financial crises and their large impact has led many to conclude that the financial sector is unusually susceptible to shocks. One theory is that small shocks can have a large impact. A shock that initially affects only a particular region or sector, or perhaps even a few institutions, can spread by contagion through interlinkages between banks and financial institutions to the rest of the financial sector and then infect the larger economy. The theoretical literature on contagion takes two approaches. On the one hand, there are a number of papers that look for contagious effects via direct linkages. Allen and Gale (2000c) study how the banking system responds to contagion when banks are connected under different network structures. In a setting where consumers have the Diamond and Dybvig (1983) type of liquidity preferences, banks perfectly insure against liquidity shocks by exchanging interbank deposits. The connections created by swapping deposits expose the system to contagion. The authors show that incomplete ­networks are more prone to contagion than complete structures. Better-connected networks are more resilient to contagion since the proportion of the losses in one bank’s portfolio is transferred to more banks through interbank agreements. Other models capture well the network externalities created from an individual bank risk. Freixas, Parigi, and Rochet (2000) consider the case of banks that face liquidity needs as consumers are uncertain about where they are to consume. In their model, the

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48   The Theory of Banking connections between banks are realized through interbank credit lines that enable these institutions to hedge regional liquidity shocks. In the same way as in Allen and Gale (2000c), interbank connections enhance the resilience of the system to the insolvency of a particular bank. The drawback is that this weakens the incentives to close inefficient banks. Moreover, the authors find that the stability of the banking system depends crucially on whether or not many depositors choose to consume at the location of a bank that functions as a money. Dasgupta (2004) uses a global games approach to show how a unique equilibrium with contagion can arise when banks hold cross deposits. In the same spirit, Brusco and Castiglionesi (2007) show that there is a positive probability of bankruptcy and propagation of a crisis across regions when banks keep interbank deposits, and they may engage in excessive risk taking if they are not well enough capitalized. Leitner (2005) develops a model of financial networks and demonstrates that agents may be willing to bail out other agents because of the threat of contagion. However, in some cases an agent may not have enough of a case to make the necessary investment, thus the whole network may collapse. A number of papers have linked the risk of contagion to financial innovation and the accounting system in use. The common feature in this analysis is the presence of incomplete markets where liquidity provision is achieved by selling assets in the market when required. Asset prices are determined by the available liquidity or, said differently, by the “cash in the market.” It is necessary that people hold liquidity and stand ready to buy assets when they are sold. These suppliers of liquidity are no longer compensated for their opportunity cost of providing liquidity state by state. The cost must be made up on average across all states. This implies volatility in the asset prices that can in turn lead to costly and inefficient crises. In order for people to be willing to supply liquidity they must be able to make a profit in some states. In equilibrium, prices of assets will be such that the profit in the states where banks and intermediaries sell assets is sufficient to compensate the providers of liquidity for all the other states where they are not called upon to provide liquidity and simply bear the opportunity cost of holding it. In other words, asset prices are low in the states where banks and intermediaries need liquidity. But from an efficiency point of view this is exactly the wrong time for there to be a transfer from the banks and intermediaries who need liquidity to the providers of liquidity. This is because the banks’ depositors who need liquidity will already have low income because they have to withdraw early. Allen and Carletti (2006) rely on cash-in-the-market pricing to show how financial innovation in the form of credit risk transfer can create contagion across sectors and lower welfare relative to the autarky solution. They focus on the structure of liquidity shocks hitting the banking sector as the main mechanism determining contagion. When banks face a uniform demand for liquidity, they keep a sufficient amount of the short-term asset and do not need to raise additional liquidity in the market. In this case, credit risk transfer is beneficial as it improves risk sharing across sectors. Differently, when banks face idiosyncratic liquidity shocks, they invest also in the long risk-free asset and trade it in the market. The presence of credit risk transfer turns out now to be

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The Roles of Banks in Financial Systems   49 detrimental as it induces a higher need of liquidity in the market and consequently a greater variability in asset prices. This, in turn, affects banks’ ability to face their liquidity shocks as it implies a severe reduction in the price of the long asset, which banks use to hedge their liquidity risk. The banks that are selling the long asset receive a lower amount and may be unable to pay their depositors. The effect of introducing credit risk transfer depends crucially also on the accounting system in use, be it historical cost or mark-to-market accounting, as shown by Allen and Carletti (2008). When banks need to liquidate a long-term asset on an illiquid market, it may not be desirable to value such assets according to market values as it reflects the price volatility needed to induce liquidity provision. Another approach to modeling contagion focuses on indirect balance-sheet linkages. Lagunoff and Schreft (2001) construct a model where agents are linked in the sense that the return on an agent’s portfolio depends on the portfolio allocations of other agents. In their model, agents who are subject to shocks reallocate their portfolios, thus breaking some linkages. Two related types of financial crisis can occur in response. One occurs gradually as losses spread, breaking more links. The other type occurs instantaneously when forward-looking agents preemptively shift to safer portfolios to avoid future losses from contagion. Similarly, de Vries (2005) shows that there is dependency between banks’ portfolios, given the fat tail property of the underlying assets, and this carries the potential for systemic breakdown. Cifuentes, Ferrucci, and Shin (2005) present a model where financial institutions are connected via portfolio holdings. The network is complete as everyone holds the same asset. Although the authors incorporate in their model direct linkages through mutual credit exposures as well, contagion is mainly driven by changes in asset prices. Complementary to the literature on network effects, Babus (2016) considers a model where banks form links with each other in order to reduce the risk of contagion. The network is formed endogenously and serves as an insurance mechanism. At the base of the link formation process lays the same intuition developed in Allen and Gale (2000c): better-connected networks are more resilient to contagion. The model predicts a connectivity threshold above which contagion does not occur, and banks form links to reach this threshold. However, an implicit cost associated with being involved in a link prevents banks from forming connections more than required by the connectivity threshold. Banks manage to form networks where contagion rarely occurs. Castiglionesi and Navarro (2007) are also interested in whether banks manage to decentralize the network structure a social planner finds optimal. In a setting where banks invest on behalf of depositors and there are positive network externalities on the investment returns, fragility arises when banks that are not sufficiently capitalized gamble with depositors’ money. When the probability of bankruptcy is low, the decentralized solution approximates the first best. Allen, Babus, and Carletti (2012) develop a model of contagion based on the interaction of asset commonality between banks and the use of short-term debt. Banks swap assets to diversify their individual risk. Two asset structures arise. In a clustered ­structure, groups of banks hold common asset portfolios and default together. In an

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50   The Theory of Banking unclustered structure, defaults are more dispersed. The portfolio quality of individual banks is opaque but can be inferred by creditors from aggregate signals about bank ­solvency. When bank debt is short term, creditors do not roll over in response to adverse signals and all banks are inefficiently liquidated. This information contagion is more likely under clustered asset structures. In contrast, when bank debt is long term, welfare is the same under both asset structures. Two other important recent contributions on contagion risk and network architecture are Elliott, Golub, and Jackson (2014) and Acemoglu, Ozdaglar, and Tahbaz-Saleshi (2015). Elliott, Golub, and Jackson (2014) develop a general model and examine network structure and contagion. They document two key aspects of the crossholding of financial organizations: integration (greater dependence on counterparties) and diversification (more counterparties per organization), which have different, non-monotonic effects on the extent of cascades. Integration can increase the likelihood of a cascade once an initial failure occurs, while it can also reduce the likelihood of the first failure due to less sensitivity to financial organizations’ own investments. Diversification also faces trade-offs: contagion versus better insurance against one another’s failures. Acemoglu, Ozdaglar, and Tahbaz-Saleshi (2015) argue that when the magnitude of negative shocks affecting financial institutions is beyond a certain point, concentrated interconnections serve as a mechanism for the propagation of negative shocks and lead to a more fragile financial system. In addition to these theoretical investigations, there has been considerable empirical interest in considering whether there is evidence of contagious failures of financial institutions that result from the mutual claims they have on one another. Most of these papers use balance-sheet information to estimate bilateral credit relationships for different banking systems. Subsequently, the stability of the interbank market is tested by simulating the breakdown of a single bank. For example, Upper and Worms (2004) analyze the German banking system. They show that the failure of a single bank could lead to the breakdown of up to 15 percent of the banking sector in terms of assets. Cocco, Gomes, and Martins (2009) consider Portugal; Furfine (2003) the US; Boss et al. (2004) Austria; and Degryse and Nguyen (2007) Belgium. Iyer and Peydró (2011) conduct a case study of interbank linkages resulting from a large bank failure due to fraud. Jorion and Zhang (2009) provide evidence of credit contagion via direct counterparty effects. Using evidence from interbank lending, Gai, Haldane, and Kapadia (2011) simulate how greater complexity and concentration in the network may amplify the fragility during systemic liquidity crises with the interbank market collapses. Upper (2010) contains a survey of this literature. The main conclusion of the literature is that contagion is usually not a serious risk provided there are no significant price movements in response to the ­turmoil. If there are, as in Cifuentes, Ferrucci, and Shin (2005), then contagion effects can be significant. The crisis that started in 2007 illustrates the practical importance of contagion. The usual justification for intervention by central banks and governments to prevent the bankruptcy of systemic financial institutions is that this will prevent contagion. This was the argument used by the Federal Reserve for intervening to ensure Bear Sterns did not go bankrupt in March 2008, for example (see Bernanke,  2008). The bankruptcy of

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The Roles of Banks in Financial Systems   51 Lehman Brothers a few months later in September of 2008 illustrated just how damaging contagion can be. The process did not work in quite the way envisaged in the academic literature and occurred despite the judgment of the Federal Reserve and Treasury that Lehman should not be saved. The first spillover was to the money market mutual fund sector. Reserve Capital “broke the buck” as it held a significant amount of paper issued by Lehman. This led to many withdrawals from other money market mutual funds and four days after Lehman announced bankruptcy, the government was forced to announce guarantees for the entire sector. After seeing Lehman Brothers collapse, confidence in the creditworthiness of banks and other financial institutions and firms fell significantly and this is when the financial crisis started to spill over into the real economy and had such a damaging effect on it. Going forward, much more research is needed to understand the many channels of contagion in a crisis. The crisis that started in 2007 also provides a dramatic example of how damaging banking crises can be. The causes for its occurrence are not fully agreed, but many attribute them to the bad incentives in the origination of mortgages and their securitization, the provision of ratings for securitizations, and the risk management systems of investment firms. The large global impact of the crisis suggests, however, that the problems with subprime mortgages are a symptom rather than the cause. One main problem is that there was a bubble, first in stock prices and then in property prices, and the economic system is now suffering the fallout from the collapse of these bubbles. The monetary policies of central banks, particularly the US Federal Reserve, appear to have been too loose and have focused too much on consumer price inflation while ignoring asset price inflation. Moreover, the Asian crisis of 1997 and the policies of the IMF during that crisis led to a desire among Asian governments to hoard funds. This created important global imbalances that expanded the credit available and helped to fuel the bubble. Allen and Gale (2000b) show how such an expansion of credit can create a bubble. Whatever the reasons behind the crisis, its effects certainly spread to the real economy. Most industrialized and non-industrialized countries experienced problems with many of their industries entering into recession. The problems were multiple. On the one hand, the difficulties of the financial sector induced intermediaries to tighten their credit standards, thus making it more difficult for firms to obtain credit and at good rates. On the other hand, the sharp fall in consumer demand decreased sales and future orders. As in the financial sector, the problems were not confined to single firms but affected whole industries. The car industry is one dramatic example, but also other manufacturing industries, construction, and many others were placed under considerable pressure. The aftermath of a systemic banking crisis also puts significant strain on government resources. As shown in Reinhart and Rogoff (2011), on average, government debt rises by 86 percent during the three years following a banking crisis due to the large scale of bank bailouts or the collapsing revenues. In some circumstances, if banks are overly exposed to government paper, banking crisis and debt crisis may also be more or less simultaneous. There is a large body of literature on policies to prevent banking crises that are outside the scope of this chapter. Surveys in this area that cover this literature are Benoit et al. (2017) and Allen, Goldstein, and Jagtiani (2018).

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52   The Theory of Banking

2.5  Banks and Growth Another important role of banks is in spurring growth. There has been a debate on the relative effectiveness of banks compared to financial markets in doing this. This debate was originally conducted in the context of German and UK growth in the late nineteenth and early twentieth centuries. Gerschenkron (1962) argued that the bank-based system in Germany allowed a closer relationship between bankers providing the finance and industrial firms than was possible in the market-based system in the UK. Goldsmith (1969) pointed out that, although the manufacturing industry grew much faster in Germany than in the UK in the late nineteenth and early twentieth centuries, the overall growth rates were fairly similar. More recently, Levine (2002) uses a broad database ­covering forty-eight countries over the period 1980–95. He finds that the distinction between bank-based and market-based systems is not an interesting one for explaining the finance–growth nexus. Rather, elements of a country’s legal environment and the quality of its financial services are most important for fostering general economic growth. In contrast, in a study of thirty-six countries from 1980–95, Tadassee (2002) does find a difference between bank-based and market-based financial systems. For underdeveloped financial sectors, bank-based systems outperform market-based systems, while for developed financial sectors, market-based systems outperform bankbased systems. Levine and Zervos (1998) show that higher stock market liquidity or greater bank development leads to higher growth, irrespective of the development of the other. There is some evidence that financial markets and banks are complements rather than substitutes. Demirgüç-Kunt and Maksimovic (1998) show that more developed stock markets tend to be associated with increased use of bank finance in developing countries. More recent evidence in Beck and Demirgüç-Kunt (2009), shows that a general deepening of the financial sector over time is more pronounced in the high-income countries, and more significant for markets than for banks. Consistent findings are documented also by Demirgüç-Kunt, Feyen, and Levine (2013) using a new database that covers seventy-two countries over the period from 1980 to 2008. Furthermore, they also find evidence of the changing importance of banks and securities markets throughout the development of the real economy. As the economy grows, the association between output growth and bank development becomes less pronounced, while the association between output growth and market development gets stronger. There is extensive theoretical literature on the relative merits of bank-based and market-based systems for innovation and growth. Bhattacharya and Chiesa (1995) consider a model of R&D incentives and financing. In a market system, lenders learn the value of each firm’s R&D at the interim stage after R&D has been undertaken but before production takes place. The lenders can share the information among the firms and will do so if it is in their interest. Bhattacharya and Chiesa show that their incentives to do this correspond to maximizing the aggregate value of the firms’ R&D projects. Also, a collusive agreement can be structured so that only one firm actually produces at the

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The Roles of Banks in Financial Systems   53 production stage. However, this collusion creates a free-rider problem and reduces incentives to undertake R&D at the first stage. If this incentive problem is severe enough, bilateral financing may be preferable. Under this arrangement, each firm is financed by one bank and there is no scope for information sharing. As a result, each firm’s R&D information remains proprietary. Allen and Gale (1999 and 2000a, chapter 13) ask whether financial markets or banks are better at providing finance for projects where there is diversity of opinion as in the development of new technologies. Diversity of opinion arises from differences in prior beliefs, rather than differences in information. The advantage of financial markets is that they allow people with similar views to join together to finance projects. This will be optimal provided the costs necessary for each investor to form an opinion before investment decisions are made are sufficiently low. Finance can be provided by the market even when there is great diversity of opinion among investors. Intermediated finance involves delegating the financing decision to a manager who expends the cost necessary to form an opinion. There is an agency problem in that the manager may not have the same prior belief as the investor. This type of delegation turns out to be optimal when the costs of forming an opinion are high and there is likely to be considerable agreement in any case. The analysis suggests that market-based systems will lead to more innovation than bank-based systems. A recent survey of the literature on the financial structure of the economy and ­economic growth is contained in Allen, Gu, and Kowalewski (2018). Cettorelli and Blank (Chapter  30, this volume) conduct a literature survey on banking and growth more specifically.

2.6  The Corporate Governance Role of Banks The importance of equity ownership by financial institutions in Japan and Germany, and the lack of a strong market for corporate control in these countries, have led to the suggestion that the agency problem in these countries is solved by banks acting as outside monitors for large corporations. In Japan, this system of monitoring is known as the main bank system. The characteristics of this system are the long-term relationship between a bank and its client firm, the holding of both debt and equity by the bank, and the active intervention of the bank should its client become financially distressed. It has been widely argued that this main bank relationship ensures the bank acts as a delegated monitor and helps to overcome the agency problem between managers and the firm. However, the empirical evidence on the effectiveness of the main bank system is mixed (see, e.g., Hoshi, Kashyap, and Scharfstein, 1990, 1993; Aoki and Patrick, 1994; Hayashi, 2000). Overall, the main bank system appears important in times of financial distress, but less important when a firm is doing well. More recently, Dass and Massa

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54   The Theory of Banking (2011) find that a stronger bank–firm relationship can introduce better monitoring and improve the borrower’s corporate governance as it increases the sensitivity of CEO compensation to performance. Some other studies document that one key mechanism that facilitates the governance role of banks is the covenants in loan contracts (Nini, Smith, and Sufi, 2012; Vashishtha, 2014) because covenant violations give banks the right to demand immediate repayment of the loan and terminate future lending commitments, allowing banks to discipline managers and influence firms’ decisions. In Germany, the counterpart of the main bank system is the Hausbank system. Banks tend to have very close ties with industry and form long-run relationships with firms, not only because of the loans they make and the shares they directly own, but also because of the proxies they are able to exercise. A number of studies have provided evidence on the  effectiveness of the outside monitoring of German banks (see, e.g., Gorton and Schmid, 2000). In an important book, Edwards and Fischer (1994) have argued that in Germany the corporate governance role of banks has been overemphasized in the literature. They provide a variety of evidence that banks do not have the degree of influence as lenders, shareholders, or voters of proxies that is usually supposed. For example, they find that the number of votes controlled in a company is only weakly related to the number of representatives the bank has on the supervisory board. Hellwig (1991, 1994) also provides a number of theoretical arguments concerning the disadvantages of the banking system in Germany.

2.7  Relationship Banking There is growing literature that analyzes the advantages and disadvantages of relationships in banking (see, for reviews, Boot, 2000; Gorton and Winton, 2003; Degryse and Ongena, 2008; Boot and Thakor, Chapter 3, this volume). If on the one hand, close and durable relationships provide better access to firms and ameliorate some of the information problems characterizing lending relationships, they also involve inefficiencies related to the hold-up and the soft-budget-constraint problems, on the other. The hold-up problem refers to the possibility that a relationship bank uses the superior private information it possesses about the firm to extract rents, thus distorting entrepreneurial incentives and causing inefficient investment choices (Sharpe,  1990; Rajan,  1992; von Thadden, 1995). The soft-budget-constraint problem concerns the inability of a relationship lender to commit itself to a particular course of action in advance. Although it is optimal to threaten to terminate the availability of credit in advance, once the borrower has defaulted, the first loan becomes a “sunk cost.” If the firm has another good project we should expect that the lender will continue to extend credit, even if the borrower defaults. Renegotiation thus creates a time-consistency problem. The threat to terminate credit creates good incentives for the borrower to avoid the risk of default. Termination of credit is not Pareto-efficient ex post, but the incentive effect makes both parties better

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The Roles of Banks in Financial Systems   55 off. However, if the borrower anticipates that the lender will not carry out the threat in practice, the incentive effect disappears. Although the lender’s behavior is now ex post optimal, both parties may be worse off ex ante. Multiple-bank relationships can help mitigate the drawbacks of single-bank relationships in terms of the hold-up and the soft-budget-constraint problems. As for the former, borrowing from multiple banks can restore competition among banks and, consequently, improve entrepreneurial incentives (Padilla and Pagano, 1997). As for the latter, Dewatripont and Maskin (1995) argue that, by complicating the refinancing process and making it less profitable, multiple-bank lending allows banks to commit not to extend further inefficient credit. Similarly, Bolton and Scharfstein (1996) show that multiple-bank lending reduces entrepreneurial incentives to default strategically because it complicates debt renegotiation. The number of bank relationships also has important implications for banks’ role as monitors. In a context where both firms and banks are subject to moral hazard problems, Carletti (2004) analyzes how the number of bank relationships influences banks’ monitoring incentives, the level of loan rates, and a firm’s choice between single and multiple bank relationships. Multiple-bank lending suffers from duplication of effort and free-riding but it benefits from diseconomies of scale in monitoring, thus involving a lower level of monitoring but not necessarily higher loan rates than single lending. Since banks choose their monitoring effort to maximize their expected profits, they may choose a level of monitoring which is excessive from the firm’s perspective. When this is the case, the firm may choose multiple-bank relationships in order to reduce the overall level of monitoring. The attractiveness of such a choice increases with the cost of monitoring, the firm’s private benefit and expected profitability. In a similar framework, Carletti, Cerasi, and Daltung (2007) analyze the circumstances where banks with limited diversification opportunities find it profitable to enter into multiple-bank relationships. They show that sharing lending allows banks to better diversify their portfolios but still entail duplication of effort and free-riding. When the benefit of greater diversification dominates, multiple-bank lending leads to higher overall monitoring as a way to mitigate the agency problem between banks and depositors and achieve higher banks’ expected profits. The attractiveness of multiple-bank lending now decreases with the level of banks’ (inside) equity and firms’ prior profitability, while it increases with the cost of monitoring. Other rationales for multiple-bank relationships relate to firms’ desire to reduce liquidity risk and disclose information through credit relationships. Detragiache, Garella, and Guiso (2000) show that, when relationship banks face internal liquidity problems, borrowing from multiple banks can avoid early liquidation of profitable projects. Yosha (1995) suggests that firms may prefer multiple-bank lending as a way to disclose confidential information about the quality of their projects and to avoid aggressive behavior by competitors. Recently, Bolton et al. (2016) extend the existing multiple relationship-lending model by introducing an aggregate shock together with idiosyncratic cash-flow risk for non-financial corporations. They find that the firms relying on a banking relationship

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56   The Theory of Banking are better able to weather a crisis and are less likely to default than firms only relying on transaction lending. The relationship firms pay higher borrowing costs on their relationship loans in normal times. Moreover, relationship banks need a capital buffer that is used to preserve the lending relationship in bad times. There have also been some empirical evidences on the benefits of relationship banking. For example, through conducting face-to-face interviews with bank chief executive officers in twenty-one countries, Beck et al. (2018) find that relationship banking is not associated with credit constraints during a credit boom, which significantly alleviates the constraints during a downturn. Such a positive role of relationship banking is more pronounced for small and opaque firms and in regions with more severe recessions. A few studies (e.g., Agarwal and Hauswald, 2010; Ergungor and Moulton, 2014) argue that relationship banking reduces default risks based on unobservable soft information. However, using the setting of consumer credit markets, Agarwal et al. (2018) show that relationship accounts exhibit lower probabilities of default and attrition, and higher utilization rates, suggesting that relationship can also benefit retail banking through providing hard information instead of soft information. As a final remark, note that there are ways, other than multiple-bank relationships, to solve the problem of a lack of commitment affecting exclusive bank relationships. For example, financial institutions may develop a valuable reputation for maintaining commitments. In any one case, it is worth incurring the small cost of a suboptimal action in order to maintain the value of the reputation. Incomplete information about the borrower’s type may lead to a similar outcome. If default causes the institution to believe it is more likely that the defaulter is a bad type, then it may be optimal to refuse to deal with a firm after it has defaulted. Institutional strategies such as delegating decisions to agents who are given no discretion to renegotiate may also be an effective commitment device. Several authors (Hart and Moore, 1988; Huberman and Kahn, 1988; Gale, 1991; Allen and Gale, 2000a, chapter 10) have argued that, under certain circumstances, renegotiation is welfare-improving. In that case, the argument is reversed. Intermediaries that establish long-term relationships with clients may have an advantage over financial markets precisely because it is easier for them to renegotiate contracts.

2.8  Concluding Remarks We have covered a number of roles of banks in the financial system in this chapter. Banks act as delegated monitors and ensure that firms use the resources allocated to them effectively. They also play an important role in sharing risk in the economy by diversifying and smoothing fluctuations over time. These are positive aspects of the roles banks play. However, the fixed nature of the claims they issue can cause fragility in the financial system. Banks are often at the center of financial crises as in the crisis that started in the summer of 2007. They can help spread crises if there is contagion and small shocks can have a large effect on the financial system and the economy. Banks play an important

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The Roles of Banks in Financial Systems   57 role in providing funds for firms and helping them and the economy to grow. They are also important for corporate governance, particularly in countries like Germany where bankers sit on boards and control a significant number of proxy votes. Finally, banks can help overcome asymmetric information problems by forming long-lived relationships with firms. There are a number of other roles that we have not covered as they are the subjects of other chapters of this Handbook, including the role of banks in payments systems, presented in Chapter 10 of this volume. Another of interest, which featured in the last edition of this Handbook, is the role of banks in underwriting securities (see Morrison, 2014). There remain other roles that are just as important, but less well understood. Many of these involve the interaction of banks with financial markets of various kinds. The recent crisis has illustrated that securitization can lead to significant problems because bank incentives are fundamentally different when loans are sold rather than retained. The role that banks play in derivative markets is also not fully understood. If there is a chain of counterparties, how can that risk be fully assessed if the chain is opaque as it usually is? Finally, how can banks be prevented from taking risks if they retain the profits when there are good outcomes but are bailed out by the government in times of crisis? These are all important issues for future research.

References Acemoglu, D., Ozdaglar, A., and Tahbaz-Saleshi, A. (2015). “Systemic Risk and Stability in Financial Networks,” American Economic Review, 105, 564–608. Agarwal, S. and Hauswald, R. (2010). “Distance and Private Information in Lending,” Review of Financial Studies, 23, 2757–88. Agarwal, S., Chomsisengphet, S., Liu, C., and Song, C. (2018). “Benefits of Relationship Banking: Evidence from Consumer Credit Markets,” Journal of Monetary Economics, 96, 16–32. Allen, F. and Carletti, E. (2006). “Credit Risk Transfer and Contagion,” Journal of Monetary Economics, 53, 89–111. Allen, F. and Carletti, E. (2008). “Mark-to-Market Accounting and Liquidity Pricing,” Journal of Accounting and Economics, 46(2–3), 358–78. Allen, F. and Gale, D. (1997). “Financial Markets, Intermediaries, and Intertemporal Smoothing,” Journal of Political Economy, 105, 523–46. Allen, F. and Gale, D. (1998). “Optimal Financial Crises,” Journal of Finance 53, 1245–84. Allen, F. and Gale, D. (1999). “Diversity of Opinion and the Financing of New Technologies,” Journal of Financial Intermediation, 8, 68–89. Allen, F. and Gale, D. (2000a). Comparing Financial Systems (Cambridge, MA: MIT Press). Allen, F. and Gale, D. (2000b). “Bubbles and Crises,” Economic Journal, 110, 236–55. Allen, F. and Gale, D. (2000c). “Financial Contagion,” Journal of Political Economy, 108, 1–33. Allen, F. and Gale, D. (2004). “Financial Intermediaries and Markets,” Econometrica, 72, 1023–61. Allen, F., Babus, A., and Carletti, E. (2012). “Asset Commonality, Debt Maturity and Systemic Risk,” Journal of Financial Economics, 104, 519–34. Allen, F., Goldstein, I., and Jagtiani, J. (2018). “The Interplay Among Financial Regulations, Resilience and Growth,” Journal of Financial Services Research, 53, 141–62.

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58   The Theory of Banking Allen, F., Gu, X., and Kowalewski, O. (2018). “Financial Structure, Economic Growth and Development,” in T. Beck and R. Levine (eds.), Handbook of Finance and Development (Cheltenham: Edward Elgar). Aoki, M. and Patrick, H. (eds.) (1994). The Japanese Main Bank System: Its Relevancy for Developing and Transforming Economies (New York: Oxford University Press), 592–633. Babus, A. (2016). “The Formation of Financial Networks,” RAND Journal of Economics, 47, 239–72. Baron, M., Verner, E., and Xiong, W. (2018). “Identifying Banking Crises,” Working Paper, Princeton University, Princeton, NJ. Beck, T. and Demirgüç-Kunt, A. (2009). “Financial Institutions and Markets across Countries and Over Time-Data and Analysis,” World Bank Policy Research Working Paper No. 4943. Beck, T., Degryse, H., Haas, R., and van Horen, N. (2018). “When Arm’s Length is Too Far: Relationship Banking over the Credit Cycle,” Journal of Financial Economics, 127, 174–96. Benoit, S., Colliard, J., Hurlin, C., and Perignon, C. (2017). “Where the Risks Lie: A Survey on Systemic Risk,” Review of Finance, 21, 109–52. Bernanke, B. (2008). “Reducing Systemic Risk,” opening speech at the 2008 Jackson Hole Symposium, Federal Reserve Bank of Kansas City. Bhattacharya, S. and Chiesa, G. (1995). “Financial Intermediation with Proprietary Information,” Journal of Financial Intermediation, 4, 328–57. Bolton, P. and Scharfstein, D. (1996). “Optimal Debt Structure and the Number of Creditors,” Journal of Political Economy, 104, 1–25. Bolton, P., Freixas, X., Gambacorta, L., and Mistrulli, P. (2016). “Relationship and Transaction Lending in a Crisis,” Review of Financial Studies, 29, 2643–76. Boot, A. (2000). “Relationship Banking: What Do We Know?” Journal of Financial Intermediation, 9, 7–25. Boot, A. and Thakor, A. (1997). “Financial System Architecture,” Review of Financial Studies, 10, 693–733. Boss, M., Elsinger, H., Thurner, S., and Summer, M. (2004). “Network Topology of the Interbank Market,” Quantitative Finance, 4, 1–8. Brusco, S. and Castiglionesi, F. (2007). “Liquidity Coinsurance, Moral Hazard and Financial Contagion,” Journal of Finance, 62, 2275–302. Bryant, J. (1980). “A Model of Reserves, Bank Runs, and Deposit Insurance,” Journal of Banking and Finance, 4, 335–44. Carletti, E. (2004). “The Structure of Bank Relationships, Endogenous Monitoring and Loan Rates,” Journal of Financial Intermediation, 13, 58–86. Carletti, E. and Leonello, A. (forthcoming). “Credit Market Competition and Liquidity Crises,” Review of Finance. Carletti, E., Cerasi, V., and Daltung, S. (2007). “Multiple-bank Lending: Diversification and Free-Riding in Monitoring,” Journal of Financial Intermediation, 16, 425–51. Carlsson, H. and van Damme, E. (1993). “Global Games and Equilibrium Selection,” Econometrica, 61, 989–1018. Cass, D. and Shell, K. (1983). “Do Sunspots Matter?” Journal of Political Economy, 91, 193–227. Castiglionesi, F. and Navarro, N. (2007). “Optimal Fragile Financial Networks,” CentER Discussion Paper 2007-100, Tilburg University. Chari, V. and Jagannathan, R. (1988). “Banking Panics, Information, and Rational Expectations Equilibrium,” Journal of Finance, 43, 749–60.

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The Roles of Banks in Financial Systems   59 Chen, Q., Goldstein, I., and Jiang, W. (2010). “Payoff Complementarities and Financial Fragility: Evidence from Mutual Fund Flows,” Journal of Financial Economics, 97, 239–62. Cifuentes, R., Ferrucci, G., and Shin, H. (2005). “Liquidity Risk and Contagion,” Journal of European Economic Association, 3. Cocco, J., Gomes, F., and Martins, N. (2009). “Lending Relationships in the Interbank Market,” Journal of Financial Intermediation, 18, 24–48. Dasgupta, A. (2004). “Financial Contagion through Capital Connections: A Model of the Origin and Spread of Bank Panics,” Journal of the European Economic Association, 6, 1049–84. Dass, N. and Massa, M. (2011). “The Impact of a Strong Bank–Firm Relationship on the Borrowing Firm,” Review of Financial Studies, 24, 1204–60. Degryse, H. and Nguyen, G. (2007). “Interbank Exposures: An Empirical Examination of Systemic Risk in the Belgian Banking System,” International Journal of Central Banking, 3(2), 123–71. Degryse, H. and Ongena, S. (2008). “Competition and Regulation in the Banking Sector: A  Review of the Empirical Evidence on the Sources of Bank Rents,” in A.  Thakor and A. Boot (eds.), Handbook of Financial Intermediation and Banking (Amsterdam: Elsevier), 483–554. Demirgüç-Kunt, A. and Maksimovic, V. (1998). “Law, Finance, and Firm Growth,” Journal of Finance, 53, 2107–37. Demirgüç-Kunt, A., Feyen, E., and Levine, R. (2013). “The Evolving Importance of Banks and Securities Markets,” The World Bank Economic Review, 27, 476–90. Detragiache, E., Garella, P., and Guiso, L. (2000). “Multiple vs. Single Banking Relationships: Theory and Evidence,” Journal of Finance, 55, 1133–61. de Vries, C. (2005). “The Simple Economics of Bank Fragility,” Journal of Banking and Finance, 29, 803–25. Dewatripont, M. and Maskin, E. (1995). “Credit and Efficiency in Centralized and Decentralized Economies,” Review of Economic Studies, 62, 541–55. Diamond, D. (1984). “Financial Intermediation and Delegated Monitoring,” Review of Economic Studies, 51, 393–414. Diamond, D. and Dybvig, P. (1983). “Bank Runs, Deposit Insurance, and Liquidity,” Journal of Political Economy, 91, 401–19. Edwards, J. and Fischer, K. (1994). Banks, Finance and Investment in Germany (Cambridge: Cambridge University Press). Elliott, M., Golub, B., and Jackson, M. (2014). “Financial Networks and Contagion,” American Economic Review, 104, 3315–153. Ergungor, O. and Moulton, S. (2014). “Beyond the Transaction: Banks and Mortgage Default of Low-Income Homebuyers,” Journal of Money, Credit and Banking, 46, 1721–52. Freixas, X., Parigi, B., and Rochet, J. (2000). “Systemic Risk, Interbank Relations and Liquidity Provision by the Central Bank,” Journal of Money, Credit and Banking, 32, 611–38. Furfine, C. (2003).“The Interbank Market During a Crisis,” Journal of Money, Credit and Banking, 35, 111–28. Gai, P., Haldane, A., and Kapadia, S. (2011). “Complexity, Concentration and Contagion,” Journal of Monetary Economics, 58, 453–70. Gale, D. (1991). “Optimal Risk Sharing through Renegotiation of Simple Contracts,” Journal of Financial Intermediation, 1, 283–306. Gennaioli, N., Shleifer, A., and Vishny, R. (2013). “A Model of Shadow Banking,” Journal of Finance, 68, 1331–63.

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60   The Theory of Banking Gennaioli, N., Shleifer, A., and Vishny, R. (2015). “Neglected Risks: The Psychology of Financial Crises.” American Economic Review: Papers & Proceedings, 105, 310–14. Gerschenkron, A. (1962). Economic Backwardness in Historical Perspective (Cambridge, MA: Harvard University Press). Goldsmith, R. (1969). Financial Structure and Development (New Haven, CT: Yale University Press). Goldstein, I. and Pauzner, A. (2005). “Demand-Deposit Contracts and the Probability of Bank Runs,” Journal of Finance, 60, 1293–327. Gorton, G. (1988). “Banking Panics and Business Cycles,” Oxford Economic Papers, 40, 751–81. Gorton, G. and Schmid, F. (2000). “Universal Banking and the Performance of German Firms,” Journal of Financial Economics, 58, 29–80. Gorton, G. and Winton, A. (2003). “Financial Intermediation,” in G.  Constantinides, M. Harris, and R. Stulz (eds.), Handbook of the Economics of Finance, Vol. 1A (Amsterdam: North-Holland), 431–552. Hart, O. and Moore, J. (1988). “Incomplete Contracts and Renegotiation,” Econometrica, 56, 755–85. Hayashi, F. (2000). “The Main Bank System and Corporate Investment: An Empirical Reassessment,” in M.  Aoki and G.  Saxonhouse (eds.), Finance, Governance, and Competitiveness in Japan (Oxford and New York: Oxford University Press), 81–97. He, Z. and Krishnamurthy, A. (2011). “A Model of Capital and Crises,” Review of Economic Studies, 79, 735–77. He, Z. and Xiong, W. (2012). “Dynamic Debt Runs,” Review of Financial Studies, 25, 1799–843. Hellwig, M. (1991). “Banking, Financial Intermediation and Corporate Finance,” in A. Giovannini and C. Mayer (eds.), European Financial Integration (New York: Cambridge University Press), 35–63. Hellwig, M. (1994). “Liquidity Provision, Banking, and the Allocation of Interest Rate Risk,” European Economic Review, 38, 1363–89. Hoshi, T., Kashyap, A., and Scharfstein, D. (1990). “The Role of Banks in Reducing the Costs of Financial Distress in Japan,” Journal of Financial Economics, 27, 67–8. Hoshi, T., Kashyap, A., and Scharfstein, D. (1993). “The Choice Between Public and Private Debt: An Analysis of Post-Deregulation Corporate Financing in Japan,” NBER Working Paper No. 4421. Huberman, G. and Kahn, C. (1988). “Limited Contract Enforcement and Strategic Renegotiation,” American Economic Review, 78, 471–84. Iyer, R. and Peydro, J.  L. (2011). “Interbank Contagion at Work: Evidence from a Natural Experiment,” Review of Financial Studies, 24(4), 1337–77. Jacklin, C. J. and Bhattacharya, S. (1988). “Distinguishing Panics and Information-based Bank Runs: Welfare and Policy Implications,” Journal of Political Economy, 96(3), 568–92. Jorion, P. and Zhang, G. (2009). “Credit Contagion from Counterparty Risk,” Journal of Finance, 64(5), 2053–87. Kindleberger, C. (1978). Manias, Panics, and Crashes: A History of Financial Crises (New York: Basic Books). Lagunoff, R. and Schreft, S. (2001). “A Model of Financial Fragility,” Journal of Economic Theory, 99, 220–64. Leitner, Y. (2005). “Financial Networks: Contagion, Commitment and Private Sector Bailout,” Journal of Finance, 60(6), 2925–53.

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The Roles of Banks in Financial Systems   61 Levine, R. (2002). “Bank-Based or Market-Based Financial Systems: Which is Better?” Journal of Financial Intermediation, 11, 398–428. Levine, R. and Zervos, S. (1998). “Stock Markets, Banks and Economic Growth,” American Economic Review, 88, 537–58. Martin, A., Skeie, D., and von Thadden, E. (2014). “The Fragility of Short-term Secured Funding Markets, Journal of Economic Theory, 149, 15–42. Mitchell, W. (1941). Business Cycles and Their Causes (Berkeley, CA: University of California Press). Morris, S. and Shin, H. (1998). “Unique Equilibrium in a Model of Self-Fulfilling Currency Attacks,” American Economic Review, 88, 587–97. Morrison, A. D. (2014). “Universal Banking,” in A. N. Berger, P. Molyneux, and J. O. S. Wilson (eds.), Oxford Handbook of Banking, 2nd edn (Oxford: Oxford University Press), 113–38. Nini, G., Smith, D., and Sufi, A. (2012). “Creditor Control Rights, Corporate Governance, and Firm Value,” Review of Financial Studies, 6, 1713–61. Padilla, A.  J. and Pagano, M. (1997). “Endogenous Communication Among Lenders and Entrepreneurial Incentives,” Review of Financial Studies, 10, 205–36. Rajan, R. (1992). “Insiders and Outsiders: The Choice Between Informed and Arm’s-Length Debt,” Journal of Finance, 47, 1367–400. Reinhart, C. M. and Rogoff, K. S. (2009). This Time is Different: Eight Centuries of Financial Folly (Princeton, NJ: Princeton University Press). Reinhart, C. M. and Rogoff, K. S. (2011). “From Financial Crash to Debt Crisis,” American Economic Review, 101(5), 1676–706. Rochet, J. and Vives, X. (2004). “Coordination Failures and the Lender of Last Resort: Was Bagehot Right After All?” Journal of the European Economic Association, 2, 1116–47. Romer, C. and Romer, D. (2017). “New Evidence on the Aftermath of Financial Crises in Advanced Countries,” American Economic Review, 107, 3072–118. Sharpe, S. (1990). “Asymmetric Information, Bank Lending, and Implicit Contracts: A Stylized Model of Customer Relationships,” Journal of Finance, 45, 1069–87. Shleifer, A. and Vishny, R. (2010). “Unstable Banking,” Journal of Financial Economics, 97, 306–18. Tadassee, S. (2002). “Financial Architecture and Economic Performance: International Evidence,” Journal of Financial Intermediation, 11, 429–54. Upper, C. (2010). “Simulation Methods to Assess the Danger of Contagion in Interbank Markets,” Journal of Financial Stability, 7, 111–25. Upper, C. and Worms, A. (2004). “Estimating Bilateral Exposures in the German Interbank Market: Is there a Danger of Contagion?” European Economic Review, 48, 827–49. Vashishtha, R. (2014). “The Role of Bank Monitoring in Borrowers’ Discretionary Disclosure: Evidence from Covenant Violations,” Journal of Accounting and Economics, 57, 176–95. von Thadden, E. (1995). “Long-Term Contracts, Short-Term Investment and Monitoring,” Review of Economic Studies, 62, 557–75. Yosha, O. (1995). “Information Disclosure Costs and the Choice of Financing Source,” Journal of Financial Intermediation, 4, 3–20.

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chapter 3

Com m erci a l Ba n k i ng a n d Sh a dow Ba n k i ng The Accelerating Integration of Banks and Markets and its Implications for Regulation Arnoud W. A. Boot and Anjan V. Thakor

3.1 Introduction The financial sector has evolved rapidly over the last decades, with the impetus for change provided by deregulation and advances in information technology. Competition has become more intense. Interbank competition within domestic markets as well as across national borders and competition from financial markets have gained importance. Both the institutional structure of financial institutions and the boundary between financial institutions and financial markets have been transformed. At no stage has this blurring of boundaries been more evident than during years leading up to the 2007–9 financial crisis, with the emergence of a large shadow-banking sector as a key manifestation. Pozsar et al. (2010) estimate the size of the shadow-banking system in the US at its peak in June 2007 at $22 trillion, surpassing easily total US banking assets, and $16 trillion in 2010, but estimates (and measures) vary greatly (see Claessens et al., 2012).1 A major issue with shadow banking is that because it involves qualitative asset transformation, it is inherently risky and may pose systematic risk that threatens financial stability

1  In its Global Shadow Banking Monitoring Report 2017, the Financial Stability Board covering t­ wenty-eight jurisdictions with over 80 percent of world GDP, reports $45 trillion assets in shadow banks (FSB, 2018). See their “narrow” definition that confines shadow banking to activities posing financial stability risk involving a dependence on short-term funding risks and/or having bank-run-like features; it excludes assets in institutions that are not susceptible to runs like pension funds, (unlevered) closed-end funds, and insurance companies.

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Commercial Banking and Shadow Banking   63 (FSB, 2018).2 There have been other developments that have the potential for creating unforeseen risks. For example, since the 2007–9 financial crisis, P2P lending has grown rapidly both in the US and Europe, raising questions about the role of non-intermediated credit relative to intermediated credit. This chapter reviews the literature related to these developments and uses it to examine the importance of this changing landscape for the structure of the financial services industry and the design and organization of regulation. As we will argue, the increasingly intertwined nature of banks and financial markets is not without costs. In particular, as the financial crisis of 2007–9 has illustrated, systemic risks may have become more prevalent. In response, some retrenchment is observed, particularly within the EU (Emter, Schmitz, and Tirpak, 2018). Generally, there has been some de-risking: banks hold more liquid assets and depend less on wholesale financing (BIS, 2018). In this chapter, we seek to provide a fundamental analysis of the underlying forces that could explain the evolution of the banking industry. We begin by discussing the key insights from the financial intermediation literature, including the potential complementarities and conflicts of interest between intermediated relationship banking activities and financial market activities (underwriting, securitization, etc.). While debt contracts dominate the financial intermediation literature, the impressive growth of private equity firms has turned the spotlight on equity. In a sense, one could interpret private equity (PE) as intermediation driven from the equity side. Given their economic functions as debt and equity intermediaries, respectively, how do banks and PE firms interact? Our discussion reveals that the interaction between banks and PE firms is only one aspect of an increasing integration of banks and markets. Banks have a growing dependence on the financial markets not only as a source of funding but also for hedging purposes and offloading risks via securitization, and possibly for engaging in proprietary trading. Financial market linkages often also imply that intra-financial sector linkages mushroom; for example, the asset-backed securities created by securitization can serve as the collateral that financial institutions use to fund themselves in the shadow-banking system. The multiple dimensions of bank dependence on markets generate both risk reduction and risk elevation possibilities for banks. For example, while hedging may reduce risk, proprietary trading, providing liquidity guarantees for securitized debt, and taking positions in credit default swaps can increase risk as well. This raises potential regulatory concerns. What do these developments imply for prudential regulation and supervision? Will the increasing interactions between banks and markets increase or decrease financial

2  In the definition of Adrian and Ashcraft (2016), shadow banking consists of financial institutions that are involved in credit, maturity, and liquidity transformation (which could create financial stability risks), but without the access to public backstops that banks have. Gorton and Metrick (2012) define the shadow-banking system as one consisting of the following key components: (i) money-market mutual funds or other institutional (market-based) lenders who replace depositors as a primary funding source for shadow banks; (ii) securitization of bank-originated loans, which permits the creation of asset-backed securities that then serve as collateral for the bank’s borrowing from mutual funds and other institutional lenders; and (iii) repurchase agreements (or Repos), which represent the financial contract used by banks to raise funding from investors.

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64   The Theory of Banking system fragility? The financial crisis of 2007–9 suggests an increase in fragility, but how much can we generalize from this crisis? These developments have also focused attention on the role of “gatekeepers” (Coffee, 2002), like credit rating agencies. While the financial intermediation literature has acknowledged the role of credit rating agencies as information processors and sellers for some time now (e.g., Ramakrishnan and Thakor, 1984; Allen, 1990), the literature has not discussed how rating agencies may affect the fragility of the financial sector through the important role they play as “spiders in the web of institutions and markets.” We take up this issue in our discussion. The organization of the chapter is as follows. In section 3.2, we focus on the economic role of financial intermediaries. The primary focus here is on the banks’ role in lending and how this compares to non-intermediated finance directly from the financial market. We will also analyze the effects of competition on the banks’ lending relationships. Does competition harm relationships and reduce their value and hence induce more transaction-oriented banking, or does competition augment the value of relationships? This discussion will summarize the key insights from the modern literature of financial intermediation. In section 3.3 we discuss the increasingly interconnected nature of banks and financial markets, with a focus on securitization. This “technology” has been at the center of the 2007–9 financial crisis. What are the future prospects for securitization? The proliferation of non-banking financial institutions, and particularly private equity firms, is discussed in section 3.4. We will argue that much of this activity might be complementary to the role of banks, rather than threatening their raison d’être. Subsequently, in section 3.5 we focus on the role of credit rating agencies. These agencies have been indispensable for the explosive growth (and temporary demise) of securitization. How will their role develop? We then discuss in section 3.6 regulatory implications. Here we link the role of banks in lending (as emphasized in our earlier discussions) to their role as providers of liquidity. This brings in the issue of fragility, which is at the heart of the current regulatory debate.

3.2  Understanding Banks as Information-Processing Intermediaries In this section we discuss two issues: (1) what is the key role of banks vis-à-vis markets? and (2) how does competition impinge on this role?

3.2.1  The Economic Role of Banks We first discuss the role of banks in qualitative asset transformation—that is, the process by which banks absorb risk to transform both the liquidity and credit risk characteristics

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Commercial Banking and Shadow Banking   65 of assets (see Bhattacharya and Thakor, 1993). For example, banks invest in risky loans but finance them with riskless deposits (e.g., Diamond, 1984; Ramakrishnan and Thakor, 1984; Millon and Thakor, 1985; Coval and Thakor, 2005). They also invest in illiquid loans and finance them with liquid demandable deposits (e.g., Diamond and Dybvig, 1983). The theory of financial intermediation has placed special emphasis on the role of banks in monitoring and screening borrowers in the process of lending. Bank lending is typically contrasted with direct funding from the financial markets. What are the comparative advantages of bank loans over public capital market-bond financing?3 The most striking insight of the contemporary theory of financial intermediation is that banks are better than markets at resolving informational problems. The possession of better information about their borrowers allows banks to get closer to, and possibly more aligned with, their borrowers. Interestingly, a feedback loop is generated, as this proximity between the financier and the borrowing firm in bank-lending arrangements may also help mitigate the information asymmetries that typically plague arm’s length arrangements in market transactions. This has several aspects. A borrower might be prepared to reveal proprietary information to its bank that it may have been reluctant to reveal to the financial markets (Bhattacharya and Chiesa, 1995). A bank might also gather information about prospective borrowers through their depository relationship with the bank,4 and may also have better incentives to invest in costly information acquisition. While costly, the substantial stake that it has in the funding of the borrower and the enduring nature of its relationship with the borrower—with the possibility of information reusability over time—increase the marginal benefit of information acquisition to the bank.5 Boot and Thakor (2000) analyze the economic surplus that relationship banking can generate. Such borrower–lender proximity may also have a dark side. An important one is the hold-up problem that stems from the information monopoly that the bank may develop 3  Much of the discussion that follows focuses on bank loans vs. bond financing in the capital market, rather than equity financing in the market. In reality, we would expect the market to segment itself into some firms going for bank loans, some going for bond market financing, and some going for equity market financing. Boot and Thakor (1997) develop a theory that predicts the choice between bank loans and bond market financing. Brown, Martinson, and Petersen (2017) provide evidence that better-developed stock markets support the faster growth of high-tech industries, whereas better-developed bank-oriented credit markets foster growth in industries that rely on external financing for physical capital. 4  Empirical evidence that depository information about potential borrowers is relevant to the bank is provided by Puri, Rocholl, and Steffen (2017). That paper uses data on a million German loans to show that when a bank extends loans to those who have had a depository relationship with the bank (and continue to have it) exhibit lower default probabilities than those without depository relationships with the bank, consistent with one of the predictions in Donaldson, Piacentino, and Thakor (2018). 5  Ramakrishnan and Thakor (1984) and Millon and Thakor (1985) focus on pre-contract information asymmetries to rationalize the value that financial intermediaries add relative to markets. Diamond (1984) focuses on post-contract information asymmetries to rationalize intermediation. Coval and Thakor (2005) show that financial intermediaries can provide an institutional resolution of the problem of cognitive biases at the individual investor level, acting as a “belief ’s bridge” between pessimistic investors and optimistic entrepreneurs. James (1987), Lummer and McConnell (1989), and Gande and Saunders (2005) provide empirical evidence on the informational value of bank financing. See also the “stories” provided by Berlin (1996) supporting the special role of banks.

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66   The Theory of Banking due to the spontaneous generation of proprietary information on borrowers. Such an informational monopoly may permit the bank to charge higher loan interest rates ex post (for theories, see Sharpe, 1990; Rajan, 1992; and see Boot, 2000, for a review). The threat of being “locked in,” or informationally captured by the bank, may dampen loan demand ex ante, causing a loss of potentially valuable investment opportunities. Alternatively, firms may opt for multiple-bank relationships (see Carletti, Cerasi, and Daltung, 2007). This may reduce the informational monopoly of any individual bank, but possibly at a cost. Ongena and Smith (2000) show that multiple-bank relationships indeed reduce the hold-up problem, but can worsen the availability of credit (see Thakor, 1996, for a theoretical rationale). Another aspect is that relationship banking could accommodate an intertemporal smoothing of contract terms (see Boot and Thakor, 1994; Allen and Gale, 1995, 1997) that would entail losses for the bank in the short term that are recouped later in the relationship.6 Petersen and Rajan (1995) show that credit subsidies to young or “de novo” companies may reduce the moral hazard problem and the informational frictions that banks face in lending to such borrowers. Banks may be willing to provide such subsidized funding if they can expect to offset the initial losses through the long-term rents generated by these borrowers. The point is that, without access to subsidized credit early in their lives, “de novo” borrowers would pose such serious adverse selection and moral hazard problems that no bank would lend to them. Relationship lending makes these loans feasible because the proprietary information generated during the relationship produces “competition-immune” rents for the bank later in the relationship and permits the early losses to be offset. The importance of intertemporal transfers in loan pricing is also present in Berlin and Mester (1999). They show that rate-insensitive core deposits allow for intertemporal smoothing in lending rates. This suggests a complementarity between deposit taking and lending. Moreover, the loan commitment literature has emphasized the importance of intertemporal tax subsidy schemes in pricing to resolve moral hazard (see Boot, Thakor, and Udell, 1991; Shockley and Thakor, 1997) and also the complementarity between deposit taking and commitment lending (see Kashyap, Rajan, and Stein, 2002). The bank–borrower relationship also displays greater contractual flexibility than that normally encountered in the financial market. This flexibility inheres in the generation of hard and soft proprietary information during a banking relationship. The information gives the bank the ability to adjust contractual terms to the arrival of new information and hence encourages it to write “discretionary contracts” ex ante that leave room for such ex post adjustments. This is in line with the important ongoing discussion in economic theory on rules versus discretion, where discretion allows for decision-making based on more subtle—potentially non-contractible—information (see, for example, Simons, 1936; Boot, Greenbaum, and Thakor, 1993). 6  One strong implication of the Boot and Thakor (1994) theory is that the gains from relationship lending will take some time to be manifested. Recent empirical evidence in support of this prediction is provided by Lopez-Espinosa, Mayordomo, and Moreno (2017) who document that the gains from relationship lending accrue only when the relationship is of a longer duration than two years.

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Commercial Banking and Shadow Banking   67 The papers by Stein (2002), and Berger et al. (2005) highlight the value of “soft information” in lending. Soft information could be an example of more subtle and non-contractible information. On this issue, two dimensions can be identified. One dimension is related to the nature of the bank–borrower relationship, which is typically long term, with accompanying reinforcing incentives for both the bank and the borrower to enhance the durability of the relationship. This allows for implicit—non-enforceable— long-term contracting. An optimal information flow is crucial for sustaining these “contracts.” Information asymmetries in the financial market, and the non-contractibility of various pieces of information, would rule out long-term alternative capital market funding sources as well as explicit long-term commitments by banks. Therefore, both the bank and the borrower may realize the added value of their relationship, and have an incentive to foster the relationship.7 The other dimension is related to the structure of the explicit contracts that banks can write. Because banks write more discretionary contracts, bank loans are generally easier to renegotiate than bond issues or other public capital market funding vehicles (see Berlin and Mester, 1992). Such renegotiability may be a mixed blessing because banks may suffer from a “soft-budget constraint” problem: borrowers may realize that they can renegotiate ex post, which could give them perverse ex ante incentives (see Dewatripont and Maskin, 1995; Bolton and Scharfstein, 1996). The soft-budget-constraint problem is related to the potential lack of toughness in enforcing contracts due to the ex post distribution of “bargaining power” linked with relationship banking proximity (see Boot,  2000). In practice, one way that banks can deal with this issue is through the priority structure of their loan contracts. If the bank has priority/seniority over other lenders, it could strengthen the bank’s bargaining position and allow it to become tougher. These issues are examined in Diamond (1993), Berglöf and von Thadden (1994), and Gorton and Kahn (1993). The bank could then credibly intervene in the decision process of the borrower when it believes that its long-term interests are in jeopardy. For example, the bank might believe that the firm’s strategy is flawed, or a restructuring is long overdue. Could the bank push for the restructuring? If the bank has no priority, the borrower may choose to ignore the bank’s wishes. The bank could threaten to call the loan, but such a threat may lack credibility because the benefits of liquidating the borrower’s assets are larger for higher-priority lenders, and the costs from the termination of the borrower’s business are higher for lower-priority lenders. When the bank loan has sufficiently high priority, the bank could credibly threaten to call back the loan, and this may offset the deleterious effect of the soft-budget constraint. This identifies a potential advantage of bank financing: timely intervention. Of course, one could ask whether bondholders could be given priority and allocated the task of timely intervention. Note that bondholders are subject to more severe information asymmetries 7  Mayer (1988) and Hellwig (1991) discuss the commitment nature of bank funding. Bolton et  al. (2016) discuss the implicit commitment in bank funding to local markets in times of crisis. Boot, Thakor, and Udell (1991) address the credibility of commitments.

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68   The Theory of Banking and are generally more dispersed (i.e., have smaller stakes). Both characteristics make them ill-suited for an “early intervention” task.

3.2.2  Intermediation and Competition Since relationship banking is an integral part of the economic services provided by banks and generates rents for banks, it also potentially invites multiple-bank entry, which then generates interbank competition. An interesting question this raises is how competition might affect the incentives for relationship banking. While this may ultimately be an empirical question, two diametrically opposite points of view have emerged theoretically. One is that competition among financiers encourages borrowers to switch to other banks or to the financial market. The consequent shortening of the expected “life span” of bank–borrower relationships may induce banks to reduce their relationship-specific investments, thereby inhibiting the reusability of information and diminishing the value of information (Chan, Greenbaum, and Thakor, 1986). Banks may then experience weaker incentives to acquire (costly) proprietary information, and relationships may suffer. There is empirical evidence that an increase in relationship length benefits the borrower. Brick and Palia (2007) document a 21-basis point reduction in the loan interest rate due to a one-standard deviation increase in relationship length. Moreover, increased credit market competition could also hurt relationship lending by imposing tighter constraints on the ability of borrowers and lenders intertemporally to share surpluses (see Petersen and Rajan, 1995). In particular, it becomes more difficult for banks to “subsidize” borrowers in earlier periods in return for a share of the rents in the future. Thus, the funding role for banks that Petersen and Rajan (1995) see in the case of young corporations (as already discussed) may no longer be sustainable in the face of sufficiently high competition. This implies that interbank competition may have an ex post effect of diminishing bank lending.8 Another way in which competition can hurt relationship lending is through consolidation. Extensive empirical literature focuses on the effect of consolidation in the banking sector on small-business lending. This consolidation may in part be a response to competitive pressures. The effects on small-business lending, however, are not clearcut. Sapienza (2002) finds that bank mergers involving at least one large bank result in a lower supply of loans to small borrowers by the merged entity. This could be linked to the difficulty that larger organizations have in using “soft information” (Stein, 2002; Berger et al., 2005). However, Berger et al. (1998) show that the actual supply of loans to small businesses may not go down after bank mergers, since they invite entry of “de novo” banks that specialize in small-business lending (see also Strahan, 2007).

8  Berlin and Mester (1999) provide a related, albeit different argument. Their analysis suggests that competition forces banks to pay market rates on deposits, which may impede their ability to engage in the potentially value-enhancing smoothing of lending rates.

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Commercial Banking and Shadow Banking   69 The opposite point of view is that competition may actually elevate the importance of a relationship-orientation as a distinct competitive edge. The idea is that competition pressures profit margins on existing products and increases the importance of financier differentiation, and more intense relationship lending may be one way for the bank to achieve this. Boot and Thakor (2000) formalize this argument to show that a more competitive environment may encourage banks to become more client-driven and customize services, thus generating a stronger focus on relationship banking.9 They distinguish between “passive” transaction lending and more intensive relationship lending by banks. Transaction lending competes head-on with funding in the financial market. Greater interbank competition results in banks engaging in more relationship lending, but each relationship loan has lower value to the borrower. By contrast, greater competition from the capital market leads to a lower volume of relationship lending, but each relationship loan has greater value. In this context, it is also interesting to note that Berger et al. (2008) find empirically that bank ownership type (foreign, state-owned, or private domestic) affects the bank’s choice between transaction and relationship lending. Relationships may foster the exchange of information, but may simultaneously give lenders an information monopoly and undermine competitive pricing. As discussed above, the informational monopoly on the “inside” lender’s side may be smaller if a borrower engages in multiple-banking relationships. This would mitigate the possibilities for rent extraction by informed lenders and induce more competitive pricing (see Sharpe, 1990; Petersen and Rajan, 1995). Transaction-oriented finance, however, may give banks little incentive to acquire information but is potentially subject to more competition. This suggests that markets for transaction-oriented finance may fail when problems of asymmetric information are insurmountable without explicit information acquisition and information-processing intervention by banks. This argument is used by some to highlight the virtues of (relationship-oriented) bank-dominated systems (e.g., Germany and Japan) vis-à-vis market-oriented systems. This is part of the literature on the design of financial systems (see Allen, 1993; Allen and Gale, 1995; Boot and Thakor, 1997). One objective of this literature is to evaluate the economic consequences of alternative types of financial system architecture. What this discussion indicates is that the impact of competition on relationship banking is complex; several effects need to be disentangled. However, empirical evidence (see Degryse and Ongena, 2007) seems to support the Boot and Thakor (2000) prediction that the orientation of relationship banking adapts to increasing interbank competition, so higher competition does not drive out relationship lending. Despite this adaptation, there is also evidence that in recent years the geographic distance between borrowers and lenders has increased (see DeYoung, Glennon, and Nigro, 2008). The latter 9  In related work, Hauswald and Marquez (2006) focus on a bank’s incentives to acquire borrowerspecific information in order to gain market share, and Dinç (2000) examines a bank’s reputational incentives to honor commitments to finance higher-quality firms. Song and Thakor (2007) theoretically analyze the effect of competition on the mix between relationship and transaction lending, and focus on fragility issues raised by the bank’s desire to match core deposit funding with relationship lending and purchased money funding with transaction lending.

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70   The Theory of Banking might point at an increasing availability of data and data-processing capacity, which might challenge relationship banking. New specialized lenders have arisen that seek to replace relationship lenders and traditional credit scoring with sophisticated algorithms based on Big Data mining (data analytics). While still in its infancy, such analysis predicts creditworthiness by analyzing buying habits, lifestyle choices, and all manner of opportunistic demographic correlates. One could envision similar developments enabling P2P lending as well.10

3.3  Bank Lending, Securitization, and Capital Market Funding Much of our focus in the previous section was on interbank competition. Nonetheless, banks also face competition from the capital market. The standard view is that banks and markets compete, so that growth in one is at the expense of the other (see Allen and Gale, 1995; Boot and Thakor, 1997). In this context, Deidda and Fattouh (2008) show theoretically that both bank and stock-market development have a positive effect on growth, but the growth impact of bank development is lower when there is a higher level of stock-market development. They also present supporting empirical evidence. What this shows is that the dynamics of the interaction between banks and markets can have real effects. How banks and markets interact is therefore of great interest. In contrast to the standard view that they compete, the observations in the previous section suggest that there are also potential complementarities between bank lending and capital market funding. We argued that prioritized bank debt may facilitate timely intervention. This feature of bank lending is valuable to the firm’s bondholders as well. They might find it optimal to have bank debt take priority over their own claims, because this efficiently delegates the timely intervention task to the bank. The bondholders will obviously ask to be compensated for their subordinated status. This—ignoring the timely intervention effect—is a “wash.” In other words, the priority (seniority) and subordination features can be priced. That is, as much as senior debt may appear to be “cheaper” (it is less risky), junior or subordinated debt will appear to be more expensive, and there should be no preference for bank seniority, other than through the timely bank-intervention channel. Consequently, the borrower may reduce its total funding cost by accessing both the bank-credit market and the financial market.11 A theoretical 10  See chapter 18 in Greenbaum, Thakor, and Boot (2016). 11  The complementarity between bank lending and capital market funding is further highlighted in Diamond (1991) and Hoshi, Kashyap, and Scharfstein (1993). Diamond (1991) shows that a borrower may want to borrow first from banks in order to establish sufficient credibility before accessing the capital markets. Hoshi, Kashyap, and Scharfstein (1993) show that bank lending exposes borrowers to monitoring, which may serve as a certification device that facilitates simultaneous capital market funding. In related theoretical work, Chemmanur and Fulghieri (1994) show that the quality of the bank is of critical

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Commercial Banking and Shadow Banking   71 analysis of complementarity appears in Song and Thakor (2010) who show that banks and markets exhibit three forms of interaction: competition, complementarity, and co-evolution. Another manifestation of potential complementarities between bank lending and capital market activities is the increasing importance of securitization, this being an example of the unbundling of financial services. Securitization is a process whereby assets are removed from a bank’s balance sheet, so banks no longer permanently fund assets when they are securitized; instead, the investors buying asset-backed securities provide the funding. Asset-backed securities rather than deposits thus end up funding dedicated pools of bank-originated assets. More specifically, the lending function can be decomposed into four more primal activities: origination, funding, servicing, and risk processing (Bhattacharya and Thakor, 1993). Origination subsumes screening prospective borrowers, and designing and pricing financial contracts. Funding relates to the provision of financial resources. Servicing involves the collection and remission of payments as well as the monitoring of credits. Risk processing alludes to hedging, diversification, and absorption of credit, interest rate, liquidity, and exchange-rate risks. Securitization decomposes the lending function such that banks no longer fully fund the assets, but continue to be involved in other primal lending activities. One potential benefit of securitization is better risk sharing (see Gorton and Pennacchi, 1995 for an economic rationale for bank loan sales and securitization). The proliferation of securitization may, however, also be induced by regulatory arbitrage—for example, as a vehicle to mitigate capital regulation. And a third benefit is highlighted by Boot and Thakor (1993), who show that the pooling of assets and tranching of claims in securitization achieve both a diversification of idiosyncratic information and the creation of information-sensitive claims that increase the issuer’s revenues from selling these securities. Central to the extensive academic work on securitization is the idea that it is not efficient for originators to completely offload the risks in the originated assets. The originating bank needs to maintain an economic interest in the assets in order to alleviate moral hazard and induce sufficient effort on the originating bank’s part in screening and monitoring. What this implies is that, even with securitization, banks do not become disengaged from the assets they originate. Banks still continue to provide the services involved in screening and monitoring borrowers, designing and pricing financial claims, and providing risk-management and loan-servicing support. As such, securitization preserves those functions that are at the core of the raison d’être for banks. This militates against the notion that securitization effectively lessens the importance of banks. Boyd and Gertler (1994) have argued that the substitution from on-balance-sheet to off-balance-sheet banking induced by securitization may have falsely suggested a shrinking role for banks. Indeed, by keeping banks involved in their primal activity of

importance for its certification role. This suggests a positive correlation between the value of relationship banking and the quality of the lender. See Petersen and Rajan (1994) and Houston and James (1996) for empirical evidence.

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72   The Theory of Banking pre-lending borrower screening, securitization preserves much of the banks’ value added on the asset side. Up to the 2007–9 financial crisis, securitization was rapidly gaining in importance. In fact, prior to the summer of 2007, securitization became prevalent for ever-wider types of credits, including business credits that were previously thought to be difficult to securitize because of their information opaqueness. Also, a rather new market for securitization involving asset-backed commercial paper (ABCP) conduits emerged as a significant force. As the subprime crisis of 2007 has shown, these developments are not without problems. The structure of real-world securitization transactions appears to have taken a rather fragile form. In particular, it is important to note that much of the securitization leading up to the crisis involved the financing of long-term assets with short-term funding, which induced substantial liquidity risk. While this liquidity risk was sometimes mitigated by liquidity guarantees (e.g., stand-by letters of credit and refinancing commitments), the underwriting institutions often underestimated the risks involved and overstretched themselves.12 Recent events may cast doubt on the optimality of such strategies. Also, because the originating institutions appeared to have retained minimal residual risk, monitoring incentives may have been compromised (see Mian and Sufi,  2009).13 The eagerness of banks to securitize claims—and keep the repackaging “machine” rolling—may have also adversely impacted the quality of loans that were originated through a dilution of banks’ screening incentives due to lower retained residual risks (e.g., subprime lending; see Keys et al., 2010). The 2007–9 financial crisis brought securitization almost to a grinding halt. However, the risk diversification that securitization can accomplish appears to be of more than just ephemeral importance. Thus, we expect securitization to re-emerge, albeit possibly in a form that entails lower levels of liquidity risk, as well as lesser moral hazard in screening (loan underwriting standards) and monitoring. A caveat is that some of the activity in securitization might have been induced merely by capital arbitrage. With the stronger regulatory scrutiny following the financial crisis, we would expect such securitization to be discouraged. Another effect of the interaction between banks and markets is that as markets evolve and entice bank borrowers away, banks have an incentive to create new products and services that combine services provided by markets with those provided by banks. This allows banks to follow their customers to the market rather than losing them. There 12  Most noteworthy are the bankruptcies among German Lander banks, which were involved in providing liquidity guarantees. 13  Securitization is facilitated in part by credit enhancement, including partial guarantees by the arranger of a securitization transaction (and/or he holds onto the most risky layer of the transaction). In the recent credit crisis, this disciplining mechanism broke down; residual risk with the arranger was minimal or framed as liquidity guarantees to off-balance-sheet vehicles without appropriately realizing the inherent risks. The marketability of securitized claims has also been facilitated by accreditation by credit rating agencies. However, the role of rating agencies has been called into question during the subprime lending crisis, see section 3.5.

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Commercial Banking and Shadow Banking   73 are numerous examples. For instance, when a borrower goes to the market to issue commercial paper, its bank can provide a backup line of credit. In similar spirit, Drucker (2005) shows that junk-rated firms and companies in local lending relationships are more likely to select an integrated (universal) commercial investment bank when they expect to issue public debt in the future. This revealed preference for commercial investment bank relationships by firms that issue informationally sensitive securities suggests that there might be benefits for banks to use private information from lending in investment banking. A similar picture emerges if one looks at US banking following the 1999 Financial Services Modernization Act. It appears that information collected through the banks’ commercial lending businesses may have reduced the costs of underwriting debt and equity (see Schenone, 2004; Drucker and Puri, 2005). While this suggests a potential for value creation, an extensive amount of literature has focused on the potential conflicts of interest related to banks combining lending and capital market activities; particularly, conflicts of interest in universal banking. Much of earlier work is motivated by the Glass–Steagall regulation in the US (see Kroszner and Rajan, 1994; Puri, 1996; Ramírez, 2002). Typical findings are reassuring, that is, conflicts were found to be limited. In more recent work, a somewhat more critical picture has emerged; the problems with securitization, as already discussed, are a good example. Moreover, as Boot and Ratnovski (2016) show, combining relationship banking with financial market-oriented transaction activities (like trading) might undermine the commitment needed for relationship banking. More specifically, the ability to shift resources to trading activities within financial institutions may undermine relationship banking activities by violating (implicit) funding commitments to those borrowers. This might be particularly acute because trading activities are typically more readily scalable than relationship banking activities; that is, the latter depend on more long-term engagements leading to more cultivated relationships. This suggests that combining banking and trading activities could lead to a lack of commitment and the loss of franchise value. Consistent with this, Laeven and Levine (2007) find that banks that combine lending and non-lending activities lose value relative to engaging in these activities separately (see also Schmid and Walter, 2009). The impetus for market-based activities grows stronger as interbank competition puts pressure on profit margins from traditional banking products, and the capital market provides access to greater liquidity and lower cost of capital for the bank’s traditional borrowers. As a consequence, there is a natural propensity for banks to become increasingly integrated with markets, and a sort of unprecedented “co-dependence” emerges that increasingly intertwines banking and capital market risks.14 A discussion of whether this is desirable and what the regulatory implications might be is given in section 3.6. 14  Innovations integrating banks and markets went far beyond securitization. For example, OTC derivatives, especially credit default swaps, showed enormous growth in the period preceding the 2007–9 crisis, outpacing real investment by a factor of twelve (Posen and Hinterschweiger, 2009). For further insights, see also Shleifer and Vishny (2010).

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74   The Theory of Banking

3.4  Banks, Equity, and Private Equity Firms The emergence of non-banking financial institutions such as PE firms is considered by some to be a (further) signal for the diminishing role of banks. However, we will argue that these developments are rather complementary to the role of banks. Let us first discuss the role that PE firms play. The arguments above about the need for banks to have seniority suggest a natural economic inhibiting of investments by banks in the equity of corporations. Equity “softens” a bank’s incentive to intervene for much the same reasons as does junior debt. So, while the emphasis of corporate finance theory on agency problems would suggest that it might be efficient for the bank to have both debt and equity claims on a corporation, this seems not to be advisable from a timely intervention point of view. This might explain why equity intermediation has largely been in the hands of PE firms and/or bulge-bracket global investment banks that typically engage less in relationship banking and focus more on transactions and the associated capital market activities. Some more observations can be made about PE firms. Their activities could be viewed as intermediation driven from the equity side. That is, PE firms attract funding from a group of investors (“partners”) and invest the funds as equity in businesses. They are extensively involved in monitoring and advising these businesses. How different is this from the role that banks play as debt intermediaries? To address this question, note first that banks do occasionally take equity positions in their role as venture capitalists, particularly for later-stage financing where there is a prospect for developing a valuable relationship on the lending side. Thus, banks participate in venture capital financing with higher probability if there is a greater likelihood of subsequent lucrative lending activity (Hellmann, Lindsey, and Puri, 2008). However, this may create a weakness in the participation decision. Bank-affiliated private equity investments, on average, do worse than non-affiliated investments (see Fang, Ivashina, and Lerner, 2010). Banks may also have (participations in) PE subsidiaries that operate independently from the other businesses of the bank. However, this somewhat limited role as an equity financier does not mean that it would be efficient for the bank permanently to become an integrated provider of debt and equity finance, a “one-stop” financier of sorts. In particular, equity as a junior security may undermine a bank’s bargaining power and thus compromise its role in timely intervention. Also, soft-budget constraint problems may then (re)emerge. At a more general level, one could ask whether the monitoring role of PE firms substitutes for the lending-related monitoring of banks. It might. Note, however, that equity and debt are fundamentally different securities. The type of monitoring needed will differ significantly. What will be true, however, is that the increasing involvement of PE investors induces banks to partner with these investors (often as providers of loans). In a sense, banks start building relationships with PE firms rather than the firms that the PE investors take equity positions in. This is not without risks since it may affect the

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Commercial Banking and Shadow Banking   75 added value of banks in timely intervention vis-à-vis the (underlying) borrower and even the banks’ incentives to be involved in this. However, to the extent that PE firms are an integral part of the capital market, this development too makes the involvement of banks in the capital market deeper and more intricate. Such complexity is further exacerbated by the emergence of other intermediaries such as hedge funds, particularly because of the growing importance of hedge funds as direct lenders. See Brophy, Ouimet, and Sialm (2009), who point out that hedge funds have emerged as “lenders of last resort,” providing finance to firms that banks do not typically lend to. This is part of the growing importance of the shadow-banking sector as a source of financing.

3.5  Role of Credit Rating Agencies Credit ratings are a fascinating part of today’s financial markets. Their importance is evident from the behavior of market participants. However, academic researchers have generally been skeptical about their incremental value, largely because of the absence of a theory of rating agencies. In the literature on financial intermediary existence, bank debt offers monitoring advantages that would not be available in the financial market. The typical argument for the lack of monitoring in the capital market is that free-rider problems among investors prevent effective monitoring. Boot, Milbourn, and Schmeits (2006) have shown that credit rating agencies (CRAs) add a monitoring-type element to the financial market, and thereby play a role as a “focal point” to resolve coordination failures among multiple dispersed investors (creditors). The CRA’s ability to resolve such coordination failure arises from the effect of its actions—the assigned rating and the “credit watch” process—on firm behavior via the conditioning of investors’ investment decisions on the assigned rating. Da Rin and Hellmann (2002) showed that banks could also resolve a multiple-equilibria problem among borrowers by helping coordinate the investment decisions of these borrowers. The role that Boot, Milbourn, and Schmeits (2006) give to CRAs has some similarity to this. This role of CRAs in resolving coordination failures in the financial market qualifies the distinction between public debt and bank financing. The mechanism is, however, less “direct” than in the case of bank financing: the credit rating (and particularly the threat of a downgrade) induces good firm behavior rather than preventing bad behavior through direct intervention. Apart from bank loans, the non-bank private debt market also offers a potentially more direct alternative than credit rating agencies in the public debt market. In fact, private debtors often impose more discipline than banks and hence serve even riskier borrowers (Carey, Post, and Sharpe, 1998). Another mechanism that links banks and CRAs is the certification role of bank loans. Datta, Iskandar-Datta, and Patel (1999) show that the monitoring associated with bank loans facilitates borrowers’ access to the public debt market. This certification role of banks therefore complements what CRAs do. As rating agencies become more sophisticated and reliable, the certification role of banks diminishes in importance, causing bank borrowers to migrate to the capital market. In this sense, CRAs intensify the competition

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76   The Theory of Banking between banks and markets. But CRAs also pull banks into the capital market. For example, banks originate loans that they securitize, and then seek ratings for the securitized pools from CRAs. The ratings, in turn, facilitate the ability of banks to sell (securitized) asset-backed securities in the capital market. One reason why credit ratings do not precisely reflect the credit risk of the rated debt instrument is that ratings are “coarse” relative to underlying default probabilities—there are only a little more than twenty ratings, but default probabilities lie in a continuum. This raises the question of why such coarseness exists. Goel and Thakor (2015) provide a theory in which they rationalize coarse credit ratings in a cheap-talk framework and show that coarseness addresses a truthful reporting (by the CRA) issue when the CRA has multiple objectives (issuers vs. investors) pulling against each other. Thus, coarse ratings emerge in equilibrium even though coarseness has negative real effects.15 This largely positive interpretation of CRAs is clouded somewhat by recent negative publicity. In the 2001 crisis surrounding Enron, CRAs were accused of being strategically sluggish in downgrading.16 More recently, CRAs have been blamed (in part) for the subprime crisis in which they were allegedly too lenient in rating the senior tranches in securitization transactions. Allegations have been made about conflicts of interest for CRAs, arising from the fact that structured finance is a source of ever-increasing income for CRAs, which then corrupts their incentives for accurately rating the issuers involved in structured finance (Cantor, 2004). In this context, Coffee and Sale (2008) point out that it is naïve to think that reputation-building incentives alone would keep credit rating agencies in check. Of particular concern are the so-called “rating triggers.” For example, some debt contracts may dictate accelerated debt repayments when the rating falls. The consequences of such accelerated debt repayments might, however, be so severe as to cause rating agencies to become reluctant to lower the ratings of those borrowers in a timely manner. Complications also arise from the role played by the so-called “monoliners.” These are insurers who traditionally guaranteed municipal bonds but now also guarantee the lowest-risk (best) tranches in securitization transactions. These insurers are virtually indispensable in the sense that the viability of many forms of securitization is predicated on this type of “reinsurance.” However, the ability of the monoliners to issue credible guarantees (and hence their role in securitization) depends on these institutions themselves having AAA ratings. This potentially generates an indirect chain-reaction mechanism for CRAs. In rating (and monitoring) the monoliners, CRAs affect the viability of the securitization market. Thus, the impact of CRAs is both direct (rating securitization tranches) and indirect (rating the monoliners). The potential failure of such monoliners 15  See also Lizzeri (1999), in whose model, some pooling of credit types is induced by the profit maximization objective of the CRA. See Sangiorgi and Spatt (2017b) for an overview of the literature on credit ratings. 16  As an illustration, consider the following discussions in the US Senate: “On March 20, 2002, the Senate Committee held a hearing entitled ‘Rating the Raters: Enron and the Credit Rating Agencies’ . . . The hearing sought to elicit information on why the credit rating agencies continued to rate Enron a good credit risk until four days before the firm declared bankruptcy…” (US Senate Hearings, 2002). Similarly, US Senate Staff Report (2002): “in the case of Enron, credit rating agencies displayed a lack of diligence in their coverage and assessment of Enron.” See also Cantor (2004) and Partnoy (1999).

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Commercial Banking and Shadow Banking   77 would have a significant effect on the value of various structured finance products and induce an additional chain reaction among players active in the structured finance market, including investors. This further underscores the increasing interlinkages in the financial markets. Other concerns are related to the oligopolistic nature of the industry, and the importance that ratings have due to regulation. The latter includes the exclusivity given to a few rating agencies via the “Nationally Recognized Statistical Rating Organization” (NRSRO) classification, weakened in the 2006 Credit Rating Agency Reform Act, but also the references to external ratings in the Basel II capital regulation framework. Under the Dodd–Frank Act 2010, the legal liability for CRAs has been elevated. Whether this will result in credit ratings that more accurately reflect credit risks is an open question.17

3.6  Regulation and the Second Raison D’être for Banks: Liquidity Creation In section 3.2, we discussed the role of banks as information processors and delegated monitors. That information processing and monitoring referred to credit risk primarily. But banks also perform another important function, which is the provision of liquidity. The typical way this is framed is that banks invest in illiquid assets (loans) but finance themselves largely with highly liquid demand deposits, and through this intermediation process create liquidity in the economy. Liquidity is then created because depositors who invest in illiquid projects through the bank have liquid claims (demand deposits) that they would not have had if they had invested directly in those projects. The actual operations of banks, however, would have them make loans while simultaneously creating a matching deposit in the borrower’s bank account, thereby creating new money (see Bank of England, 2014). This alternative framing, would still lead banks to provide liquidity to the economy.18 In the process of creating liquidity, banks expose themselves to the risk of unanticipated deposit withdrawals and become fragile. Our discussion of this issue in this section will focus on “institution-driven fragility,” manifested in the classic run on an individual bank, as well as “market-driven fragility,” which refers to risks that come primarily via the financial market and interbank linkages, and appear to be more systemic. We will discuss how the increasing integration of banks into financial markets allows banks to 17  The Dodd–Frank Act also repealed the exemption given to CRAs in Regulation FD that allowed firms to have undisclosed material discussions with rating agencies. The institutional feature of rating shopping (i.e., firms may choose to hide ratings) is another element in the effectiveness of CRAs. See Sangiorgi and Spatt (2017a, 2017b). 18  In this spirit, Donaldson, Piacentino, and Thakor (2018) have banks create private money by making loans that go beyond their stock of physical deposits, thereby creating “funding liquidity” and allowing the economy to invest more in real projects than its initial endowment.

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78   The Theory of Banking shift some of their traditional risks to the markets, and what this implies for financial system stability and regulation. Issues related to the economics of bank regulation are covered in Bhattacharya, Boot, and Thakor (1998, 2004).

3.6.1  Fragile Banks as Liquidity Providers In the classical interpretation, a financial crisis is directly linked to the notion of bank runs. In a fractional reserve system with long-term illiquid loans financed by (liquid) demandable deposits, runs may come about due to a coordination failure among depositors (Diamond and Dybvig, 1983). Even an adequately capitalized bank could be subject to a run if the deadweight liquidation costs of assets are substantial. Regulatory intervention via lender of last resort (LOLR) support, deposit insurance, and/or suspension of convertibility could all help, and perhaps even eliminate the inefficiency. In fact, such intervention can be justified because of its potential to expunge the negative social externalities arising from the possible contagion effects associated with an individual bank failure. While these implications arise theoretically in a rather simple and stylized setting, many have generalized this simple setting by allowing for asymmetric information and incomplete contracts; see Rochet (2004) for a review. The general conclusion is that fragility is real, and information-based runs are plausible. In particular, Gorton’s (1988) empirical evidence suggests that bank runs are not sunspot phenomena (as in Diamond and Dybvig, 1983), but are triggered by adverse information about economic fundamentals. More importantly, the banking crises stemming from such runs have independent negative real effects (see DellʼAriccia, Detragiache, and Rajan, 2008). Also relevant in this context is the rich body of literature that has now developed on banks and liquidity (see, e.g., Acharya and Schaefer, 2006; Acharya, Gromb, and Yorulmazer,  2007; Brunnemeier and Pedersen, 2009). Given that bank runs are triggered by adverse information that depositors have about the financial health of banks, one might think that a simple solution would be to make banks safer by, for example, imposing higher capital requirements. Calomiris and Kahn (1991) first argued that the threat of bank runs may be a valuable disciplining device to keep bank managers honest, since a greater diversion of bank resources for personal consumption can increase the likelihood of a bank run. Building on this argument, Diamond and Rajan (2001) have suggested that financial fragility created by high bank leverage may play an important role in inducing banks to create liquidity, and thus a reduction in fragility through higher bank capital may lead to lower liquidity creation. Acharya and Thakor (2016) show that this link between bank leverage and liquidity creation has a dark side in that it causes higher bank leverage to generate higher systemic risk via spillover effects, namely inefficient “contagious liquidations” of healthy banks due to the observed liquidations of highly-levered failing banks. Until recently, there has been no empirical work done on this issue, in part because of a paucity of empirical measures of liquidity creation. Berger and Bouwman (2009) develop measures of liquidity creation and provide empirical evidence on the relationship between bank capital

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Commercial Banking and Shadow Banking   79 and liquidity creation. They show that higher capital leads to higher liquidity creation in the case of large banks (which create over 80 percent of the liquidity in the US economy), and lower liquidity creation in the case of small banks. Since capital requirements also affect the asset portfolios of banks through their lending decisions (see Thakor, 1996) and these requirements may be binding for some banks, this raises issues about the interaction of credit and liquidity risks that need to be explored. Mehran and Thakor (2011) show both theoretically and empirically that bank capital and value are positively related in the cross-section, pointing to the private benefits of higher capital for banks. Admati et al. (2011) similarly argue that the commonly asserted punitive costs of bank equity do not exist in reality, and stress the virtues of having higher capital. Complicating this issue further is that the liquidity provision function of banks is also affected by the financial markets. Two observations are germane in this regard. First, access to financial markets weakens the liquidity insurance feature of demand-deposit contracts. To see this, note that the root cause of the fragility in the Diamond and Dybvig (1983) world is the underlying demand-deposit contract. The rationale for this contract— as modeled by Diamond and Dybvig (1983)—is the desire for liquidity insurance on the part of risk-averse depositors with uncertainty about future liquidity needs. However, as shown by von Thadden (1998), the very presence of financial markets allows depositors to withdraw early and invest in the financial market, which puts a limit on the degree of liquidity insurance. In fact, when the market investment opportunity is completely reversible, deposit contracts cannot provide any liquidity insurance. This is related to the earlier work of Jacklin (1987), who shows that deposit contracts have beneficial liquidity insurance features, provided that restricted trading of deposit contracts can be enforced.19 In any case, these arguments suggest that the proliferation of financial markets weakens the liquidity-provision rationale for demand deposits, which may help explain the market-based proliferation of close substitutes for deposits. A second observation has to do with whether the development of financial markets leads to a diminished role for the Central Bank in providing liquidity via its LOLR function. In the Bagehot tradition, one could ask whether the LOLR has a role to play in providing liquidity to liquidity-constrained-yet-solvent institutions when capital markets and interbank markets are well developed. Goodfriend and King (1988) argue that solvent institutions then cannot be illiquid since informed parties in the repo and interbank market would step in to provide the needed liquidity. In this spirit, former European Central Bank (ECB) board member Tommaso Padoa-Schioppa suggested that the classical bank run may only happen in textbooks since the “width and depth of today’s interbank market is such that other institutions would probably replace those which withdraw their funds” (as quoted in Rochet and Vives, 2004). While these remarks correctly suggest that the development and deepening of financial markets could reduce the need for an LOLR in providing liquidity support, we 19  Actually, Jacklin (1987) shows that with the “extreme” Diamond-Dybvig preferences, a dividendpaying equity contract can achieve the same allocations without the possibility of bank runs. However, for other preferences, a demand-deposit contract does better, provided that trading opportunities are limited.

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80   The Theory of Banking believe that it would be hasty to conclude that there is no role for an LOLR, particularly when information asymmetries are considered. For example, Rochet and Vives (2004) show that a coordination failure in the interbank market may occur, particularly when fundamentals are weak, and that this may lead to a need for liquidity support by the LOLR for a solvent institution.20 The 2007–9 financial crisis gives ample reason to believe that coordination failures in interbank markets are real and that the role of an LOLR is still important. This discussion suggests two, somewhat tentative, conclusions. First, the development of financial markets (including interbank markets) has improved the risk-sharing opportunities available to banks and has probably decreased the likelihood of a run on an individual bank. Whether the total insolvency risk of individual institutions has declined depends on the actual risk-taking and capitalization. Second, because these improved risk-sharing opportunities have arisen from a greater degree of integration between banks and markets, they may also have contributed to an increase in systemic risk. In particular, financial market linkages (and focus) may have induced herding behavior (Boot, 2014). Adrian and Shin (2010) point at the effect of favorable financial market conditions on leverage (increasing) and funding (becoming more fragile and short term). These effects cause stress in the financial system at large when market conditions deteriorate. In other words, while the likelihood of an individual bank failing due to an idiosyncratic shock may have declined, there may be a concomitant increase in the probability that liquidity and solvency problems may propagate quickly through the financial system as a whole, leading to higher systemic risk. This raises thorny regulatory issues, which we turn to next.

3.6.2  Regulatory Implications The preceding discussion has focused the spotlight on one fact: banks and markets are becoming increasingly integrated. This is happening in part because greater competition is inducing banks to follow their borrowers to the capital market and offer products that combine features of bank-based and market-based financing. It is also happening because banks themselves are using the financial market increasingly for their own risk management purposes. And the availability of market participants as purchasers of new bank products encourages financial innovations by banks. But, as Thakor (2012) shows, this can also increase the likelihood of financial crises. There is thus a multitude of factors that have contributed to an astonishingly rapid melding process.21 20  Recent evidence provided by Berger et al. (2017) shows that when the Federal Reserve increased banks’ access to the discount window through its Term Auction Facility, lending by (treated) banks went up. Another line of research studies the impact of liquidity on asset pricing (e.g., Acharya and Pedersen, 2005) and the possible role of asset price bubbles as a source of fragility and contagion (see De Bandt and Hartmann, 2002; and Allen, 2005, for surveys on contagion). 21  Interestingly, the fact that this integration can increase the risk to which the bank’s depositors are exposed can induce banks to slow down the integration to enhance the value of the bank’s services to its depository customers, as shown by Merton and Thakor (forthcoming). The key is that many bank services

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Commercial Banking and Shadow Banking   81 An important implication of this integration is that it is becoming more and more difficult to isolate banking risks from financial market risks. A financial market crisis inevitably cascades through the banking system, and what happens in the banking system does not take long to reverberate through the financial market. So, if the main task of bank regulators is the safety and soundness of the banking system, they must now also worry about the financial market whose participants are outside the bank regulator’s domain. Explicit recognition that these sorts of effects have created the specter of “endogenous systemic risk” has led to the creation of the Financial Stability Oversight Council (FSOC) in the US and the European Systemic Risk Board (ESRB) in the EU as parts of the post-subprime-crisis regulatory landscape. Moreover, even though the explicit insurance guarantee applies only to bank deposits, the temptation for government regulators to bail out various uninsured participants— including investment banks and financial market investors—in the event of a crisis in the capital market seems difficult to resist on ex post efficiency grounds, particularly because of the implications for bank safety and systemic stability.22 It will be interesting to examine the connotations of this for ex ante incentives and the magnitude of the implicit “soft” safety net provided by the government. What seems safe to conjecture is that a perception of a greater regulatory concern with ex post efficiency—and hence a greater desire to intervene—has elevated the importance of moral hazard. And this has happened in an environment in which regulatory issues are becoming increasingly international, both due to the cross-border proliferation of financial institutions and the increasing integration of banks with financial markets, which are typically international in scope.23 The decentralized, mainly national structure of regulatory and supervisory arrangements in a financial world that operates across borders may give rise to potential conflicts of interest between the national authorities and “outsiders.” For example, national authorities might be prone to “too-big-to-fail” (TBTF) rescues, and this worsens benefit from being remote from the credit risk originating from the bank itself. This point also relates to the value of creating risk-free claims in the economy (see also Dang, Gorton, and Holmström, 2015). 22  The guarantee provided in 2008 to a collapsing Bear Stearns by the government to facilitate its sale to JPMorgan Chase is an example, as are the general measures to let investment banks qualify for a commercial banking license (and in doing so allow them access to deposits and let them qualify for deposit insurance). Bailouts were common in the financial crisis, also in Europe. Following the crisis, attempts have been made to make, so-called, bail-ins possible; meaning that upon the rescue of a financial institution unsecured financiers would lose their money. 23  The importance of international coordination was already on the radar screen far before the financial crisis. The Basel (BIS) capital accords (with agreements on minimum capital requirements) could be seen as a first success story of international coordination. Typically, progress was a response to crises; for example, the first step came with the creation of the Basel Committee in 1974 following the Herstatt failure (a relatively small bank that via its international linkages nevertheless had a big effect on international financial markets). Its first major (advisory) document followed in 1975 on host and home country supervisory responsibilities (the Basel Concordat). Several revisions followed, including the 1992 revision that followed the 1991 failure of the Luxembourg-based Bank Credit and Commerce International (BCCI) that pointed at an ill-defined home country definition. In 1988, the first Basel capital accord came about (Basel I). For more, see Alessi (2012).

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82   The Theory of Banking the moral hazard on the part of large institutions. Yet one could argue that the moral hazard engendered by TBTF policies could be attenuated somewhat by attaching to TBTF rescues specific provisions that would involve replacing management, wiping out the claims of shareholders and uninsured debtholders, etc. This is true in theory but does not appear to happen often in practice. One reason might be the possibility of capture of local regulators and supervisors due to the closeness of their relationships to the “national flagship” institutions (Boot and Thakor, 1993). There are also issues of “too many to fail” (see Acharya and Yorulmazer,  2007) or “too interconnected to fail” (Herring, 2008), which could also induce regulatory leniency toward these institutions. Alternatively, national authorities may not sufficiently internalize the disruptive consequences that a domestic bank failure could have in other countries. Efficiency might be hampered in other ways as well. For example, the national scope of supervision may help encourage the emergence of “national champions” among regulators, who may then seek to protect institutions in their countries. More fundamentally, the decentralized structure could give rise to an uneven playing field, regulatory arbitrage possibilities, and coordination failures in the resolution of financial distress in cross-border operating institutions. Casual observation would seem to suggest that integration and further coordination (if not centralization of authority) of both regulation and supervision might yield substantial efficiency gains not only for the supervisory authorities but also, and perhaps more importantly, for the supervised financial institutions themselves.24

3.6.3  Reform Suggestions The struggle for better cross-border coordination in regulation and supervision should go hand in hand with more fundamental reforms in the regulatory structure. The first is that the scope of regulation and supervision needs to be clearly identified and, if possible, contained. Effective supervision and regulation—given the mushrooming cross-sector and cross-border footprint of financial institutions—requires a better delineation of safety and systemic risk concerns. The cross-sector integration of financial institutions and the increasingly more seamless integration of financial markets and institutions have considerably broadened the scope of regulation and the potential sources of systemic risk. Another relevant question is whether market discipline could help in containing systemic risks, or whether market responses merely amplify such risks (see Flannery,  1998). Here the picture gets a bit murky. Basel II tries to encourage market discipline via its third pillar that is aimed at greater transparency. The idea is that market discipline could help supervisors in safeguarding the well-being of the financial sector. This has 24  A noteworthy example of cross-border coordination and centralization in supervision is the regulatory overhaul in the EU following the financial (and Euro) crisis. It has led to a common regulatory and supervisory framework, the so-called Banking Union. See chapters 15 and 16 in Greenbaum, Thakor, and Boot (2016).

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Commercial Banking and Shadow Banking   83 merit on the face of it and has support in the literature as well. The literature has viewed market discipline working in three ways: (1) by providing regulators with market-based signals of bank risk-taking through the yields on subordinated debt issued by banks; (2) by providing banks with disincentives to take excessive risk through the upward adjustments in sub-debt yields in response to greater bank risk; and (3) by choking off the supply of sub-debt when sufficiently high risk-taking by the bank is detected by the market, thereby providing additional encouragement to the bank to temper its risk-taking. Nonetheless, it has been shown both theoretically and empirically that market discipline can be effective only if the claims of uninsured investors (sub-debt and equity) are not protected via de facto ex post insurance in a government-sponsored rescue of a failing institution. For a theoretical treatment of these issues, see Decamps, Rochet, and Roger (2004), and for empirical analyses that support the risk-controlling role of market discipline, see Barth, Caprio, and Levine (2004), and Goyal (2005). However, despite all of the research support for the role of market discipline, our knowledge of whether market discipline facilitates or hinders the regulatory task of maintaining banking stability during a financial crisis is quite limited. In particular, when the financial sector is severely stressed, as during the 2007–9 credit crisis, market discipline may induce herding behavior, as everybody “heads simultaneously for the exit,” and this actually could be a source of instability. This suggests that regulation and supervision in “normal times” should perhaps be distinguished from that during crisis episodes. Market discipline, although valuable in normal times, may be very distortive in times of systemic stress. This may be one reason why, during crises, regulators have been inclined to provide more or less blanket guarantees to distressed institutions, ostensibly to counter the potentially adverse effects of market discipline. To complicate matters even further, it would be dangerous to conclude that market discipline, say via the use of market value accounting and other mechanisms, is something that can be relied upon in good times and eschewed in bad times. The key is to figure out the appropriate regulatory actions in good times—when banks have the flexibility to comply without compromising their viability—that would enable banks to be more capable of withstanding the stresses of market discipline during bad times. In such good times, risk management by banks tends to be corrupted at the same time that market discipline is the weakest and risk is “underpriced” (see, e.g., Thakor, 2015, 2016; Boot, 2014). Market discipline may thus not work in good times, or even be counterproductive due to the “underpriced” risk inviting excessive leverage and risk-taking. It will also be important to remember that banks cannot be completely insured from the effects of market stress during bad times (e.g., through the use of blanket guarantees for all claimants), or else the ex ante effectiveness of market discipline is lost entirely (e.g., Decamps, Rochet, and Roger, 2004). This brings up the issue of introducing firewalls in the financial sector. For example, does a subsidiary structure reduce systemic risk concerns? We do not think that an answer is readily available. More generally, what type of constraints, if any, should be put on the corporate structure of financial institutions? Until the 2007–9 financial crisis, the general belief was that deregulation in the financial sector would continue further,

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84   The Theory of Banking possibly leading to even bigger and broader financial institutions. But now it is far from clear what the future will bring. Some have suggested reintroducing the Glass–Steagall Act to insulate local banking from the risks and fads that periodically afflict financial markets. Proposals that echo the Glass–Steagall Act include the Dodd–Frank Act in the US, the Vickers Report in the UK (Vickers, 2011), and the Liikanen Report (Liikanen, 2012) in the EU. To what extent these are effective, and not overly costly, is open to debate.25 In any case, changes in the industrial structure of the financial sector might be of paramount importance for the design and effectiveness of regulation and supervision.26 A second issue has to do with the evolution of capital regulation. The introduction of Basel II rules meant that banks could fine-tune their required capital ratios based on their (certified) internal models. There are questions about whether these models induce procyclicality, and whether such model-dependency induces systemic risk by itself (e.g., institutions using the same models, and thus potentially being subject to the same shortcomings). There have also been concerns about the potential adverse consequences of the discretion that Basel II provides.27 Perhaps similar concerns led the FDIC to impose a minimum leverage ratio on banks in the Basel II environment; an element that the post-crisis Basel III amendments have introduced in the Basel framework as well. The FDIC has argued that requiring a minimum level of capital—regardless of risk— is essential for timely regulatory intervention in the event of problems. Such timely intervention seems particularly important in cross-border situations, given the complexities created by bank failures when multiple countries are involved. Timely intervention could help contain conflicts between local authorities in such cases (see Eisenbeis and Kaufman, 2005). This is one reason why new rules are proposed—commonly referred to as Basel III—that stipulate higher capital requirements, and indeed also a leverage ratio, although one could justifiably argue, as in Admati et al. (2011), that the levels of even these higher requirements may be well short of adequate.28 25  All these proposals seek to protect core banking functions against risks originating from financial markets. In the case of the Dodd–Frank Act, restrictions particularly aim at containing risks coming from private equity, hedge fund investments and derivatives. Vickers and Liikanen focus on internally separating banking operations. See BIS (2013, chapter 5) and Greenbaum, Thakor, and Boot (2016, chapter 16) for a discussion and comparison of the various proposals. Farhi and Tirole (2017) develop a theoretical framework for such containment. 26  Also important might be the ownership structure of financial institutions (see Berger et al., 2008). The concentration in the credit rating business and the importance of ratings for structured finance (securitization) is another issue. Structural changes could be desirable here as well. 27  This concern stems from the observation that individual banks are unlikely to sufficiently internalize the systemic-risk externalities of their actions. Consequently, the latitude that Basel II grants in having banks use their own internal risk assessment models to determine appropriate capital levels might be troublesome. Banks may tweak these models in order to generate prescriptions to keep low levels of capital (see Behn, Haselman, and Vig (2014) for evidence on this for German banks). The follow-up with Basel III seeks to provide remedies. 28  See also Thakor (2014). Berger and Bouwman (2013) provide empirical evidence that higher capital produces greater benefits for banks during financial crises, including a higher probability of survival. This is consistent with Thakor’s (2012) theory that higher capital weakens incentives for banks to introduce financial innovations that are associated with higher probabilities of financial crises.

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Commercial Banking and Shadow Banking   85 A third issue is deposit insurance. The 2007–9 financial crisis has made it clear that, when a real crisis hits, national authorities effectively feel compelled to fully guarantee the deposit bases of their financial institutions to eliminate the possibility of massive runs. This heavy dependence on insured deposits is an issue that needs a re-examination. Extant research (see Bhattacharya, Boot, and Thakor, 1998) has clearly shown the moral hazards that insured deposits entail. Moreover, Barth, Caprio, and Levine (2004) have shown that high levels of (de facto or de jure) deposit insurance impede the effectiveness of market discipline and increase the likelihood of a banking crisis. A question is whether strict regulatory limits should be put on the risks that institutions can expose these deposits to. Earlier research had at some point advocated narrow banking, which fully insulates insured deposits. But are there alternatives? And, more generally, can insured deposits be made less important as a funding vehicle for financial institutions? A fourth issue is whether regulation and supervision sufficiently address macro prudential issues, in particular systemic concerns. Despite many references to systemic risk, it appears that the majority of regulatory initiatives are focused on the well-being of individual financial institutions. That is, a micro prudential focus dominates (see Brunnemeier et al., 2009). This should be addressed to better reconcile regulation and supervision with the systemic concerns that are paramount. The fifth issue is that very little is known about the efficiency and effectiveness of various regulatory and supervisory structures. As Barth et al. (2003) put it, “there is very little empirical evidence on how, or indeed whether, the structure, scope or independence of bank supervision affects the banking industry.” Their own research suggests that the effect is at best marginal, but measurement problems are vexing. They suggest that narrowing the focus on the effect that regulation has on systemic risk may help. But here, too, little is known about the regulatory structures that are most efficient in dealing with systemic risk. We need considerable additional research to sharpen our identification of the costs and benefits of different regulatory and supervisory arrangements. Given the strikingly different national supervisory arrangements that exist today, our lack of knowledge on this issue is a significant barrier to progress toward a harmonized “superior” model.29 Finally, more research is needed on the role that bank culture can play in attenuating problems of excessive risk and financial fragility. Song and Thakor (forthcoming) have recently provided a theory of bank culture in which culture acts as a mediating variable in bank risk-taking and may attenuate the propensity of banks to herd on excessive and correlated risk-taking. This theory is a start, and it complements discussions within the Federal Reserve System in the US, and in the ECB with respect to what can be done to change corporate culture in banking (Dudley, 2014). The evidence in Cohn, Fehr, and 29  Some theoretical work suggests that competition between regulatory regimes might be helpful; see Kane (1988). This touches on a broader point: diversity in the financial sector—diversity in regulatory approaches, bank business models and ownership structures etc.—can be valuable. Too much homogeneity could invite systemic risk by itself (Boot, 2014; Butzbach, 2016; see also Berger et al., 2008).

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86   The Theory of Banking Marechal (2014) suggests that the culture in banking may encourage dishonest behavior; see also Cerqueti, Fiordelisi, and Rau (2016).30

3.7 Conclusions We have reviewed some of the literature on why banks exist, the risks they create, and how interbank competition as well as that from markets affects the economic roles served by banks as well as the attendant risks. One important development is that banks have become increasingly integrated with markets. This integration generates two effects that work in opposite directions. On the one hand, individual banks become better equipped to manage their own risks because it becomes easier and less costly to hedge these risks using the market. This could reduce the risk of an individual bank failing due to an idiosyncratic shock. On the other hand, there is an increase in the probability that a shock to a small subset of banks could generate systemic effects that ripple through the financial market, so that this banks–markets integration may be causing an elevation of systemic risk. It is easy to see that this substantially complicates the task of prudential regulation of banks and raises the specter of a widening of the “implicit” governmental safety net as ex post efficiency concerns tempt the government to bail out even uninsured players. This is no longer a mere theoretical conjecture, as demonstrated by the bailouts of investment banks and insurance companies in 2008–9. We believe that these are important issues that deserve greater theoretical and empirical attention. In particular, we need to have a better understanding of what the regulatory intervention should be in a crisis. Governmental initiatives such as those witnessed in the US during the 2007–9 crisis— massive governmental injections of liquidity and capital into banks and other financial institutions without an adequate corporate control role for the government—are very costly and possibly ineffective due to daunting moral hazard and asymmetric information problems. Some key lessons might be learnt from previous financial crises—for example, the Swedish financial crisis of the 1990s (see Ingves and Lind, 1994; Aghion, Bolton, and Fries, 1999). To conclude, we believe the most important, yet only partially answered, research questions raised by our discussion are the following: • What are the implications of the ever-increasing integration of banks and markets for systemic risk and fragility? • What will FinTech developments, including P2P lending, portend for banks? 30  We have not focused on the internal incentive structure in banks (which might be related to bank culture). As has become clear in the current crisis, internal risk management showed substantial lapses (see Group of Thirty,  2009). Other issues abstained from include procyclicality in Basel II and IFRS accounting standards.

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Commercial Banking and Shadow Banking   87 • What issues should we consider in the optimal design of regulation to respond to the (until recently, at least) growing cross-border footprints of major financial institutions and the increasing integration of banks and financial markets? • What changes, if any, should be imposed on the structure of the financial services industry in general, and the banking sector in particular, to contain the “mushrooming” nature of systemic risk concerns (i.e., to contain the scope of regulation and supervision)? • What role, if any, can market discipline play in helping safeguard the stability of the financial sector? • How do banks and private equity firms (and other non-banking financial institutions) interact and what implications does this interaction have for the regulation of banks and financial markets? • What role do credit rating agencies play in financial markets, how does this affect banks, and what implications does this have for systemic risks that bank regulators care about? These questions represent a rich agenda for future research.

References Acharya, V. and Pedersen, L. (2005). “Asset Pricing with Liquidity Risk,” Journal of Financial Economics, 77, 375–410. Acharya, V. and Schaefer, S. (2006). “Liquidity Risk and Correlation Risk: Implications for Risk Management,” Working Paper. Acharya, V. and Thakor, A. V. (2016). “The Dark Side of Liquidity Creation: Leverage- Induced Systemic Risk and Implications for the Lender of Last Resort,” Journal of Financial Intermediation, 28, 4–21. Acharya, V. and Yorulmazer, T. (2007). “Too Many to Fail—An Analysis of Time-Inconsistency in Bank Closure Policies,” Journal of Financial Intermediation, 16, 515–54. Acharya, V., Gromb, D., and Yorulmazer, T. (2007). “Failure in the Market for Liquidity Transfers and the Origins of Central Banking,” Working Paper. Admati, A. R., Demarzo, P. M., Hellwig, M. F., and Pfleiderer, P. C. (2011). “Fallacies, Irrelevant Facts, and Myths in the Discussion of Capital Regulation: Why Bank Equity is Not Expensive,” Stanford University Working Paper. Adrian, T. and Ashcraft, A. B. (2016). “Shadow Banking: A Review of the Literature,” in G. Jones (ed.), Banking Crises: Perspectives from the New Palgrave Dictionary of Economics (London: Palgrave Macmillan), 282–315. Adrian, T. and Shin, H. S. (2010). “The Changing Nature of Financial Intermediation and the Financial Crisis of 2007–09,” Annual Review of Economics, 2, 603–18. Aghion, P., Bolton, P., and Fries, S. (1999). “Optimal Design of Bank Bailouts: The Case of Transition Economies,” Journal of Institutional and Theoretical Economics, 155, 51–70. Alessi, C. (2012). The Basel Committee on Banking Supervision, Council on Foreign Relations, July 12. Allen, F. (1990). “The Market for Information and the Origin of Financial Intermediation,” Journal of Financial Intermediation, 1, 3–30.

OUP CORRECTED PROOF – FINAL, 08/23/2019, SPi

88   The Theory of Banking Allen, F. (1993). “Stock Markets and Resource Allocation,” in C. Mayer and X. Vives (eds.), Capital Markets and Financial Intermediation (Cambridge: Cambridge University Press), 81–108. Allen, F. (2005). “Modeling Financial Instability,” National Institute Economic Review, 192, 57–67. Allen, F. and Gale, D. (1995). “A Welfare Comparison of Intermediaries and Financial Markets in Germany and the US,” European Economic Review, 39, 179–209. Allen, F. and Gale, D. (1997). “Financial Markets, Intermediaries and Intertemporal Smoothing,” Journal of Political Economy, 105, 523–46. Bank of England (2014). “Money Creation in the Modern Economy,” Quarterly Bulletin Bank of England, Q1, 14–27. Barth, J., Caprio, G., and Levine, R. (2004). “Bank Regulation and Supervision: What Works Best?” Journal of Financial Intermediation, 13, 205–48. Barth, J. R., Nolle, D. E., Phumiwasana, T., and Yago, G. (2003). “A Cross-Country Analysis of the Bank Supervisory Framework and Bank Performance,” Financial Markets, Institutions & Instruments, 12, 67–120. Behn, M., Haselman, R., and Vig, V. (2014). “The Limits of Model-Based Regulation,” Working Paper, London Business School. Berger, A. and Bouwman, C. (2009). “Bank Liquidity Creation,” Review of Financial Studies, 22, 3779–837. Berger, A. and Bouwman, C. (2013). “How Does Bank Capital Affect Bank Performance During Financial Crises?” Journal of Financial Economics, 109, 146–76. Berger, A., Black, L., Bouwman, C., and Dlugosz, J. (2017). “Bank Loan Supply Responses to Federal Reserve Liquidity Facilities,” Journal of Financial Intermediation, 32, 1–15. Berger, A., Klappper, L. F., Martínez-Pería M. S., and Zaidi, R. (2008). “Bank Ownership Type and Banking Relationships,” Journal of Financial Intermediation, 17, 37–62. Berger, A., Miller, N., Petersen, M., Rajan, R., and Stein, J. (2005). “Does Function Follow Organizational Form? Evidence from the Lending Practices of Large and Small Banks,” Journal of Financial Economics, 76, 237–69. Berger, A., Saunders, A., Scalise, J., and Udell, G. (1998). “The Effects of Bank Mergers and Acquisitions on Small Business Lending,” Journal of Financial Economics, 50, 187–229. Berglöf, E. and von Thadden, E.-L. (1994). “Short-Term versus Long-Term Interests: Capital Structure with Multiple Investors,” Quarterly Journal of Economics, 109, 1055–84. Berlin, M. (1996). “For Better and for Worse: Three Lending Relationships,” Business Review Federal Reserve Bank of Philadelphia, (November/December), 3–12. Berlin, M. and Mester, L. (1992). “Debt Covenants and Renegotiation,” Journal of Financial Intermediation, 2, 95–133. Berlin, M. and Mester, L. (1999). “Deposits and Relationship Lending,” Review of Financial Studies, 12, 579–607. Bhattacharya, S. and Chiesa, G. (1995). “Proprietary Information, Financial Intermediation, and Research Incentives,” Journal of Financial Intermediation, 4, 328–57. Bhattacharya, S. and Thakor, A. V. (1993). “Contemporary Banking Theory,” Journal of Financial Intermediation, 3, 2–50. Bhattacharya, S., Boot, A. W. A., and Thakor, A. V. (1998). “The Economics of Bank Regulation,” Journal of Money, Credit and Banking, 30, 745–70. Bhattacharya, S., Boot, A. W. A., and Thakor, A. V. (eds.). (2004). Credit Intermediation and the Macro Economy (Oxford: Oxford University Press). BIS (2013). 83rd BIS Annual Report 2012/2013, June 23. BIS, Basel, Switzerland.

OUP CORRECTED PROOF – FINAL, 08/23/2019, SPi

Commercial Banking and Shadow Banking   89 BIS (2018). “Structural Changes in Banking After the Crisis,” Report prepared by a Working Group established by the Committee on the Global Financial System (CGFS), No. 60, Bank for International Settlements, Basel. Bolton, P. and Scharfstein, D. (1996). “Optimal Debt Structure and the Number of Creditors,” Journal of Political Economy, 104, 1–25. Bolton, P., Freixas, X., Gambacorta, L., and Mistrulli, P.  E. (2016). “Relationship and Transaction Lending in a Crisis,” Columbia University Working Paper. Boot, A. W. A. (2000). “Relationship Banking: What Do We Know?” Journal of Financial Intermediation, 9, 7–25. Boot, A. W. A. (2014). “Financial Sector in Flux,” Journal of Money, Credit and Banking, 46(1), 129–35. Boot, A. W. A. and Ratnovski, L. (2016). “Banking and Trading,” Review of Finance, 20(6), 2219–46. Boot, A. W. A. and Thakor, A. V. (1993). “Self-Interested Bank Regulation,” American Economic Review, 83, 206–12. Boot, A. W. A. and Thakor, A. V. (1994). “Moral Hazard and Secured Lending in an Infinitely Repeated Credit Market Game,” International Economic Review, 35(3), 899–920. Boot, A. W. A. and Thakor, A. V. (1997). “Financial System Architecture,” Review of Financial Studies, 10, 693–733. Boot, A. W. A. and Thakor, A. V. (2000). “Can Relationship Banking Survive Competition?” Journal of Finance, 55, 679–713. Boot, A. W. A., Greenbaum, S. I., and Thakor, A. V. (1993). “Reputation and Discretion in Financial Contracting,” American Economic Review, 83, 1165–83. Boot, A. W. A., Milbourn, T., and Schmeits, A. (2006). “Credit Ratings as Coordination Mechanisms,” Review of Financial Studies, 19, 81–118. Boot, A. W. A., Thakor, A. V., and Udell, G. (1991). “Credible Commitments, Contract Enforcement Problems and Banks: Intermediation as Credibility Assurance,” Journal of Banking & Finance, 15, 605–32. Boyd, J. H. and Gertler, M. (1994). “Are Banks Dead, or are the Reports Greatly Exaggerated?” Federal Reserve Bank of Minneapolis Quarterly Review, 18, 2–23. Brick, I. E. and Palia, D. (2007). “Evidence of Jointness in the Terms of Relationship Lending,” Journal of Financial Intermediation, 16, 452–76. Brophy, D., Ouimet, P. P., and Sialm, C. (2009). “Hedge Funds as Investors of Last Resort?” Review of Financial Studies, 22, 541–74. Brown, J., Martinson, G., and Petersen, B. (2017). “Stock Markets, Credit Markets and Technology-led Growth,” Journal of Financial Intermediation, 32, 45–59. Brunnemeier, M. and Pedersen, L. (2009). “Market Liquidity and Funding Liquidity,” Review of Financial Studies, 22, 2201–38. Brunnemeier, M., Crockett, A., Goodhart, C., and Shin, H. (2009). “The Fundamental Principles of Financial Regulation, Preliminary Draft of Geneva Reports on the World Economy,” No. 11, International Center for Monetary and Banking Studies, Geneva. Butzbach, O. (2016). “Systemic Risk, Macro-Prudential Regulation and Organizational Diversity in Banking,” Policy and Society, 35(3), 239–51. Calomiris, C. and Kahn, C. (1991). “The Role of Demandable Debt in Structuring Optimal Banking Arrangements,” American Economic Review, 81, 497–513. Cantor, R. (2004). “An Introduction to Recent Research on Credit Ratings,” Journal of Banking & Finance, 28, 2565–73.

OUP CORRECTED PROOF – FINAL, 08/23/2019, SPi

90   The Theory of Banking Carey, M., Post, M., and Sharpe, S. A. (1998). “Does Corporate Lending by Banks and Finance Companies Differ? Evidence on Specialization in Private Debt Contracting,” Journal of Finance, 53, 845–78. Carletti, E., Cerasi, V., and Daltung, S. (2007). “Multiple Bank Lending: Diversification and Free-Riding in Monitoring,” Journal of Financial Intermediation, 16, 425–51. Cerqueti, R., Fiordelisi, F., and Rau, R. (2016). “Corporate Culture and Enforcement Actions in Banking,” University of Cambridge, Working Paper. Chan, Y. S., Greenbaum, S. G., and Thakor, A. V. (1986). “Information Reusability, Competition and Bank Asset Quality,” Journal of Banking & Finance, 10, 243–53. Chemmanur, T. J. and Fulghieri, P. (1994). “Reputation, Renegotiation, and the Choice between Bank Loans and Publicly Traded Debt,” Review of Financial Studies, 7, 475–506. Claessens, S., Pozsar, Z., Ratnovski, L., and Singh, M. (2012). “Shadow Banking: Economics and Policy,” IMF Staff Discussion Note No. SDN 12/12, December 4. Coffee, J.  C. (2002). “Understanding Enron: It’s about the Gatekeepers, Stupid,” Columbia Center for Law and Economics Studies, Working Paper No. 207. Coffee, J. C. and Sale, H. A. (2008). “Redesigning the SEC: Does the Treasury have a Better Idea?” Columbia Center for Law and Economics Studies, Working Paper No. 342. Cohn, A., Fehr, E., and Marechal, M. A. (2014). “Business Culture and Dishonesty in the Banking Industry,” Nature, 516, 86–9. Coval, J. and Thakor, A.  V. (2005). “Financial Intermediation as a Beliefs-Bridge Between Optimists and Pessimists,” Journal of Financial Economics, 75, 535–70. Dang, T. V., Gorton, G., and Holmström, B. (2015). “Ignorance, Debt and Financial Crises,” Working Paper. Da Rin, M. and Hellmann, T. (2002). “Banks as Catalysts for Industrialization,” Journal of Financial Intermediation, 11, 366–97. Datta, S., Iskandar-Datta, M., and Patel, A. (1999). “Bank Monitoring and Pricing of Corporate Public Debt,” Journal of Financial Economics, 51, 435–49. De Bandt, O. and Hartmann, P. (2002). “Systemic Risk: A Survey,” in C. Goodhart and G. Illing (eds.), Financial Crises, Contagion and the Lender of Last Resort (Oxford: Oxford University Press), 249–98. Decamps, J., Rochet, J., and Roger, B. (2004). “The Three Pillars of Basel II: Optimizing the Mix,” Journal of Financial Intermediation, 13, 132–55. Degryse, H. and Ongena, S. (2007). “The Impact of Competition on Bank Orientation,” Journal of Financial Intermediation, 16, 399–424. Deidda, L. and Fattouh, B. (2008). “Banks, Financial Markets and Growth,” Journal of Financial Intermediation, 17, 6–36. Dell’Ariccia, G., Detragiache, E., and Rajan, R. (2008). “The Real Effect of Banking Crises,” Journal of Financial Intermediation, 17, 89–112. Dewatripont, M. and Maskin, E. (1995). “Credit and Efficiency in Centralized and Decentralized Economies,” Review of Economic Studies, 62, 541–55. DeYoung, R., Glennon, D., and Nigro, P. (2008). “Evidence from Informational-Opaque Small Business Borrowers,” Journal of Financial Intermediation, 17, 113–43. Diamond, D. (1984). “Financial Intermediation and Delegated Monitoring,” Review of Economic Studies, 51, 393–414. Diamond, D. (1991). “Monitoring and Reputation: The Choice Between Bank Loans and Directly Placed Debt,” Journal of Political Economy, 99, 689–721. Diamond, D. (1993). “Seniority and Maturity of Debt Contracts,” Journal of Financial Economics, 33, 341–68.

OUP CORRECTED PROOF – FINAL, 08/23/2019, SPi

Commercial Banking and Shadow Banking   91 Diamond, D. and Dybvig, P. H. (1983). “Bank Runs, Deposit Insurance and Liquidity,” Journal of Political Economy, 91, 401–19. Diamond, D. and Rajan, R.  G. (2001). “Liquidity Risk, Liquidity Creation and Financial Fragility: A Theory of Banking,” Journal of Political Economy, 109, 287–327. Dinç, I. S. (2000). “Bank Reputation, Bank Commitment, and the Effects of Competition in Credit Markets,” Review of Financial Studies, 13, 781–812. Donaldson, J., Piacentino, G., and Thakor, A. (2018). “Warehouse Banking,” Journal of Financial Economics, 129(2, August), 250–67. Drucker, S. (2005). “Information Asymmetries and the Effects of Banking Mergers in Firm– Bank Relationships,” Proceedings, Federal Reserve Bank of Chicago, 140–7. Drucker, S. and Puri, M. (2005). “On the Benefits of Concurrent Lending and Underwriting,” Journal of Finance, 60, 2763–99. Dudley, W. (2014). “Enhancing Financial Stability by Improving Culture in the Financial Services Industry,” remarks at the Workshop on Reforming Culture and Behavior in the Financial Services Industry, Federal Reserve Bank of New York, October 20. Eisenbeis, R. A. and Kaufman, G. G. (2005). “Bank Crises Resolution and Foreign-Owned Banks,” Federal Reserve Bank of Atlanta Economic Review, 90, 1–18. Emter, L., Schmitz, M., and Tirpak, M. (2018). “Cross-Border Banking in the EU since the Crisis: What is Driving the Great Retrenchment?” European Central Bank, Working Paper. Fang, L., Ivashina, V., and Lerner, J. (2010). “An Unfair Advantage? Combining Banking with Private Equity Investing,” Working Paper. Farhi, E. and Tirole, J. (2017). “Shadow Banking and the Four Pillars of Traditional Financial Intermediation,” Working Paper. Flannery, M. (1998). “Using Market Information in Prudential Bank Supervision: A Review of the US Empirical Evidence,” Journal of Money, Credit and Banking, 30, 273–305. Financial Stability Board (FSB) (2018). “Global Shadow Banking Monitoring Report 2017,” Financial Stability Board, March 5. Gande, A. and Saunders, A. (2005). “Are Banks Still Special when there is a Secondary Market for Loans?” New York University, Working Paper. Goel, A. and A. V. Thakor (2015). “Information Reliability and Welfare: A Theory of Coarse Credit Ratings,” Journal of Financial Economics, 115(3), 541–57. Goodfriend, M. and King, R. (1988). “Financial Deregulation, Monetary Policy and Central Banking,” in W. Haraf and R. M. Kushmeider (eds.), Restructuring Banking and Financial Services in America, American Enterprise Institute Studies 481 (Lanham, MD: University Press of America). Gorton, G. (1988). “Banking Panics and Business Cycles,” Oxford Economic Papers, 40, 751–81. Gorton, G. and Kahn, J.  A. (1993). “The Design of Bank Loan Contracts, Collateral, and Renegotiation,” National Bureau of Economic Research Working Paper No. W4273. Gorton, G. and Metrick, A. (2012). “Securitized Banking and the Run on Repo,” Journal of Financial Economics, 104, 425–51. Gorton, G. and Pennacchi, G. (1995). “Banks and Loan Sales: Marketing Nonmarketable Assets,” Journal of Monetary Economics, 35, 389–411. Goyal, V. (2005). “Market Discipline of Bank Risk: Evidence from Subordinated Debt Contracts,” Journal of Financial Intermediation, 14, 318–50. Greenbaum, S. I., Thakor, A. V., and Boot, A. W. A. (2016). Contemporary Financial Intermediation, 3rd edn (Cambridge, MA: Elsevier Academic Press). Group of Thirty (2009). “Financial Reform: A Framework for Financial Stability,” Report by the Working Group on Financial Reform, Washington, DC.

OUP CORRECTED PROOF – FINAL, 08/23/2019, SPi

92   The Theory of Banking Hauswald, R. and Marquez, R. (2006). “Competition and Strategic Information Acquisition in Credit Markets,” Review of Financial Studies, 19, 967–1000. Hellmann, T., Lindsey, L., and Puri, M. (2008). “Building Relationships Early: Banks in Venture Capital,” Review of Financial Studies, 21, 513–41. Hellwig, M. (1991). “Banking, Financial Intermediation and Corporate Finance,” in A. Giovanni and C. P. Mayer (eds.), European Financial Integration (New York: Cambridge University Press), 35–63. Herring, R. J. (2008). “The US Subprime Crisis: Lessons for Regulators,” Proceedings of the 44th Annual Conference on Bank Structure and Competition, Federal Reserve Bank of Chicago, 48–55. Hoshi, T., Kashyap, A., and Scharfstein, D. (1993). “The Choice between Public and Private Debt: An Analysis of Post-Deregulation Corporate Financing in Japan,” National Bureau of Economic Research Working Paper No. 4421. Houston, J. and James, C. (1996). “Bank Information Monopolies and the Mix of Private and Public Debt Claims,” Journal of Finance, 51, 1863–89. Ingves, S. and Lind, G. (1994). “The Management of the Bank Crisis: In Retrospect,” Sverigs Riksbank Quarterly Review, 1, 5–18. Jacklin, C. J. (1987). “Demand Deposits, Trading Restrictions and Risk Sharing,” in E. Prescott and N. Wallace (eds.), Financial Intermediation and Intertemporal Trade (Minneapolis, MN: University of Minnesota Press), 26–47. James, C. (1987). “Some Evidence on the Uniqueness of Bank Loans,” Journal of Financial Economics, 19, 217–35. Kane, E. J. (1988). “How Market Forces Influence the Structure of Financial Regulation,” in W. S. Haraf and R. M. Kushmeider (eds.), Restructuring Banking and Financial Services in America (Washington, DC: American Enterprise Institute Press), 343–82. Kashyap, A., Rajan, R., and Stein, J. (2002). “Banks as Liquidity Providers: An Explanation for the Co-Existence of Lending and Deposit-Taking,” Journal of Finance, 57, 33–73. Keys, B., Mukherjee, T., Seru, A., and Vig, V. (2010). “Did Securitization Lead to Lax Screening: Evidence from Subprime Loans,” Quarterly Journal of Economics, 125, 307–62. Kroszner, R. S. and Rajan, R. G. (1994). “Is the Glass–Steagall Act Justified? A Study of the US Experience with Universal Banking before 1933,” American Economic Review, 84, 810–32. Laeven, L. and Levine, R. (2007). “Is there a Diversification Discount in Financial Conglomerates?” Journal of Financial Economics, 85, 331–67. Liikanen, E. (2012). “High-level Expert Group on Reforming the Structure of the EU Banking Sector,” Final Report, Brussels, October 2. Lizzeri, A. (1999). “Information Revelation and Certification Intermediaries,” Rand Journal of Economics, 30, 214–31. Lopez-Espinosa, G., Mayordomo, S., and Moreno, A. S. A. (2017). “When does Relationship Lending Start to Pay?” Journal of Financial Intermediation, 31, 16–29. Lummer, S. L. and McConnell, J. J. (1989). “Further Evidence on the Bank Lending Process and the Reaction of the Capital Market to Bank Loan Agreements,” Journal of Financial Economics, 25, 99–122. Mayer, C. (1988). “New Issues in Corporate Finance,” European Economic Review, 32, 1167–83. Mehran, H. and Thakor, A. V. (2011). “Bank Capital and Value in the Cross-Section,” Review of Financial Studies, 24(4), 1019–67. Merton, R. and Thakor, R. (forthcoming). “Customers and Investors: A Framework for Understanding the Evolution of Financial Institutions,” Journal of Financial Intermediation.

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Commercial Banking and Shadow Banking   93 Mian, A.  R. and Sufi, A. (2009). “The Consequences of Mortgage Credit Expansion: Evidence from the 2007 Mortgage Default Crisis,” Quarterly Journal of Economics, 124, 1449–96. Millon, M. and Thakor, A. V. (1985). “Moral Hazard and Information Sharing: A Model of Financial Information Gathering Agencies,” Journal of Finance, 40, 1403–22. Ongena, S. and Smith, D. C. (2000). “What Determines the Number of Bank Relationships? Cross-Country Evidence,” Journal of Financial Intermediation, 9, 26–56. Partnoy, F. (1999). “The Siskel and Ebert of Financial Markets: Two Thumbs Down for the Credit Rating Agencies,” Washington University Law Quarterly, 77, 619–712. Petersen, M. and Rajan, R. G. (1994). “The Benefits of Lending Relationships: Evidence from Small Business Data,” Journal of Finance, 49, 1367–400. Petersen, M. and Rajan, R. (1995). “The Effect of Credit Market Competition on Lending Relationships,” Quarterly Journal of Economics, 110, 407–43. Posen, A. S. and Hinterschweiger, M. (2009). “How Useful were Recent Financial Innovations? There is Reason to be Skeptical,” Real Time Economic Issues Watch, May 7. Pozsar, Z., Adrian, T., Ashcraft, A., and Boesky, H. (2010). “Shadow Banking,” Federal Reserve Bank of New York, FRNBNY Staff Report No. 458. Puri, M. (1996). “Commercial Banks in Investment Banking: Conflict of Interest or Certification Role?” Journal of Financial Economics, 40, 373–401. Puri, M., Rocholl, J., and Steffen, S. (2017). “What do a Million Observations Have to Say About Loan Default? Opening the Black Box of Relationships,” Journal of Financial Intermediation, 31, 1–15. Rajan, R. G. (1992). “Insiders and Outsiders: The Choice between Informed and Arm’s Length Debt,” Journal of Finance, 47, 1367–400. Ramakrishnan, R. and Thakor, A. V. (1984). “Information Reliability and a Theory of Financial Intermediation,” Review of Economic Studies, 51, 415–32. Ramírez, C. (2002). “Did Banks’ Security Affiliates Add Value? Evidence from the Commercial Banking Industry during the 1920s,” Journal of Money, Credit and Banking, 34, 391–411. Rochet, J.-C. (2004). “Bank Runs and Financial Crises: A Discussion,” in S.  Bhattacharya, A.  W.  A.  Boot, and A.  V.  Thakor (eds.), Credit Intermediation and the Macro Economy (Oxford: Oxford University Press), 324–38. Rochet, J.-C. and Vives, X. (2004). “Coordination Failures and the Lender of Last Resort: Was Bagehot Right After All?” Journal of the European Economic Association, 2(6), 1116–47. Sangiorgi, F. and Spatt, C. (2017a). “Opacity, Credit Rating Shopping, and Bias,” Management Science, 63(12), 4016–36. Sangiorgi, F. and Spatt, C. (2017b). “The Economics of Credit Rating Agencies,” Foundations and Trends in Finance, 12(1), 1–116. Sapienza, P. (2002). “The Effects of Banking Mergers on Loan Contracts,” Journal of Finance, 57, 329–67. Schenone, C. (2004). “The Effect of Banking Relationships on the Firm’s IPO Underpricing,” Journal of Finance, 59, 2903–3058. Schmid, M.  M. and Walter, I. (2009). “Do Financial Conglomerates Create or Destroy Economic Value?” Journal of Financial Intermediation, 18, 193–216. Sharpe, S. A. (1990). “Asymmetric Information, Bank Lending, and Implicit Contracts: A Stylized Model of Customer Relationships,” Journal of Finance, 45, 1069–87. Shleifer, A. and Vishny, R. W. (2010). “Unstable Banking,” Journal of Financial Economics, 97, 306–18.

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94   The Theory of Banking Shockley, R. and Thakor, A. V. (1997). “Bank Loan Commitment Contracts: Data, Theory and Tests,” Journal of Money, Credit and Banking, 29, 517–34. Simons, H.  C. (1936). “Rules versus Authorities in Monetary Policy,” Journal of Political Economy, 44, 1–30. Song, F. and Thakor, A.  V. (2007). “Relationship Banking, Fragility and the Asset-Liability Matching Problem,” Review of Financial Studies, 20, 2129–77. Song, F. and Thakor, A. V. (2010). “Financial System Architecture and the Co-evolution of Banks and Markets,” The Economic Journal, 120, 1021–255. Song, F. and Thakor, A. V. (forthcoming). “Bank Culture,” Journal of Financial Intermediation. Stein, J.  C. (2002). “Information Production and Capital Allocation: Decentralized versus Hierarchical Firms,” Journal of Finance, 57, 1891–921. Strahan, P. E. (2007). “Bank Structure and Lending: What We Do and Do Not Know,” Boston College Working Paper. Thakor, A. V. (1996). “Capital Requirements, Monetary Policy and Aggregate Bank Lending: Theory and Empirical Evidence,” Journal of Finance, 51, 279–324. Thakor, A.  V. (2012). “Incentives to Innovate and Financial Crisis,” Journal of Financial Economics, 103(1), 130–48. Thakor, A. V. (2014). “Bank Capital and Financial Stability: An Economic Tradeoff or a Faustian Bargain?” Annual Review of Financial Economic, 6, 185–223. Thakor, A.  V. (2015). “Lending Booms, Smart Bankers and Financial Crises,” American Economic Review, 105(5, May), 305–9. Thakor, A.  V. (2016). “The Highs and the Lows: A Theory of Credit Risk Assessment and Pricing through the Business Cycle,” Journal of Financial Intermediation, 25(1), 1–29. US Senate Hearings (2002). “Rating the Raters: Enron and the Credit Rating Agencies,” Hearings before the Senate Committee on Governmental Affairs, Washington, DC. US Senate Staff Report (2002). “Financial Oversight of Enron: The SEC and Private-Sector Watchdogs,” Report of the Staff to the Senate Committee on Governmental Affairs, Washington, DC. Vickers, J. (2011). “Independent Commission on Banking,” Final Report, London, September 12. von Thadden, E.-L. (1998). “Intermediated versus Direct Investment: Optimal Liquidity Provision and Dynamic Incentive Compatibility,” Journal of Financial Intermediation, 7, 177–97.

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chapter 4

Cor por ate Complex it y a n d Systemic R isk A Progress Report Jacopo Carmassi and Richard J. Herring

4.1 Introduction The first edition of this chapter, drafted in 2007–8, before the start of the Great Financial Crisis (GFC), documented the growing complexity of the corporate structure of Global Systemically Important Banks (G-SIBs)1 and analyzed the factors driving this complexity. We found that for the sixteen international banks designated as systemically important, the median number of controlled subsidiaries was 923 with a high of 2,435. Moreover, these sixteen banks had extensive cross-border involvement. The median percent of foreign subsidiaries was 53 percent with a high of 96 percent. These findings and the opacity of these relationships led us to conclude that, in the event of an insolvency, international corporate complexity would defy an efficient resolution. We conjectured that if the authorities lacked confidence they would be able to resolve such an institution without potentially devastating systemic spillovers, they would feel obliged to improvise a bailout, notwithstanding any prior avowals to the contrary. This would contribute to the perception that some institutions were too complex to fail, which would undermine market discipline that might otherwise constrain 1  The Basel Committee on Banking Supervision (BCBS) published the methodology for identifying G-SIBs in July 2011 (BCBS, 2011) and the Financial Stability Board (FSB, 2011a) published the first official list of G-SIBs, initially termed Global Systemically Important Financial Institutions, in November 2011. Of necessity, the first edition of this chapter relied on a slightly different classification, Large and Complex Financial Institutions (LCFIs), developed by the Bank of England and the International Monetary Fund before the G-SIB concept was introduced. Thirteen of the sixteen institutions identified as LCFIs in 2007 survived the crisis and all thirteen of these survivors were listed among the twenty-nine G-SIBs identified in 2011. For simplicity, we have dropped the LCFI terminology and refer only to G-SIBs.

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96   The Theory of Banking risk-taking by these institutions. Before the GFC, the regulatory authorities largely neglected the issue of the corporate complexity of G-SIBs. The behavior of the authorities during the GFC was consistent with our earlier conjecture. At the height of the GFC the authorities in the United States, the United Kingdom and the Eurozone had committed over $14 trillion, about one-quarter of the world GDP, to prop-up their banking systems (Haldane and Alessandri, 2009). Indeed, the one major exception to this pattern of bailouts, the bankruptcy of Lehman Brothers in September 2008, by far the smallest and one of the least complex of our initial list of  systemically important international financial institutions, demonstrated that the authorities lacked the tools to implement an orderly resolution of an international financial institution with a complex, international corporate structure. The attempt to resolve Lehman Brothers without the appropriate policy infrastructure did lead to spillovers that damaged much of the international financial system and contributed to the depth of the consequent recession. The issue of the complexity and opacity of the corporate structure of G-SIBs vaulted to the top of the reform agenda in the wake of the GFC. Excessive risk-taking and leverage are generally regarded as the fundamental causes of the GFC, but corporate complexity and opaque interconnections among and within institutions impeded effective oversight by the authorities ex ante and greatly complicated crisis management and resolution of insolvent institutions ex post. The authorities began to realize that massive bailouts created expectations of still greater future bailouts that would create huge taxpayer liabilities, which could not be justified on political or economic grounds. As Thomas Huertas (2014) observed, a continuing policy of too-big- (or too-complex-) to-fail was “too expensive to continue.” The Group of 20 Heads of State (G20) meeting in September 2009 officially recognized the problem and mandated the Financial Stability Board to identify G-SIBs and ensure that each G-SIB prepared a credible recovery and resolution plan that would ensure each G-SIB could be resolved in an orderly manner without taxpayer subsidy. The second edition of this chapter, drafted in 2013, re-examined the topic of corporate complexity as these reforms were being implemented. We analyzed the reform agenda and investigated whether any discernable impact had yet been made on our measure of corporate complexity, the number of controlled subsidiaries.2 The results were decidedly mixed. Despite the disappearance of three of the institutions on our initial list of G-SIBs, the overall trend toward bigger and more complex banks had continued (often encouraged by publicly subsidized mergers). Although some banking groups had made 2  Admittedly, this is a very simplistic indicator of corporate complexity, but it remains the only indicator that can be measured with any degree of accuracy. We have relied on Bureau Van Dijk (BvD) data (first Bankscope, then Orbis and BankFocus), because they provide information about the full international set of G-SIBs using a clear methodology that is consistent across countries and banks. Although SEC filings and the FED/National Information Center data are available for the eight US G-SIBs, each of these sources uses a different methodology, which produces different results for the number of controlled subsidiaries. These results differ—not only from each other but also from the BvD data. See Carmassi and Herring (2015) for a detailed comparison of data and criteria across BvD, FED/ NIC data and SEC filings.

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Corporate Complexity and Systemic Risk   97 verifiable progress in rationalizing and simplifying their corporate structures, others had greatly increased their number of subsidiaries so that, on average, our measure of corporate complexity had not decreased since the crisis. In this third edition of the Handbook, we examine progress in the rationalization and simplification of the corporate complexity of G-SIBs ten years after the GFC and nine years after the Group of Twenty (2009) announced that all “Systemically important financial firms should develop international-consistent firm-specific contingency and resolution plans.” To implement this promise, the FSB developed Key Attributes of Effective Resolution Regimes for Financial Institutions (KA) (FSB, 2011b) to be adopted by all countries that host G-SIBs. Among other measures, the KA required that G-SIBs should be required to identify essential and systematically important functions and map them into the legal entities within which they are conducted. In addition, countries were urged to establish resolution regimes that would provide for speed and transparency and as much predictability as possible for orderly resolution. The overall objective was to establish credible resolution procedures that would enhance market discipline and provide incentives for market-based solutions to deal with faltering banking groups. Although banks have been obliged to disclose massive amounts of data relevant to resolution, very little of it is made public. Analysts outside the regulatory community face substantial challenges in monitoring progress toward the achievement of the KA. The FSB has established a peer review process to monitor progress by each country, which is reported annually to the G20. The implementation report for 2017 (FSB, 2017a, pp. 26–7) indicates that ten of the twenty-eight FSB jurisdictions have powers to require changes to firms’ structure and operations to improve resolvability.3 Whether the existence of such powers has resulted in a significant reduction in the number of subsidiaries controlled by G-SIBs is a key question addressed in this chapter. More broadly, we analyze why complexity may jeopardize systemic stability, review the factors that have incentivized G-SIBs to adopt such complex and opaque structures, examine the broader policy agenda to enhance the resolvability and consider what additional measures could be taken to enhance the transparency of the corporate structure of G-SIBs.

4.2  Why the Complex, Opaque, International Corporate Structure of G-SIBs Jeopardizes Systemic Stability Mervyn King (2010) observed, “[M]ost large complex financial institutions are global— at least in life if not in death.” This poses a fundamental problem to resolving a G-SIB. In the event of insolvency an integrated G-SIB’s lines of business would first need to be mapped into the legal entities that would then need to be taken through national 3  The ten jurisdictions that have such powers are France, Germany, Hong Kong, Italy, Japan, The Netherlands, Spain, Switzerland, the United Kingdom and the United States.

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98   The Theory of Banking bankruptcy or administrative process. Prior to the post-crisis reforms, most G-SIBs were managed as integrated global entities, with complex operational and financial interrelationships and minimal regard for legal entities in which transactions were booked and operations were located. The Lehman Brothers (LB) bankruptcy demonstrated the daunting challenges the authorities faced in resolving a G-SIB that was managed as a single, integrated entity. Lehman’s total reported assets were roughly $700 billion when it applied for bankruptcy. Its corporate structure included 433 subsidiaries in twenty countries (based on Bureau Van Dijk (BvD) data; see Herring and Carmassi, 2010). Not only was this hierarchy opaque to outsiders, but also court records show that employees were often unaware of distinctions among these legal entities or, indeed, of which legal entity employed them. These legal entities held a number of different regulatory licenses and were regulated by a variety of different national authorities including securities and banking regulators. In addition, LB participated in a number of exchanges and clearing settlement systems, each of which had procedures that must be followed to approve the continuing operations of its members. This posed formidable coordination challenges to any effort to preserve the value of LB as a going concern. LB actively participated in global financial markets in which it was the sixth largest counterparty in OTC derivatives markets and a major borrower in the repo market, which totaled roughly $11 trillion at the time. More than 43,000 trades were still live when Lehman failed and had to be negotiated separately with each counterparty. The bankruptcy filing set-off cross default clauses in more than 900,000 contracts and triggered close-out netting by counterparties that caused downward pressure on asset prices, which adversely affected the solvency of other major financial institutions. The result was 60 civil proceedings extending over three continents, which made it virtually impossible to preserve whatever going concern value might have otherwise been salvaged. Because LB was managed as an integrated group with minimal regard for the legal entities, disentangling its financial obligations and operations impeded an efficient resolution. Lehman Brothers Holdings Inc. (LBHI) issued the vast majority of the unsecured debt for the group and invested most of the proceeds in its subsidiaries. This was a common approach to managing a global corporation, designed to facilitate control over global operations, while reducing funding, capital, and tax costs. LBHI, in effect, served as treasurer for its affiliates, running a zero-balance cash-management system. LBHI lent to its operating subsidiaries at the beginning of each day and then swept the cash back to LBHI at the end of each day to be managed overnight from LBHI headquarters in New York. The bankruptcy petition was filed in the United States before most of the subsidiaries had been funded, which tied up most of LB’s cash in US court proceedings, leaving its international subsidiaries bereft of liquidity. Lehman also centralized its information technology so that data for different products and different subsidiaries were co-mingled. This was an efficient way of running the business as a going concern but presents an enormous problem in uncoordinated global bankruptcy proceedings. LB used approximately 2,700 proprietary, third-party, and offthe-shelf programs, each of which interacted with or created transactions data that LB

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Corporate Complexity and Systemic Risk   99 stored on 26,666 servers, 20,000 of which contained accumulated emails, files, voicemail messages, instant messages, and recorded calls. The largest data centers were in New York, London, Tokyo, Hong Kong, and Mumbai, but this integrated approach fragmented when the bankruptcy petition was filed so that individual subsidiaries lost access to information stored in other jurisdictions. Much of this information needed to be preserved, extracted, stored, and analyzed for bankruptcy administrators to resolve each legal entity. Consequently, it was necessary to negotiate complex protocols among the various jurisdictions in which the data resided and the jurisdictions in which the legal entity resided, before the various resolution authorities could sort out the claims of various creditors and counterparties. This breakdown in the management information systems impeded the determination of what had become of the trades customers had placed with individual entities or funds advanced by creditors to individual legal entities. In addition, the LB bankruptcy revealed that most jurisdictions were totally illequipped to deal with the collapse of a major international institution, except through costly and disruptive liquidation proceedings. For example, the administrators in the United Kingdom found it difficult even to fund basic services such as lights and catering while they undertook investigations within the firm. As chaotic and destructive as the LB bankruptcy proved to be, the authorities realized it could have been much worse. Many G-SIBs had much larger balance sheets (measured in  trillions not billions), more extensive interconnections, more complex intra-affiliate transactions, more diverse lines of business, more complex organizational structures, and more extensive international involvement. Given the lack of coordination among international resolution authorities, and the inadequacy of most resolution regimes for coping with the insolvency of a complex international financial institution, there seemed no plausible way to resolve such an institution without exacerbating international financial instability. Against this background, the G20 met in 2009 to agree on plans to reform the international financial system. But before turning to a discussion of these reforms we first examine data showing the extent of complexity before the GFC and how the number of subsidiaries controlled by G-SIBs has evolved over the subsequent ten years. We will then consider why G-SIBs have chosen to adopt such large and complex corporate structures.

4.3  Corporate Complexity of G-SIBs: An Update 10 Years After the Crisis The first edition of this chapter documented the corporate complexity of international systemically important banks at the end of 2007, just before the GFC. The second edition of this chapter examined the evolution in the corporate complexity of G-SIBs from 2007 to 2013. Our key measure of corporate complexity is the number of “ultimately

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100   The Theory of Banking owned”/controlled subsidiaries in the BvD database. Ultimately owned subsidiaries are those legal entities in which the G-SIB’s ownership share is at least 50.01 percent in all the nodes of the ownership chain.4 This criterion for control is conservative because effective control can be exercised through a much smaller ownership position if the remaining shares are widely dispersed among a number of shareholders. The Fed, for example, uses a threshold of 25 percent to identify controlled subsidiaries. Despite this conservative bias, we found that most G-SIBs controlled a remarkably large number of subsidiaries in both 2007 and 2013. As of December 2007, the average number of ultimately owned subsidiaries of international, systemically important banks was 969 with considerable variation (with a difference of 2,168 controlled subsidiaries) between the most and the least complex institution. On average, the majority of these subsidiaries were incorporated in foreign jurisdictions (56 percent). By number, only a small share of subsidiaries was involved in the banking (5 percent) or insurance business (2 percent), while larger shares were classified as vehicles and trusts (22 percent), other financial firms (27 percent) and, most notably, non-financial entities (43 percent). The overall picture did not change in 2013 with a new sample consisting of the 28 institutions identified as G-SIBs by the FSB in November 2012. The average number of subsidiaries remained almost the same (964 in May 2013), as did the share of foreign subsidiaries (60 percent in May 2013). The average size of the 28 G-SIBs increased from $1.5 trillion as of year-end 2007 to $1.6 trillion as of year-end 2012, mainly as a result of mergers and acquisitions that occurred during the crisis. Thus, five years after the crisis, systemically important banks had remained very complex and had grown larger. In 2009, the Group of Twenty (G20) heads of state had announced ambitious plans to ensure that each G-SIB could be resolved without intolerable spillovers and without government assistance (see section  4.5 below). These reforms included initiatives to simplify and rationalize the corporate structure of G-SIBs and to map lines of business in each G-SIB into its legal entities. These measures were expected to reduce the number of controlled subsidiaries, but the reforms were quite challenging for most jurisdictions requiring fundamental legislative and institutional changes, which were expected to take several years to implement.5 Thus, it was premature to draw conclusions about the impact of the post-crisis reforms on our measure of corporate complexity in the second edition of this chapter. A key contribution of this chapter is to provide new data on the corporate complexity of G-SIBs as of October 2018, ten years after the start of the GFC. These new data will help to shed more light on whether the post-crisis reforms have reduced our measure of corporate complexity—the number of subsidiaries controlled by G-SIBs. Table 4.1 reports information regarding the size, foreign business and total number of ultimately owned subsidiaries of 32 G-SIBs. This sample combines the 28 G-SIBs 4  The BvD dataset also provides the possibility of using a 25 percent threshold, but we have chosen the more conservative option. 5  For example, in 2012 banks in the US were required for the first time to file resolution plans with the regulators. In Europe, the new resolution framework, which includes resolution planning, was adopted only in 2014.

Table 4.1  Size and Complexity of G-SIBs, 2018 vs. 2013 (G-SIBs Ranked by Total Assets 2017)

G-SIBs

Total assets 2017 (USD mln)

Total assets 2013 (USD mln)

% of foreign assets, 2017

% of foreign revenues/income, 2017

Total subsidiaries (October 2018)

Total subsidiaries (May 2013)

1

ICBC

4,006,242

3,100,051

13%

11%

266

36

2

China Construction Bank

3,397,688

2,517,568

5%

4%

255

89

3

Agricultural Bank of China

3,233,212

2,386,291

4%

2%

29

14

Bank of China

2,989,653

2,273,581

10%

7%

199

116

Mitsubishi UFJ

2,890,455

2,509,791

35%

74%

236

112

6

JPMorgan Chase

2,533,600

2,415,689

24%

22%

2,703

1,095

7

HSBC

2,521,771

2,671,318

69%

75%

1,922

1,565

8

BNP Paribas

2,350,929

2,496,891

68%

.

1,794

2,592

9

Bank of America

2,281,477

2,104,995

14%

14%

2,828

1,910

10

Crédit Agricole

2,114,568

2,328,285

17%

37%

1,469

1,255

11

Wells Fargo

1,951,757

1,527,015

5%

1%

2,151

1,549

12

Mizuho

1,930,768

1,709,508

30%

50%

132

103

13

Sumitomo Mitsui

1,874,462

1,570,582

24%

30%

199

165

14

Citigroup

1,842,465

1,880,035

49%

45%

2,009

2,297

15

Deutsche Bank

1,768,645

2,222,282

71%

63%

1,499

2,124

16

Santander

1,732,154

1,538,576

67%

90%

1,024

605

17

Barclays

1,531,189

2,212,686

58%

47%

935

1,739

18

Société Générale

1,529,260

1,674,494

27%

52%

1,016

913

19

BPCE

1,510,938

1,549,446

9%

21%

1,848

1,448 (continued)

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4 5

G-SIBs

Total assets 2017 (USD mln)

Total assets 2013 (USD mln)

% of foreign assets, 2017

% of foreign revenues/income, 2017

Total subsidiaries (October 2018)

Total subsidiaries (May 2013)

20

ING Groep

1,014,866

1,491,244

71%

59%

310

764

21

Unicredit

1,003,562

1,166,496

56%

53%

1,322

2,216

22

Royal Bank of Scotland

997,225

1,692,709

9%

34%

728

799

23

Royal Bank of Canada

944,810

822,250

47%

27%

300

305

24

UBS

939,570

1,136,685

58%

61%

357

458

25

Goldman Sachs

916,787

911,595

41%

37%

3,857

420

26

Morgan Stanley

851,733

832,666

33%

27%

3,439

1,311

27

BBVA

827,587

803,429

54%

73%

502

415

28

Credit Suisse

816,455

979,031

70%

63%

561

242

29

Nordea

697,527

869,432

82%

79%

216

220

30

Standard Chartered

663,501

674,380

82%

97%

808

118

31

Bank of New York Mellon

371,758

374,310

30%

51%

1,231

279

32

State Street Corporation

238,496

243,028

34%

42%

293

155

Average

1,696,097

1,646,448

40%

43%

1,139

884

Median

1,631,672

1,622,538

35%

45%

872

605

Range

3,767,746

2,857,023

78%

96%

3,828

2,578

Source: BankFocus (BvD) for total assets and number of subsidiaries; annual reports, SNL and other public regulatory and bank reports for the share of foreign assets and foreign revenues/income. Data on subsidiaries for BCPE SA in 2018 as of May. Data on subsidiaries for Agricultural Bank of China, China Construction Bank, and Royal Bank of Canada as of July 2015 instead of May 2013.

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Table 4.1  Continued

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Corporate Complexity and Systemic Risk   103 a­ nalyzed in the second edition of this chapter with four additional G-SIBs included in the most recent list (FSB, 2017b).6 Table 4.1 shows that the average size of G-SIBs has remained almost unchanged at $1.6 trillion. This average is mainly driven by the four Chinese G-SIBs, each of which had balance sheets well above $2 trillion already in 2013 and had become substantially larger by 2017. Excluding the Chinese G-SIBs, the average size of the remaining G-SIBs decreased slightly from $1.51 trillion (year-end 2013) to $1.45 trillion (year-end 2017). This average conceals substantial differences across banks. Some G-SIBs have downsized significantly (for example, Royal Bank of Scotland: −41 percent; Barclays: −31 percent; Deutsche Bank: −20 percent), while others have grown larger (for example, Wells Fargo: +28 percent; Mitsubishi UFJ: +15 percent; Santander: +13 percent). With regard to foreign activities, on average over 40 percent of both total assets and foreign revenues/ income are related to foreign business, in line with 2007 and 2013 data shown in the ­previous editions of this chapter.7 The right-most two columns of Table 4.1 display the number of controlled subsidiaries of G-SIBs, based on the BvD dataset, as of October 2018 and May 2013 (the point in time for the number of subsidiaries used in the second edition of this chapter).8 These data indicate that our measure of corporate complexity has not decreased. On the contrary, the average has increased from 884 in 2013 to 1,139 in 2018. This result, however, is strongly influenced by large increases in the number of subsidiaries reported for most US G-SIBs, which may be attributable to a change in the sources of data used by BvD for US banks and so it may be appropriate to remove the US G-SIBs for the purpose of comparing the evolution of the subsidiaries of G-SIBs. Even without the inclusion of the BvD data for US G-SIBs, the overall number of controlled subsidiaries remains high although it decreased somewhat. Excluding US G-SIBs from both the 2013 and 2018 data, the average number of subsidiaries of the remaining G-SIBs decreased from 821 in 2013 to 766 in 2018, a 7 percent reduction. Even so, the evidence across G-SIBs remains mixed. Some banks substantially increased their number of controlled subsidiaries since 2013 (e.g., Standard Chartered +585 percent; Credit Suisse +132 percent; UFJ +111 percent; Bank of China +72 percent; Santander +69 percent), while others have sharply reduced

6  ICBC, China Construction Bank, the Agricultural Bank of China and the Royal Bank of Canada have been added to the list, while two of the institutions designated as G-SIBs in 2012—BBVA and BPCE—were no longer classified as G-SIBs in 2017. We have retained BBVA and BPCE in our sample to broaden our analysis of how the number of controlled subsidiaries has evolved. 7  Data on foreign revenues/income are not fully comparable across G-SIBs because, due to data availability issues, different measures had to be used for different banks (e.g., operating income, income before taxation, etc.). 8  For simplicity, in the following text we will refer to 2013 and 2018 data without specifying the month. Because the Agricultural Bank of China, the China Construction Bank and the Royal Bank of Canada were not classified as G-SIBS in 2012, we did not download data on their corporate structures from the BvD database in May 2013 when we performed our analysis for the second edition of this chapter. Unfortunately it is difficult and costly to retrieve historical BvD data and so we show only data from July 2015, which are the oldest data we have for these institutions.

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104   The Theory of Banking their number of controlled subsidiaries (e.g., Barclays −46 percent; Unicredit −40 percent; BNP Paribas −31 percent; Deutsche Bank −29 percent). Based on BvD data for October 2018 including the eight US G-SIBs, fifteen G-SIBs had more than 1,000 controlled subsidiaries and six US G-SIBs had over 2,000 subsidiaries. The extent of cross-border complexity, as measured by the number of countries in which G-SIBs operate, remains high. As shown in Table 4.2, on average G-SIBs now control subsidiaries in forty-five different countries (with 59 percent of foreign subsidiaries as measured in 2018) compared to forty-one (60 percent of foreign subsidiaries measured in 2013). Notably, however, the average proportion of subsidiaries located in off-shore financial centers (OFCs) has increased from 15 percent in 2013 to 18 percent in 2018. Twenty-one G-SIBs have located more than 10 percent of their subsidiaries in OFCs, while eleven of these G-SIBs have located more than 20 percent of their subsidiaries in OFCs. The distribution of subsidiaries across industries is broadly consistent over time. Table 4.3 shows that, by number, 5 percent subsidiaries of the 32 G-SIBs were classified as banking subsidiaries in both 2018 and 2013 and 1 percent were insurance subsidiaries in 2018 versus 2 percent in 2013. Trusts and vehicles represented 23 percent of all entities in 2018 (up from 19 percent in 2013), while other financial companies accounted for 17 percent (down from 28 percent in 2013). Non-financial subsidiaries remain the largest category, representing over half of the total number of subsidiaries in 2018 (54 percent, up from 46 percent in 2013). Again, bank-by-bank data reveal significant differences across banks. For example, Asian G-SIBs tend to have a higher share of banking subsidiaries and a smaller number of total subsidiaries. For some G-SIBs the share of nonfinancial subsidiaries is remarkably high with 80 percent of Unicredit’s subsidiaries classified as non-financial, the highest proportion among G-SIBs. In the following section we will also discuss, together with other factors affecting complexity, some of the potential drivers of the high share of non-financial subsidiaries of G-SIBs. The lack of sufficient and consistent disclosures across G-SIBs impedes deeper analysis of the evolution of corporate complexity among G-SIBs. To our knowledge, only the BvD database9 provides consistent and systematic information on the subsidiaries of all G-SIBs. As highlighted in Carmassi and Herring (2015, 2016a), significant discrepancies emerge when comparing data on corporate structures across different sources. Although the Federal Reserve data available on the National Information Center (NIC) website provide granular information on the organizational structures of US banks, the lists of subsidiaries do not match the lists of those reported by BvD. Reconciliation of the two sets of data is impeded by some of the opaque criteria used by the Fed in compiling its data.10 9  The BvD database amalgamates earlier Bankscope data with Orbis and BankFocus data. 10  One of the criteria for the inclusion of subsidiaries in the FED/NIC lists is a definition of control under Regulation Y, which is essentially a 25 percent control. However, additional entities that meet FR Y-10/10F “reportability criteria” are included, as well as entities for which the relationship is “of interest to the Federal Reserve.” These latter two conditions make it challenging to fully understand how the FED/NIC lists are built and how they compare to the lists provided by other datasets such as BvD. The FED/NIC dataset offers, however, a key benefit relative to other sources, because it appears to be the only

Table 4.2  Geographical Diversification of G-SIBs and Subsidiaries in OFCs, 2018 vs. 2013 (G-SIBs Ranked by Number of Countries in 2018)

G-SIBs

Number of countries (October 2018)

Number of countries (May 2013)

% of domestic subsidiaries (October 2018)

% of foreign subsidiaries (October 2018)

% of domestic subsidiaries (May 2013)

% of foreign subsidiaries (May 2013)

Number of subsidiaries in OFCs (October 2018)

% of subsidiaries in OFCs (October 2018)

% of subsidiaries in OFCs (May 2013)

1

Citigroup

85

95

58%

42%

39%

61%

354

18%

10%

2

Société Générale

78

74

45%

55%

47%

53%

120

12%

8%

3

BNP Paribas

69

88

19%

81%

17%

83%

123

7%

8%

4

HSBC

68

69

14%

86%

21%

79%

524

27%

27%

BPCE

68

70

71%

29%

65%

35%

97

5%

6%

Goldman Sachs

66

24

49%

51%

29%

71%

1124

29%

11%

7

Deutsche Bank

58

61

21%

79%

24%

76%

420

28%

27%

8

JPMorgan Chase

57

57

70%

30%

45%

55%

389

14%

10%

9

Standard Chartered

57

32

6%

94%

42%

58%

280

35%

8%

10

Morgan Stanley

53

45

62%

38%

41%

59%

681

20%

20%

11

Crédit Agricole

51

59

61%

39%

55%

45%

156

11%

9%

12

Bank of America

48

48

81%

19%

72%

28%

223

8%

10%

13

UBS

43

45

5%

95%

17%

83%

29

8%

8%

14

Barclays

42

58

35%

65%

37%

63%

176

19%

21%

15

Unicredit

42

67

28%

72%

41%

59%

35

3%

3%

16

Royal Bank of Scotland

40

36

47%

53%

40%

60%

110

15%

13%

17

Santander

39

37

24%

76%

25%

75%

65

6%

7%

18

Credit Suisse

35

37

6%

94%

10%

90%

81

14%

21% (continued)

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5 6

Table 4.2  Continued Number of countries (May 2013)

% of domestic subsidiaries (October 2018)

% of foreign subsidiaries (October 2018)

% of domestic subsidiaries (May 2013)

% of foreign subsidiaries (May 2013)

Number of subsidiaries in OFCs (October 2018)

% of subsidiaries in OFCs (October 2018)

% of subsidiaries in OFCs (May 2013)

19

Wells Fargo

32

27

92%

8%

93%

7%

113

5%

4%

20

ICBC

31

16

30%

70%

44%

56%

113

42%

47%

21

ING Groep

31

44

30%

70%

32%

68%

21

7%

4%

22

BBVA

30

29

26%

74%

30%

70%

11

2%

4%

23

Bank of New York Mellon

30

22

52%

48%

35%

65%

220

18%

17%

24

Sumitomo Mitsui

29

20

34%

66%

59%

41%

45

23%

18%

25

Bank of China

28

16

45%

55%

72%

28%

100

50%

15%

26

Royal Bank of Canada

27

29

19%

81%

18%

82%

52

17%

25%

27

Nordea

23

19

25%

75%

5%

95%

12

6%

4%

28

Mitsubishi UFJ

22

21

21%

79%

46%

54%

17

7%

4%

29

Mizuho

22

16

45%

55%

62%

38%

32

24%

7%

30

State Street Corporation

21

14

46%

54%

26%

74%

84

29%

28%

31

China Construction Bank

16

12

54%

46%

42%

58%

96

38%

63%

32

Agricultural Bank of China

6

4

76%

24%

57%

43%

4

14%

21%

Average

45

41

41%

59%

40%

60%

196

18%

15%

Median

42

37

40%

60%

41%

60%

110

15%

10%

Range

64

91

87%

87%

88%

88%

1,113

48%

60%

Source: Authors’ calculations on Bankscope (for 2013) and BankFocus (for 2018) data. Number of countries indicates the number of jurisdictions where a G-SIB has at least one ultimately owned subsidiary. The list of OFCs includes the 42 jurisdictions identified by the Financial Stability Forum in 2000 (FSF, 2000). Data on subsidiaries for BCPE SA in 2018 as of May. Data on subsidiaries for Agricultural Bank of China, China Construction Bank and Royal Bank of Canada as of July 2015 instead of May 2013.

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G-SIBs

Number of countries (October 2018)

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Corporate Complexity and Systemic Risk   107

Table 4.3  Breakdown by Industry of Subsidiaries of G-SIBs, October 2018 (in bold) and May 2013

G-SIBs

Banks

Insurance companies

Mutual and pension funds/ nominees/ trusts/trustees

Other financial Non-financial subsidiaries subsidiaries

Total

5

1

2

2

19

29

3

1

1

5

4

14

17%

3%

7%

7%

66%

100%

21%

7%

7%

36%

29%

100%

206

26

704

458

1434

2828

72

17

584

322

915

1910

7%

1%

25%

16%

51%

100%

4%

1%

31%

17%

48%

100%

41

5

17

62

74

199

23

3

27

13

50

116

21%

3%

9%

31%

37%

100%

20%

3%

23%

11%

43%

100%

Bank of New York Mellon

60

6

782

144

239

1231

17

0

120

67

75

279

% by industry

5%

0.5%

64%

12%

19%

100%

6%

0%

43%

24%

27%

100%

36

5

151

237

506

935

Agricultural Bank of China % by industry Bank of America % by industry Bank of China % by industry

Barclays % by industry BBVA % by industry BNP Paribas % by industry BPCE SA

54

16

465

380

824

1739

4%

1%

16%

25%

54%

100%

3%

1%

27%

22%

47%

100%

21

29

238

58

156

502

36

16

59

144

160

415

4%

6%

47%

12%

31%

100%

9%

4%

14%

35%

39%

100%

114

55

187

275

1163

1794

103

68

323

760

1338

2592

6%

3%

10%

15%

65%

100%

4%

3%

12%

29%

52%

100%

101

21

198

251

1277

1848

108

56

219

556

509

1448 (continued)

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108   The Theory of Banking

Table 4.3  Continued

G-SIBs % by industry China Construction Bank % by industry Citigroup % by industry Crédit Agricole SA % by industry Credit Suisse % by industry Deutsche Bank % by industry Goldman Sachs % by industry HSBC

Banks

Insurance companies

Mutual and pension funds/ nominees/ trusts/trustees

Other financial subsidiaries

Non-financial subsidiaries

Total

5%

1%

11%

14%

69%

100%

7%

4%

15%

38%

35%

100%

17

1

25

49

163

255

11

1

12

21

44

89

7%

0.4%

10%

19%

64%

100%

12%

1%

13%

24%

49%

100%

125

30

528

452

874

2009

111

41

456

650

1039

2297

6%

1%

26%

22%

44%

100%

5%

2%

20%

28%

45%

100%

94

29

252

171

923

1469

73

32

132

434

584

1255

6%

2%

17%

12%

63%

100%

6%

3%

11%

35%

47%

100%

34

13

144

107

263

561

30

4

89

52

67

242

6%

2%

26%

19%

47%

100%

12%

2%

37%

21%

28%

100%

78

8

348

349

716

1499

68

8

541

618

889

2124

5%

1%

23%

23%

48%

100%

3%

0.4%

25%

29%

42%

100%

18

29

1264

415

2131

3857

15

10

74

121

200

420

0.5%

1%

33%

11%

55%

100%

4%

2%

18%

29%

48%

100%

116

20

278

343

1165

1922

89

37

309

298

832

1565

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Corporate Complexity and Systemic Risk   109

6%

1%

14%

18%

61%

100%

6%

2%

20%

19%

53%

100%

31 19

1 2

14 7

23 5

197 3

266 36

12%

0.4%

5%

9%

74%

100%

53%

6%

19%

14%

8%

100%

20

8

34

88

160

310

41

43

130

253

297

764

% by industry

6%

3%

11%

28%

52%

100%

5%

6%

17%

33%

39%

100%

JPMorgan Chase

109

5

791

361

1437

2703

54

13

305

205

518

1095

4%

0.2%

29%

13%

53%

100%

5%

1%

28%

19%

47%

100%

53

1

60

65

57

236

27

0

22

30

33

112

22%

0.4%

25%

28%

24%

100%

24%

0%

20%

27%

29%

100%

29

0

32

28

43

132

23

3

26

22

29

103

22%

0%

24%

21%

33%

100%

22%

3%

25%

21%

28%

100%

20

8

934

483

1994

3439

19

12

245

236

799

1311

1%

0.2%

27%

14%

58%

100%

1%

1%

19%

18%

61%

100%

8

7

22

26

153

216

13

5

29

117

56

220

4%

3%

10%

12%

71%

100%

6%

2%

13%

53%

25%

100%

56

9

50

99

86

300

37

10

60

125

73

305

19%

3%

17%

33%

29%

100%

12%

3%

20%

41%

24%

100%

% by industry ICBC % by industry ING Groep

% by industry Mitsubishi UFJ % by industry Mizuho % by industry Morgan Stanley % by industry Nordea % by industry Royal Bank of Canada % by industry

(continued)

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110   The Theory of Banking

Table 4.3  Continued

G-SIBs Royal Bank of Scotland % by industry Santander % by industry Société Générale % by industry Standard Chartered % by industry State Street Corporation % by industry Sumitomo Mitsui % by industry UBS % by industry

Banks

Insurance companies

Mutual and pension funds/ nominees/ trusts/trustees

Other financial subsidiaries

Non-financial subsidiaries

Total

43

8

121

194

362

728

33

5

162

206

393

799

6%

1%

17%

27%

50%

100%

4%

1%

20%

26%

49%

100%

104

13

229

223

455

1024

64

13

102

197

229

605

10%

1%

22%

22%

44%

100%

11%

2%

17%

33%

38%

100%

111

17

124

245

519

1016

95

20

97

405

296

913

11%

2%

12%

24%

51%

100%

10%

2%

11%

44%

32%

100%

34

5

69

78

622

808

28

2

27

41

20

118

4%

1%

9%

10%

77%

100%

24%

2%

23%

35%

17%

100%

15

1

107

70

100

293

6

1

61

45

42

155

5%

0.3%

37%

24%

34%

100%

4%

1%

39%

29%

27%

100%

24

0

28

36

111

199

22

0

32

51

60

165

12%

0%

14%

18%

56%

100%

13%

0%

19%

31%

36%

100%

31

4

106

54

162

357

28

4

108

152

166

458

9%

1%

30%

15%

45%

100%

6%

1%

24%

33%

36%

100%

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Corporate Complexity and Systemic Risk   111

Unicredit % by industry Wells Fargo % by industry Total % by industry

54

4

93

111

1060

1322

57

6

193

751

1209

2216

4%

0.3%

7%

8%

80%

100%

3%

0.3%

9%

34%

55%

100%

60

15

493

549

1034

2151

19

42

323

356

809

1549

3%

1%

23%

26%

48%

100%

1%

3%

21%

23%

52%

100%

1868

384

8425

6106

19655

36438

1398

491

5340

7638

12562

27429

5%

1%

23%

17%

54%

100%

5%

2%

19%

28%

46%

100%

Note: The sum of the percentages on the share of subsidiaries by industry does not always equal precisely 100% due to rounding. Source: Bankscope (for 2013 data) and BankFocus (for 2018 data). Private equity and venture capital subsidiaries and hedge funds are included among “other financial subsidiaries.” Foundations and research institutes are included in “Non-financial subsidiaries.” Data on subsidiaries for BCPE SA in 2018 as of May. Data on subsidiaries for Agricultural Bank of China, China Construction Bank, and Royal Bank of Canada as of July 2015 instead of May 2013.

The FED/NIC data are focused on US banks—and US activities of non-US banks. These data provide an alternative source, based on a consistent methodology, for analysis of the corporate structures of the eight US G-SIBs. This is particularly useful because some data reported by BvD for most US G-SIBs exhibit an abrupt increase which may be attributable to a change in sources of data rather than a meaningful change in the number of controlled subsidiaries. Table 4.4 reports the number of subsidiaries of the eight US G-SIBs from 2002 to 2018 (October) based on FED/NIC data. Although the average number of controlled subsidiaries remains high (1,173), it is heavily influenced by the high number of controlled subsidiaries at Goldman Sachs and Morgan Stanley. A clear reduction in the average number of subsidiaries is observable after it peaked in 2009 at 2,333. A particularly strong decrease in complexity occurs after 2012, with the average number of subsidiaries progressively decreasing. By October 2018, the number had fallen almost by half relative to December 2012. The Living Will process, including a focus on the rationalization of legal entities to enhance resolvability, is likely to have played a crucial role in providing incentives for this reduction in the number of controlled subsidiaries. database that provides historical data on corporate structures (which can be downloaded at any point in time). Unfortunately, the FED/NIC dataset covers only US banks and the US operations of non-US banks and it does not report the financials of subsidiaries.

US G-SIBs

October December December December December December December December December December December December December December December December December 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002

1 Morgan Stanley

2,429

2,436

2,769

2,918

3,048

3,151

3,330

3,444

3,693

3,770

3,507

.

.

.

.

.

.

2 Goldman Sachs

2,308

2,686

2,827

2,952

3,443

3,713

3,857

3,761

3,640

3,517

3,346

.

.

.

.

.

.

3 Bank of America

1,362

1,371

1,426

1,584

1,738

1,814

2,000

2,140

2,341

2,780

1,559

1,405

1,691

1,549

1,601

1,048

1,043

4 Citigroup

981

1,004

1,067

1,196

1,304

1,382

1,731

1,705

1,747

1,821

1,863

1,969

1,528

1,441

1,491

1,438

1,476

5 JPMorgan Chase

926

956

1,297

1,900

2,525

3,664

3,761

3,667

4,655

4,260

4,458

2,892

2,971

2,972

2,930

1,302

1,255

6 Bank of New York Mellon

739

775

815

861

893

904

919

912

754

674

637

598

.

.

.

.

.

7 Wells Fargo

445

565

752

1,363

1,327

1,450

1,454

1,409

1,543

1,625

1,712

613

612

677

676

662

635

8 State Street Corporation

197

203

195

208

226

241

247

248

238

215

287

283

215

227

214

204

182

1,173

1,250

1,394

1,623

1,813

2,040

2,162

2,161

2,326

2,333

2,171

1,293

1,403

1,373

1,382

931

918

Average Median Range

954

980

1,182

1,474

1,533

1,632

1,866

1,923

2,044

2,301

1,788

1,009

1,528

1,441

1,491

1,048

1,043

2,232

2,483

2,632

2,744

3,217

3,472

3,610

3,513

4,417

4,045

4,171

2,609

2,756

2,745

2,716

1,234

1,294

Source: Federal Reserve/National Information Center.

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Table 4.4  Number of Subsidiaries of US G-SIBs According to the FED/NIC Data Set, 2002–18

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Corporate Complexity and Systemic Risk   113 Nonetheless, differences between BvD and FED/NIC data, which cannot be reconciled based on publicly available information, present a substantial obstacle to drawing meaningful conclusions about trends in the number of controlled subsidiaries. Even so, no other official entity discloses data comparable in quantity and granularity to the FED. Quite possibly, internal sources maintained by non-US regulatory authorities may also differ from BvD data, but disclosure standards outside the US are so weak that the question cannot be posed.

4.4  What Drives the Corporate Complexity of G-SIBs? The banks’ decisions regarding their corporate structure are affected by external incentives and constraints, such as regulation, taxation, accounting rules, and disclosure requirements, but also by internal factors, as efforts to minimize asymmetric information costs and the legacy of mergers and acquisitions (M&A).11 Regulation has been an important driver of the proliferation of subsidiaries within G-SIBs. In some countries, the primary regulator may require a G-SIB to create separate legal entities to conduct certain kinds of business. Historically, requirements for corporate separateness have been a central feature of US bank regulation (Herring and Santomero, 1990), from the Edge Act in 1919 through the Glass–Steagall Act in 1933 to the Gramm–Leach–Bliley Act of 1999 and the Intermediate Holding Company Rule of 2014. In addition, regulatory authorities in host countries often require foreign financial institutions to form separate, locally chartered subsidiaries to conduct certain kinds of business. They take the view that host country authorities can supervise the safety and soundness and conduct of business more effectively and better protect financial stability within their borders. The Reserve Bank of New Zealand has been the most outspoken advocate of this approach, requiring not only that foreign-owned institutions establish a local subsidiary, but also that the subsidiary be insulated from the parent by a number of operational and financial firewalls. Taxation provides additional incentives to proliferate corporate subsidiaries, particularly in tax havens. Although tax policy is not generally considered to be part of the regulatory framework, its impact on corporate structure is profound and ubiquitous. The deductibility of interest payments, but not dividends, has led to a preference for debt finance relative to equity, as with most corporations, and has created an incentive to use affiliates to raise debt. Furthermore, institutional innovations are designed to capture the tax benefits of debt while satisfying regulatory capital requirements for equity.12 Because the authorities often use the tax code to encourage particular kinds of activities, this may also provide incentives for G-SIBs to establish separate entities to obtain tax 11  This section is largely based on Carmassi and Herring (2016a). For a more complete discussion see chapter 4 in the second edition of this Handbook. 12 One example is the proliferation of vehicles for issuing Trust Preferred Securities (TruPS) (Goodman, Lucas, and Fabozzi, 2007).

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114   The Theory of Banking benefits. Banks frequently establish separate entities to qualify for tax subsidies targeted at special activities such as real estate investment, leasing, or energy conservation. The ability to establish subsidiaries in foreign tax havens may facilitate the use of excess foreign tax credits and defer taxes on certain kinds of income more or less indefinitely. In addition, particular locations may be preferred so that a G-SIB can take advantage of special tax-sparing treaties with specific countries in which it conducts business. Moreover, the establishment of an intermediate-level holding company in such jurisdictions may reduce the cost of transferring funds from one foreign entity to another by avoiding withholding and transfer taxes. G-SIBs may also establish subsidiaries in tax havens for the benefit of foreign customers who would otherwise be subject to withholding taxes (these customers may also value the secrecy that tax havens also tend to provide). This web of tax incentives is even more complex than the morass of regulatory constraints, and so it is virtually impossible to measure the extent of their impact on the complexity of the corporate structure of G-SIBs. The count of the number of subsidiaries in tax havens can only catch part of the magnitude of the impact. Nonetheless, as shown in Table 4.2 in the previous section, G-SIBs locate a remarkable proportion of their subsidiaries in OFCs, which tend to be tax havens as well. Despite years of effort to harmonize accounting principles and practices across countries, substantial differences remain. A G-SIB may sometimes be able to exploit those differences by establishing a subsidiary in a strategic location or by creating a separate entity to escape accounting consolidation requirements or disclosure laws. Regulators rely on accounting measures to set capital and liquidity requirements and so often the underlying motive for the creation of a more elaborate legal structure is not only to achieve a more favorable accounting treatment for a particular activity or portfolio of assets, but also to lighten the burden of complying with the costs of regulation. The growth in special purpose vehicles (SPVs) before the crisis illustrates the distortions that can occur and the implications for corporate complexity. In addition to TruPS (mentioned in footnote 12), another example of the use of a separate entity to reduce taxes is provided by Hume (2011). He reported that one G-SIB had established a separate legal entity in the Cayman Islands to offload billions of troubled mortgage-backed securities. This new entity qualified as a separate company because the equity, equal to 3.5 percent of the assets, was placed with external investors, which qualified the new entity for off-balance-sheet treatment under accounting regulations. Nonetheless, the G-SIB guaranteed the external shareholders against loss and provided a loan to finance the remaining 96.5 percent of the assets. The creation of this separate legal entity (which, by design, would not be counted as a controlled subsidiary of the parent) allowed the parent to avoid establishing a loan loss reserve against the portfolio of assets—which would have been required if they had remained on the balance sheet—and an increase in regulatory capital requirements. This example illustrates the difficulty in understanding a G-SIB’s span of control solely from data about ownership shares. Although accountants and regulators have revised their rules to close such loopholes after the crisis, similar opportunities and incentives undoubtedly remain. Although external incentives are of fundamental importance, banks would have strong reasons to introduce a certain amount of legal separateness in their corporate

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Corporate Complexity and Systemic Risk   115 structures even in the absence of regulatory requirements and tax and regulatory incentives. Even if regulatory restrictions and incentives, tax distortions and accounting loopholes were eliminated, G-SIBs are likely to prefer to establish a number of subsidiaries rather than conduct all of their business through a single legal entity. The corporate finance literature creates a presumption that many of these subsidiaries are established to reduce frictions in markets (both external and internal). Herring and Carmassi (2010, 2014) identified a number of ways that corporate separateness could diminish such frictions including: reducing asymmetric information costs between shareholders and creditors; reducing asymmetric information costs and agency problems between external shareholders and managers; mitigating customer concerns regarding potential conflicts of interest; reducing the costs of financial distress by protecting the group from a risky subsidiary and/or protecting a subsidiary from risks in the rest of the group; and the legacy of mergers and acquisitions. The impact of mergers and acquisitions deserves special consideration because many G-SIBs have grown through a series of substantial mergers and acquisitions, some of them exceptionally large13 (Herring and Carmassi,  2010, 2014; Carmassi and Herring, 2016a). Mergers and acquisitions are likely to have a significant impact on the complexity of the corporate structure of G-SIBs, as confirmed by the empirical analysis by Carmassi and Herring (2016a) who found a significant and persisting impact of large M&A deals on the corporate complexity of G-SIBs based on time series from 2002 to 2013. Previous studies identified a positive (but less than proportional) correlation between bank size and the number of subsidiaries (e.g., Avraham, Selvaggi, and Vickery, 2012; Cetorelli and Goldberg, 2014; Laeven, Ratnovski, and Tong, 2014); Carmassi and Herring (2016a) found that this correlation would lose significance when time effects are considered and that only the effect of M&A transactions would remain significant. The restructuring of corporate legal structures is likely to involve substantial transactions costs and may require considerable attention from top-level management, and so the corporate structure of the acquired institution is often left largely intact. Relative to a firm of equal size that has grown organically, an acquisitive G-SIB is likely to have many more subsidiaries, if only because of the transactions costs in closing or consolidating the acquired subsidiaries. In addition to the avoidance of transactions costs in consolidating the subsidiaries of the acquired firm, the surviving G-SIB may choose to retain a considerable amount of corporate separateness in the target firm with the hope that preserving the brand might help to retain the reputational capital of the target firm and to facilitate acceptance of the merger. As Dermine (2006) noted, by committing to keep a local structure and staff in place, local shareholders and the board of directors of the target may be reassured about the future of the target firm. Also, the host country regulatory authorities sometimes require that the acquiring bank maintain the target bank as a separate, locally chartered corporation. Nonetheless, even when a G-SIB wants to reduce its corporate complexity, it may take a significant amount of time to do so because of a wide range of frictions such as 13  The history of JPMorgan Chase provides a good example of how mergers may increase corporate complexity.

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116   The Theory of Banking outstanding litigation involving particular subsidiaries. Moreover, rationalization of corporate structure requires resources and management attention at a time when the main goal may be simply continuing operations and trying to meet profitability objectives. Given the low costs of creating some kinds of additional legal entities it may sometimes be easier to create a new legal entity than to identify and make use of an existing one. As a result, some of the proliferation of subsidiaries may simply be attributable to lackadaisical housekeeping of corporate structures. To the extent that increased complexity may have been the result of inadequate attention to the growing complexity of corporate structures, the Living Will process should be effective in encouraging banking groups to simplify and rationalize their corporate structures. Finally, given the challenges that a complex corporate structure poses for timely ­resolution, it is certainly possible that some banks find it useful to develop complex corporate structures to ensure that they are considered too complex to fail. The perception of this status might be expected to give them an advantage in funding costs. The described impediments to consolidating subsidiaries once the merger has been completed make it likely that mergers will have a lasting impact on the degree of complexity of financial institutions. In addition, and more broadly, given changes in regulations and tax policies—and the tendency to grandfather some institutions when taxes or regulations are changed—the current structures of G-SIBs must be regarded as path dependent. These structures reflect a broad range of external and internal incentives that may have changed over time (and across countries). The complicated corporate structures tend to accrue and a number of frictions may impede corporate simplification—especially in the absence of regulatory pressures to do so. As shown in section 4.3 and Table 4.3, a specific source of corporate complexity of G-SIBs is the very high number of non-financial subsidiaries. This factor was identified by Herring and Carmassi (2010) and subsequently confirmed by other studies (Cetorelli and Goldberg, 2014; Herring and Carmassi, 2014; Carmassi and Herring, 2015). As discussed in Carmassi and Herring (2015), non-financial subsidiaries include a wide variety of businesses, ranging from hotels and restaurants to energy and aviation. Several rationales can be identified for the ownership by G-SIBs of such a relevant number of non-financial subsidiaries. First, a G-SIB may have acquired a non-financial corporation with several subsidiaries: for example, Bank of China acquired Singapore Aircraft Leasing Enterprise Pte. Ltd., an aircraft operating leasing company, in December 2006, and renamed it BOC Aviation Pte. Ltd., which in 2016 was renamed BOC Aviation Limited. Our list of subsidiaries of Bank of China reports 40 subsidiaries of BOC Aviation being ultimately owned subsidiaries of Bank of China. These subsidiaries account for about 20 percent of the total subsidiaries of Bank of China and are located in many different jurisdictions worldwide, including among others the US, UK, France, Ireland, Hong Kong, Cayman Islands, and Bermuda. As a further example, in May 2017 Goldman Sachs acquired, via its Goldman Sachs Merchant Banking Division, the control of Caldic, a Dutch full-service distributor and manufacturer for food, health and industrial markets. Our list of subsidiaries for Goldman Sachs include fifty-two Caldic subsidiaries around the globe.

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Corporate Complexity and Systemic Risk   117 Other non-financial subsidiaries could be related to attempts to mitigate litigation risk. For example, when a bank forecloses on a property, say a hotel, the latter may be decomposed into multiple separate entities (e.g., one for the garage, one for the swimming pool, etc.) to prevent a lawsuit against one entity from jeopardizing the viability of other parts of the hotel complex or creating a financial burden for the parent (Carmassi and Herring,  2015). These types of non-financial subsidiaries are unlikely to impede an orderly resolution, but current meager disclosures make it impossible to know. Beneficial ownership may also account for many of the non-financial subsidiaries in the BvD database. This kind of subsidiary will be reported by BvD as an ultimately owned subsidiary, that is, with an ownership path of at least 50.01% in all the nodes of the ownership chain, even though the subsidiary is held for the benefit of a typically undisclosed client. While the G-SIB is the owner of record, it does not control such subsidiaries. Unfortunately, there is no systematic way to exclude these beneficially owned subsidiaries from the BvD database. Several examples of this kind of non-financial subsidiary may be found. For example, Servizio Italia Società Fiduciaria e di Servizi per Azioni is an Italian subsidiary owned by BNP Paribas. It is a fiduciary based in Rome, which owns 528 subsidiaries, 511 of which conduct a wide range of non-financial businesses.14 Similarly, Unicredit owns a Milan-based fiduciary, Cordusio Società Fiduciaria per Azioni, which owns 388 entities, of which 374 are categorized as nonfinancial. Data for Standard Chartered provide yet another example: SCTS Capital Pte. Ltd, a Singapore-based subsidiary of Standard Chartered offering fiduciary services, owns 419 entities, of which 394 are classified as non-financial.15 The subsidiaries list for HSBC provides an example with an even larger number of non-financial subsidiaries: HSBC Group Nominees UK Limited is a London-based subsidiary of HSBC, which owns 1,051 entities, 697 of which are classified as non-financial. The ownership path can be extremely intricate. For example, as many as thirteen entities are in the ownership chain between some of these subsidiaries and HSBC Holdings Plc. These anecdotes shed some light on the variety of non-financial subsidiaries of G-SIBs, but it is very difficult to track this information in a comprehensive and consistent way across G-SIBs. We lack systematic evidence about what non-financial subsidiaries do and whether they would impede an orderly resolution. Subsidiaries that represent beneficial ownership claims are probably irrelevant to an orderly resolution, but given current disclosure practices it is impossible to make a systematic analysis of the issue. Better transparency would help identify all the entities of this type and, if convincing explanations are provided about why they are non-material in a resolution, they should be excluded in a systematic and consistent way from the analysis of the resolvability of G-SIBs.16 14  These entities are active in a very broad range of business, including real estate, healthcare, agriculture, textiles, grocery stores, wine wholesalers, energy corporations, and jewelry stores. 15  The inclusion of this entity in the list of subsidiaries of Standard Chartered may partially explain the sharp rise in Standard Chartered’s number of controlled subsidiaries from 2013 to 2018. 16  Presumably the resolution authorities are making the appropriate adjustments in their analysis, but in the interests of transparency, and to facilitate public understanding of the resolution process, this information should be publicly disclosed.

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118   The Theory of Banking Finally, material entities that provide key critical non-financial services (e.g., IT and technological services) within each G-SIB represent another category of non-financial subsidiaries, which has grown as a result of regulatory pressures to ensure the provision of shared services during a resolution. These entities are highly relevant from a resolution perspective, but with the exception of information included in the public sections of US Living Wills, current disclosures do not enable us to quantify their share of non-financial subsidiaries systematically. In conclusion, a large number of external and internal factors may explain the high number of controlled subsidiaries of most G-SIBs. Unfortunately, current disclosures impede a deeper analysis of the most important factors that motivate G-SIBs to form new subsidiaries or continue existing subsidiaries. Undoubtedly, however, a considerable amount of this corporate complexity is attributable to regulation and taxation, policies that are generally set without regard to their impact on the opacity of corporate structures.

4.5  Policies to Enhance the Resolvability of G-SIBs The G20 laid out a two-pronged reform agenda. First, the G20 mandated a set of policies designed to reduce the probability that any G-SIB might become insolvent. These included the requirement that G-SIBs maintain more and higher quality capital, increased risk weights on some positions and additional incentives to shift most derivatives trading to public exchanges, capital surcharges for G-SIBs, the introduction of a Total Loss-Absorbing Capacity requirement, the establishment of a leverage ratio constraint, the introduction of liquidity requirements, heightened prudential supervision including oversight of contingent recovery plans, and the implementation of stress tests to ensure that the capital resources would be adequate even under highly stressful conditions.17 The G20 implicitly recognized that it was neither desirable, nor feasible, to set prudential standards so high that a G-SIB would never become insolvent. Thus, the second prong of the reform agenda focused on resolvability, including resolution plans, to ensure that every G-SIB would be safe to fail (Huertas, 2014). The FSB was assigned principal responsibility for developing a resolution infrastructure that would eliminate the obstacles to an orderly resolution that were evident in the collapse of LB and provide a way of ensuring the continuity of systemically important functions, while allocating losses to shareholders and creditors in a way that respects payment priorities in bankruptcy, without reliance on public resources. In response to this mandate from the G20, 17  See Herring and Carmassi (2014) and Carmassi and Herring (2015) for additional discussion of these initiatives and associated references. This section will focus on the second prong of the reform agenda, that is, the measures to establish credible resolution policies.

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Corporate Complexity and Systemic Risk   119 the KA were adopted in 2011 (FSB, 2011b).18 The GFC revealed that no country had established an effective resolution regime appropriate for G-SIBs and so KA set out goals that would require major reform efforts including new legislation in all jurisdictions. The KA require that each jurisdiction designate a resolution authority (or coordinated multiple resolution authorities) that should ensure the continuity of systemically important financial services and payment, clearing and settlement functions; protect insured depositors and investors with segregated assets; respect the hierarchy of creditors;19 avoid unnecessary destruction of value; and seek to minimize resolution costs in the home and host jurisdictions. Resolution should be initiated when “a firm is no longer viable or likely to be no longer viable, and has no reasonable prospect of becoming so.”20 The resolution authority should have sweeping powers that no resolution authority had when the KA were adopted.21 These included powers to: remove and replace senior management and directors; appoint an administrator to take control and manage the firm in resolution; operate and resolve the firm, including the ability to terminate contracts, continue to assign contracts, purchase or sell assets, write down debt and take other actions to restructure or wind down the firm’s operations; ensure continuity of essential services and functions; override the rights of shareholders of the firm in resolution, including requirements for approval of restructuring measures; establish a temporary bridge institution to take over and continue operating critical functions and viable operations of the firm in resolution; establish a separate asset management vehicle to manage and run-down non-performing loans or difficult-to-value assets; carry out bail-in of creditors of the failed institution to achieve continuity of essential functions by recapitalizing a newly established or bridge entity; temporarily stay the exercise of early termination rights that may be triggered when the firm enters resolution; impose a moratorium on payments to unsecured creditors and some specified customers, and a stay on actions to attach assets, while protecting the enforcement of eligible netting and collateral agreements; and effect the closure and orderly liquidation of the whole or part of the failing firm with timely payout of insured deposits22 and prompt (for example, within seven days) access to transaction accounts and to segregated client funds). Furthermore, the resolution authority should have: the authority to enter into 18  The KA were adopted at a meeting of the FSB in October 2011 and endorsed by the G20 Heads of State and Government at the Cannes Summit in November 2011. The KA are intended to apply to all systemically important financial institutions, but this discussion focuses only on G-SIBs, the firms which have received the most attention. 19  In practice, this means that creditors should have a right to compensation where they do not receive at least as much as they would have received in a liquidation of the firm under the applicable insolvency regime. 20  This concept is remarkably vague and probably reflects success in achieving agreement through the avoidance of excessively clear language. But it may lead to markedly different points of intervention if each jurisdiction develops its own interpretation of when intervention is necessary. 21 The following selective summary of resolution powers, funding of firms in resolution, and cross-border cooperation is based on FSB (2011b, pp. 5–15). 22  Although the FDIC has long followed the practice of enabling access to insured deposits the next business day after intervention, for authorities in most other jurisdictions assuring access within seven days was a stretch goal. This, of course, undermines the role of deposit insurance in preventing runs.

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120   The Theory of Banking agreements with resolution authorities in other jurisdictions; the obligation to take into account the impact on the group as a whole and on financial stability in other affected jurisdictions; and the obligation to make efforts to avoid actions that could reasonably be expected to trigger instability elsewhere in the group or in the financial system.23 The funding of firms in resolution received special emphasis to make clear that the public authorities should not bail out creditors as a means of resolving firms. If the authorities, nonetheless, provide temporary funding to maintain essential functions, any losses incurred should be recovered from shareholders and unsecured creditors or, if necessary, from the broader financial system in an ex post assessment. Any provision of temporary funds by the authorities should be subject to strict conditions that minimize moral hazard. The KA acknowledged that some countries may choose to have the power to place a faltering firm under temporary public ownership and control to continue critical operations while seeking a permanent, private sector solution. But the KA caution this option should be deployed only as a last resort and any losses must be recovered from the firm’s shareholders and unsecured creditors or, if necessary, in an ex post assessment on the broader financial system. In 2015, the FSB (2015) instituted a Total Loss Absorbing Capacity (TLAC) standard to increase the loss-absorbing capacity and facilitate the recapitalization of a G-SIB in resolution from its own pre-resolution capital structure. (Moreover, these additional resources may also ease the challenge of funding the group in resolution.) The TLAC standard defines a minimum requirement for the instruments and liabilities that should be readily available for bail-in within a G-SIB resolution. Cross-border cooperation was notably absent in the LB resolution and so the KA placed special emphasis on the importance of building a framework to facilitate and sustain cooperation. The KA specify that the resolution authority should be given a statutory mandate to achieve a cooperative solution with foreign resolution authorities whenever possible. Legislation and regulation should not contain provisions that trigger automatic action in response to official intervention or the initiation of resolution proceedings in another jurisdiction, and national laws and regulations should not discriminate against creditors on the basis of their nationality, the location of their claims or the jurisdiction where the claims are payable. Nonetheless, the KA provide that jurisdictions may reserve the right to take discretionary national action to protect domestic stability if international cooperation and information sharing prove inadequate. Along the same lines, the resolution authority should have resolution powers over local branches of foreign firms and the capacity to use these powers to support a resolution carried out by a foreign home authority or, in exceptional cases, to take measures on its own initiative if the home jurisdiction does not take adequate account of the need to protect financial stability in the local jurisdiction. The possibility that a local authority may choose to ring-fence a foreign firm’s assets to  satisfy local creditors has led market participants to doubt that a cooperative

23  Of course, this sort of consideration was notably absent in the US resolution of Lehman Brothers.

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Corporate Complexity and Systemic Risk   121 cross-border solution will be achieved in a crisis.24 The KA stop short of prohibiting ring-fencing, but attempt to discourage such behavior. This may be the best that could be achieved in the absence of any supra-national entity that could compel countries to cooperate, but it may not be enough to reassure markets in times of stress. In order to encourage cross-border cooperation, the KA require that home and key host authorities maintain a crisis management group (CMG) for each G-SIB with the objective of enhancing preparedness and facilitating the management and resolution of any cross-border crisis involving the G-SIB. The CMGs, which include supervisory authorities, central banks and ministries of finance, should review, at least annually, progress in coordination and information sharing within the CMGs, recovery and resolution plans for the G-SIB under institution-specific cooperation agreements and the resolvability of the G-SIB. Regular reports should be submitted to the FSB and the FSB Peer Review Council. The institution-specific cooperation agreements should: establish the objectives and processes for cooperation with the CMGs; define the roles and responsibilities of the home and host authorities pre-crisis and during a crisis; set up processes for information sharing before and during a crisis; develop processes for coordination in the development of Recovery and Resolution Plans for the G-SIB, including the parent and significant branches and subsidiaries; and set out procedures for timely information-sharing and consultation procedures between home and host countries. To boost confidence in the effectiveness of CMGs, the KA state the existence of such agreements should be made public. Jurisdictions are also permitted to publish the broad structure of such agreements if all parties agree. The resolution authority, in coordination with the CMG, is responsible for making an ongoing assessment of the resolvability of each G-SIB.25 This requires an evaluation of the feasibility of resolution strategies planned for each G-SIB and their credibility in light of the likely impact on the financial system and real economy if the resolution strategy is implemented. The resolution authority should assess: the extent to which critical financial services, payment, and clearing and settlement functions can be performed; the nature and extent of intra-group exposures and their impact on resolution if they need to be unwound; the capacity of the group to deliver sufficiently detailed, accurate and timely information to facilitate resolution;26 and the robustness of cross-border agreements within the CMG. The KA require that the resolution or supervisory authorities should have the power to improve a group’s resolvability by requiring changes in a G-SIB’s business practices, structure or organization to reduce the complexity and costliness of resolution. In particular, the authorities should evaluate whether to require a G-SIB’s functions be 24  See Carmassi and Herring (2016b) for an extensive discussion of ring-fencing issues. 25  The KA regard a G-SIB as “resolvable” if it is feasible and credible for the resolution authorities to resolve it in a way that protects systemically important functions without severe systemic disruption and without exposing taxpayers to loss. An evaluation of the resolvability of a G-SIB is a judgment about the extent to which it can be regarded as resolvable. 26  Virtually no relevant information was available when LB applied for bankruptcy and so the authorities particularly emphasized this requirement.

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122   The Theory of Banking segregated in legally and operationally independent entities that are shielded from problems in the rest of the group. Although the exercise of such powers may result in a reduction of the number of subsidiaries, it is also possible that a requirement to segregate functions in legally and operationally independent entities may increase the number of subsidiaries. A prime example of this approach is Great Britain, which has required its large clearing banks to ring-fence their domestic retail activities and form a separate legal entity to conduct all other business. The US has added to this pressure to increase the number of legal entities by requiring that large foreign banks in the United States form an intermediate holding company in the US. The foregoing summary has provided only a broad-brush overview of an ambitious and complex international agenda to strengthen the infrastructure for resolving G-SIBs. An external analyst faces insuperable challenges in evaluating progress in the implementation of such a complicated set of policy reforms, yet it is essential for market participants to have confidence that these measures are being implemented and that they will make it feasible for the authorities to resolve any G-SIB without public subsidy and intolerable spillovers. If market participants lack confidence that an orderly resolution of G-SIBs is feasible, such institutions will continue to benefit from an implicit public subsidy, which provides them with an incentive to become still larger and more complex. The FSB makes regular public reports to the G20 on progress in implementing the KA. The sixth and most recent report (FSB, 2017a) concludes that only a subset of the FSB jurisdictions have adopted bank resolution regimes with comprehensive powers consistent with the KA.27 Fortunately this subset includes most of the jurisdictions in which G-SIBs are headquartered, but the majority of FSB jurisdictions have not yet implemented reforms consistent with the KA. The FSB notes particular lags in implementation of bail-in powers, powers to impose a temporary stay on the exercise of early termination rights and powers to require changes to banks’ structures and operations to improve resolvability. CMGs have been established for all G-SIBs, but cross-border cooperation agreements have been signed for only 70 percent of G-SIBs, and operational resolution plans have been developed for only 70 percent of G-SIBs. The report also identifies operational and financial interdependencies within G-SIBs as potential impediments to the resolvability and restructuring of a G-SIB, a problem that was clearly apparent in the LB bankruptcy. Moreover, the report notes that booking models employed by G-SIBs could hinder the separation of business lines and legal entities in a restructuring and winding-down of derivatives and trading activity during resolution, a problem which also clearly impeded the bankruptcy resolution of LB. The report (FSB, 2017a, p. 16) concludes that “The complexity and interconnectedness of G-S[IB]s pose challenges to resolvability. Despite changes to legal and operational structures in the case of some G-S[IB]s, the complexity of organizational structures and high degree of internal and external (financial and operational) interconnectedness remain important challenges to resolvability.” 27 This document summarizes the findings from the third Resolvability Assessment Process for G-SIBs completed in 2017.

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Corporate Complexity and Systemic Risk   123 While the overview of progress in implementation of the resolution reforms provided by the FSB provides general insights about progress in implementing the KA, it lacks sufficient detail to reassure market participants about the resolution prospects of individual G-SIBs in the event of a crisis. Unfortunately, most countries have done little or nothing to disclose information about the resolvability of individual banks. The striking exception is the United States, where G-SIBs are required to make public a section of their Living Will submissions and the authorities have posted letters to each G-SIB expressing their view on the progress—or lack of progress—the G-SIB has made in achieving resolvability. This degree of transparency far surpasses that in the rest of the world. And, although the transparency has steadily improved in the US, no other country appears to have followed the US lead. Disclosures about US-based G-SIBs enable us to draw additional insights into progress made in improving the resolvability of these banks and so this section concludes with a brief overview of the Living Will process in the United States. The Dodd–Frank Wall Street Reform and Consumer Protection Act of 2010 (DFA) provided the resolution authority in the US with the full set of powers detailed in the KA. But resolution policy has taken a distinctive pattern in the US, because the DFA requires that each G-SIB demonstrate how it could be resolved under bankruptcy procedures without recourse to public assistance. This is a particularly tough standard because most experts agree that current bankruptcy laws are not well suited to the need for speed in resolving a G-SIB active in global financial markets. Markets tend to move at lightning speed in contrast to the usual deliberate pace of bankruptcy courts, which tend to place heavy emphasis on due process. Without measures to accelerate and simplify the bankruptcy process, most of the going concern value of a G-SIB could be lost as creditors and counterparties flee the institution in a disorderly scramble. The House of Representatives has passed legislation to create a new chapter of the US bankruptcy code28 better suited to the speed with which a large financial institution must be resolved to minimize spillovers and loss, but the Senate has not addressed the problem and so the legislation remains in limbo as of October 2018. In the meanwhile, substantial efforts have been made to design procedures under which a G-SIB could be successfully resolved under existing bankruptcy law.29 The success of such procedures, however, depends crucially on structuring banks so that they are resolvable under the constraints imposed by Congress. The Living Will process in the US has emphasized restructuring banks to make bankruptcy a feasible resolution strategy. The proposal to employ current bankruptcy procedures to US G-SIBs builds on a resolution strategy developed jointly by the Federal Deposit Insurance Corporation and the Bank of England (2012) termed the Single Point of Entry (SPOE). The SPOE is designed to enable a G-SIB to be resolved without threatening financial stability and 28  The legislation is based on a proposed Chapter 14 of the bankruptcy code specifically designed for large financial institutions. The proposal, developed by the Hoover Institution Resolution Project, is described in Scott and Taylor (2012). 29  For an overview of how this might be accomplished see Wharton Financial Institutions Center (2016).

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124   The Theory of Banking without putting public funds at risk. It is a top-down strategy to be applied by a single resolution authority to the top of the financial group, while permitting systemically important operations to continue. In the US, the strategy would apply a single receivership to the top-level holding company, assigning losses to shareholders and unsecured creditors of the holding company, and transfer sound operating subsidiaries to a solvent bridge institution, which would restructure the operations to maintain as much going-concern value as possible for creditors. The strategy finesses the complexities of dealing with a welter of intermediate holding companies and subsidiaries by focusing the resolution process on the top-level holding company. In so doing, it neatly separates the financial problem of a non-viable bank from the much more complicated underlying problems with its business model and operations. With proper preparation, the financial problem— capitalizing a successor bridge institution—could be achieved relatively quickly without risk to public funds by converting a sufficient amount of the unsecured debt of the nonviable holding company into equity for the new bridge institution. The solvent successor bridge institution would then undertake the much more time-consuming process of restructuring the bank through shrinking lines of business causing distress or breaking the group into smaller entities and closing or selling certain operations. Although the SPOE was originally designed for use by the FDIC, if it should be obliged to resolve a G-SIB under Title II of the DFA, subsequent analysis has shown how the concept could be applied to a bankruptcy proceeding. The preconditions for executing an SPOE have largely determined the requirements for Living Wills prepared by US G-SIBs. These include: establishing a “clean holding company” that issues debt and equity for the group, but has no operational responsibilities; ensuring that the holding company has issued a sufficient amount of unsecured debt to enable it to  recapitalize a faltering subsidiary; negotiating agreements with jurisdictions that host material entities of the G-SIB that permit the US to control the resolution ­process so long as the interests of host-country creditors are protected; rationalizing the structure of G-SIBs to ensure that critical shared services will continue to be ­provided to the successor bridge entity after the bankruptcy petition is filed; and designing mechanisms to make sure the bankruptcy filing is made while the G-SIB still has adequate capital and liquidity to fund the resolution without reliance on public funds. Under the terms of the DFA, G-SIBs are required to submit Living Wills to the Federal Reserve Board (Fed) and FDIC, detailing how they could be resolved through bankruptcy. These submissions are massive, sometimes involving tens of thousands of pages, but they must include a summary of the G-SIB’s resolution strategy and resolvability preparedness that is made public. The Fed and FDIC evaluate feasibility and credibility of these plans and provide feedback to each institution about measures it should take to ensure that it will be resolvable under bankruptcy. G-SIBs take this feedback quite seriously because the DFA provides the authorities with the power to take punitive measures, including restrictions on payouts to shareholders, restraints on growth or directives to divest lines of business, if the Fed board and the FDIC board each conclude that a G-SIB’s Living Will is not credible. Initially the feedback from the

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Corporate Complexity and Systemic Risk   125 authorities to each individual G-SIB was strictly confidential, but in the most recent round of reviews, feedback letters have been released to the public, thus providing important, additional details about measures that each G-SIB must take to improve its resolvability. This has greatly enhanced the credibility of the process since the institutionspecific comments are detailed and indicate that the authorities are examining the submissions carefully.30 In the first round of submissions, the public sections of Living Wills conveyed little new information relevant to resolvability. Terminology was not standardized, and disclosures were quite ad hoc, providing little basis for meaningful comparisons and little information that was not already publicly available. Table 4.5 summarizes some of the key features of the public sections of Living Wills released in 2017. The bottom two rows of the table provide a crude measure of how these public disclosures have expanded. The July 2012 and 2013 submissions averaged thirty-one pages. In contrast, the July 2017 submissions averaged 108 pages. More importantly disclosures were much more relevant to assessing an institution’s resolvability and somewhat easier to compare, although still not standardized. In the 2017 round of disclosures, all eight US G-SIBs listed and described each of their material entities including relevant financial data, which was an important advance. Each G-SIB attempted to map its lines of business in to its material entities, but the approaches varied markedly across banks with some banks providing information that is difficult to assess. Attempts were made to represent inter-affiliate exposures and operational interconnectedness among material entities, but it was difficult to make any comparisons across G-SIBs. Some banks did an excellent job of identifying critical services provided by each material entity, but others did not provide such disclosures. Disclosure of participation in financial market utilities was relatively consistent across all eight G-SIBs. Clearly “best-practice” standards are evolving, but certainly the improvement from the first round of disclosures in 2012 and 2013 is remarkable. While these improvements in disclosure are welcome, gaps remain. It is useful to know which entities the G-SIB regards as material, but this leaves open the question of the role and importance of the majority of subsidiaries that are not designated as material. These subsidiaries should be categorized and an explanation provided about why each category is irrelevant to the resolvability of the group. In addition, the data collected by the SEC and the Fed should be reconciled and the criteria for classification should be clearly defined. For example, the Fed includes entities that are “of interest” even though they are not controlled subsidiaries and no explanation is provided about why they are of interest. This lack of clarity makes it impossible for an external analyst to reconcile the Fed’s data with other publicly available sources.

30  The credibility of the process was also enhanced when some submissions were judged “not credible” and improvements were required. In December 2016, the Fed and the FDIC imposed restrictions on the growth of international and non-bank activities of Wells Fargo, due to deficiencies on “legal entity rationalization” and “shared services.” Wells Fargo subsequently remediated these deficiencies.

Bank of America

Bank of New York Mellon

Citigroup

Goldman Sachs

JPMorgan Chase

Morgan Stanley

State Street

Wells Fargo

List of material entities

X

X

X

X

X

X

X

X

Description of business of material entities

X

X

X

X

X

X

X

X

Financials of material entities

X

X

X

X

X

X

X

X

Mapping between material entities and business lines

X–

X–

X–

X–

X

X

X+

X–

X

X (simplified)

X

X

X

X

X– (simplified) X

Organizational hierarchy before resolution Organizational hierarchy after resolution

X

X (simplified)

Inter-affiliate exposures/funding

X (qualitative)

X (qualitative)

X (qualitative)

X (qualitative)

X– (qualitative)

Not material

X (qualitative)

X

X+

X+

X+

X

X+

X

X+

X+

X

X

X

Critical services by legal entity Material entities operational interconnectedness

X–

Participation in FMUs

X

X

X

X

X

X

X

X+

No. pages public section resolution plan 2017 (July)

87

121

125

116

170

108

70

66

No. pages first public section of resolution plan (July 2012 or 2013)

42

24

32

32

33

31

22

28

Source: Authors’ assessment of public sections of resolution plans (July 2017). An “X” indicates that information is included. An “X+” indicates that the quality of information is relatively higher when compared to peers. An “X–” indicates that the quality of information is relatively lower when compared to peers. “Simplified” means that the information on organizational hierarchy is included but is less detailed than information provided by peers. “Qualitative” means that the information provided is mostly of a qualitative nature. “FMUs” are financial market utilities, which provide the infrastructure for transferring, clearing, and settling payments, securities, and other financial transactions among financial institutions.

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Table 4.5  Public Sections of Resolution Plans of the 8 US G-SIBs (July 2017): Key Selected Information

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Corporate Complexity and Systemic Risk   127

4.6 Conclusions This chapter offers a progress report on the number of subsidiaries controlled by G-SIBs, ten years after the GFC. The previous two editions of this chapter had documented the corporate complexity of G-SIBs just before the GFC and five years later and showed that the number of controlled subsidiaries had not decreased despite the initiation of an ambitious reform agenda designed to enhance the resolvability of G-SIBs. This chapter provides new data, showing again that, despite some simplification, our proxy for corporate complexity remains very high. Furthermore, the obstacles that such corporate complexity might pose to an orderly resolution may be underestimated because we have not been able to collect consistent data on foreign branches of G-SIBs, which may create problems in resolution. It is likely that our measure of corporate complexity has remained high because G-SIBs have compelling incentives to maintain large numbers of controlled subsidiaries. The internal and external drivers influencing the decision to form controlled subsidiaries, examined in section 4.4, have not changed. G-SIBs may still decide to create separate subsidiaries to deal with asymmetric information issues; they can still be involved in large M&A with large and persisting effects on their corporate structures; they are still constrained by rules imposing some form of corporate separateness both domestically and in foreign jurisdictions; and cross-jurisdictional differences in tax regimes and accounting and disclosure rules continue to motivate G-SIBs to adopt complex corporate structures. Nonetheless, some G-SIBs have made significant efforts to simplify and rationalize their corporate structures. Undoubtedly, regulatory pressure and, in some cases, market forces have played a role. Fed/NIC data show a strong reduction in the number of controlled subsidiaries for most US G-SIBs, which may well be a result of the regular Living Wills evaluations in the US. Several other G-SIBs headquartered outside the US have also reduced the number of their controlled subsidiaries, but this trend is not uniform across G-SIBs and some G-SIBs have substantially increased their number of controlled subsidiaries. Our comparison of the data on the corporate structures of US G-SIBs reported in the BvD and the Fed/NIC databases revealed troubling discrepancies which we have not been able to resolve. In part this is because the criteria and methodology for constructing these databases are particularly complex. This is surprising since it should be quite straightforward to report the number of legal entities controlled by each G-SIB. Of course, other aspects of complexity such as operational and financial interdependencies are much more difficult to measure in principle and we lack any consistent, systematic data to make comparisons across G-SIBs. These shortcomings in the data impede deeper analysis and hamper a better understanding of how opaque and complex corporate structures may affect the resolvability of G-SIBs and their implications for systemic risk.

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128   The Theory of Banking One of the objectives stated in the FSB KA was to improve transparency regarding the structure and resolvability of G-SIBs to facilitate market discipline on these institutions and eliminate any implicit too-big-to fail subsidy. It is difficult to see how this objective can be fully achieved without more systematic disclosures regarding the resolution strategies and the resolvability of G-SIBs. The US has led the way improving disclosures of the relevant data through the public sections of Living Wills and supervisory evaluations of the Living Will submissions but, as of October 2018, no other country has followed this precedent. While the US disclosures could be improved by standardizing classification criteria and reporting formats, public information relevant to evaluating the resolvability of US G-SIBs is markedly better than for any G-SIB headquartered outside the US (as this chapter was being prepared, living wills disclosure was announced also in the United Kingdom). A useful first step for improving our understanding of the aspects of corporate complexity that we have analyzed in this chapter is the establishment of a definitive database on the corporate structures of G-SIBs that applies a consistent,31 transparent methodology to all G-SIBs and is made publicly available in a format that can be easily analyzed. These data should include all key information on organizational hierarchies, the name, business, location, financials, and intra-group connections and exposures for each subsidiary. Given the key role of the BCBS and the FSB in the identification and regulation of G-SIBs, these institutions would appear as the most natural candidates to collect, manage and post these data. The establishment of this data set at the FSB or BCBS would also facilitate inclusion of a more direct measure of corporate complexity in the methodology for the identification of G-SIBs. The most recent revision of the G-SIB methodology (BCBS, 2018, p. 6) states “The systemic impact of a bank’s distress or failure is expected to be positively related to its overall complexity—that is, its business, structural and operational complexity.” Yet, the three proxies the current methodology employs to measure complexity— the notional value of OTC derivatives, the amount of Level 3 assets,32 and the value of the trading book and available-for-sale assets—omit any indicator of the complexity 31  Consistent, transparent criteria are crucial for addressing one of the major problems marring currently available data—the lack of common, clear criteria for the identification of the subsidiaries of G-SIBs. 32  “Level 3 Assets” are an accounting category of assets that must be reported at current value, but cannot be valued at market prices determined in broad, deep financial markets or on the basis of straightforward models linked to current market prices. Level 3 Assets are distinguished from Level 1 Assets (which are valued from readily observable market prices and can thus be “marked-to-market”) and from Level 2 Assets (which are valued based on models that rely on readily observable market inputs and are thus “marked-to-matrix”). In contrast, Level 3 Assets are not actively traded, like Level 1 Assets, and have a more tenuous relationship to actively traded assets than Level 2 assets. The values of Level 3 Assets are estimated based on complex models that rely heavily on subjective assumptions and are described as “marked-to-model” or, more cynically, “marked-to-management.” The category typically includes distressed debt, private equity, complex, bespoke derivatives contracts and other illiquid assets. The BCBS has used Level 3 Assets as one of its proxies for complexity in the identification of G-SIBs, because these assets would be likely to impede an orderly resolution. In general, Level 3 Assets are heavily concentrated on the books of large, international banks.

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Corporate Complexity and Systemic Risk   129 of corporate structure.33 This omission might not be important if corporate complexity were perfectly correlated with the complexity of a bank’s assets as reflected in its OTC derivatives, Level 3 assets and trading and available for sale book, but it is not. Carmassi and Herring (2016a) have shown that the correlation of these measures with the number of subsidiaries is far from perfect. The LB bankruptcy demonstrated the crucial importance of the number and location of the group’s separate legal entities. It is surely time to address the omission of corporate complexity in the methodology for the identification of G-SIBs.

References Avraham, D., Selvaggi P., and Vickery J. I. (2012). “A Structural View of U.S. Bank Holding Companies,” Federal Reserve Bank of New York Economic Policy Review, 18(2), 65–81. Basel Committee on Banking Supervision (BCBS) (2011). “Global Systemically Important Banks: Assessment Methodology and Higher Loss Absorbency Requirement - Rules Text,” November. Basel Committee on Banking Supervision (BCBS) (2018). “Global Systemically Important Banks: Revised Assessment Methodology and the Higher Loss Absorbency Requirement,” July. Carmassi, J. and Herring, R. J. (2015). “Corporate Structures, Transparency and Resolvability of Global Systemically Important Banks,” Systemic Risk Council, Washington, DC, January 27. Carmassi, J. and Herring, R. J. (2016a). “The Corporate Complexity of Global Systemically Important Banks,” Journal of Financial Services Research, 49, 175–201. Carmassi, J. and Herring, R.  J. (2016b). “The Cross-Border Challenge in Resolving Global Systemically Important Banks,” in K. Scott, T. Jackson, and J. Taylor (eds.), Making Failure Feasible (Stanford, CA: Stanford University Press), 249–75. Cetorelli, N. and Goldberg, L.  S. (2014). “Measures of Global Bank Complexity,” Economic Policy Review, 20(2), Special Issue on Large and Complex Banks, March 31. Dermine, J. (2006). “European Banking Integration: Don’t Put the Cart Before the Horse,” Financial Markets, Institutions & Instruments, 15, 57–106. Financial Stability Forum (2000). Press Release, May 26, 2000. Financial Stability Board (FSB) (2011a). “Policy Measure to Address Systemically Important Financial Institutions,” Press Release, November 4. FSB (2011b). “Key Attributes of Effective Resolution Regimes for Financial Institutions”, November 4. The version referenced in the text was updated in October 2014, and is available at: https://www.fsb.org/wp-content/uploads/r_141015.pdf FSB (2015). “Total Loss-Absorbing Capacity (TLAC) Principles and Term Sheet,” November, available at: https://www.fsb.org/wp-content/uploads/TLAC-Principles-and-Term-Sheetfor-publication-final.pdf FSB (2017a). “Ten Years On—Taking Stock of Post-crisis Resolution Reforms,” Sixth Report on the Implementation of Resolution Reforms, July 6. FSB (2017b). “2017 List of Global Systemically Important Banks (G-SIBs),” November 21. 33  To some extent, the indicators for cross-jurisdictional activity—cross-jurisdictional claims and cross-jurisdictional liabilities—reflect a degree of international corporate complexity, but they are simply measures of financial claims and do not convey any information about the legal entities that transact these claims, which would be the focus of a resolution. The number of jurisdictions where a G-SIB has subsidiaries or branches would be more relevant but it is only included as ancillary indicator.

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130   The Theory of Banking Goodman, L., Lucas, D., and Fabozzi, F. (2007). “Financial Innovations and the Shaping of Capital Markets: The Case of CDOs,” Journal of Alternative Investments, 10(1), 62–70. Haldane, A. G. and Alessandri, P. (2009). “Banking on the State,” paper based on a presentation delivered at the Federal Reserve Bank of Chicago Twelfth Annual International Banking Conference on “The International Financial Crisis: Have the Rules of Finance Changed?” Chicago, September 25. Herring, R. J. and Carmassi, J. (2010). “The Corporate Structure of International Financial Conglomerates: Complexity and its Implications for Safety & Soundness,” in A. N. Berger, P.  Molyneux, and J.  O.  S.  Wilson (eds.), Oxford Handbook of Banking (Oxford: Oxford University Press). Herring, R. J. and Carmassi, J. (2014). “Complexity and Systemic Risk: What’s Changed Since the Crisis?” in A. N. Berger, P. Molyneux, and J. O. S. Wilson (eds.), Oxford Handbook of Banking, 2nd edn (Oxford: Oxford University Press). Herring,  R.  J. and Santomero,  A.  M. (1990). “The Corporate Structure of Financial Conglomerates,” Journal of Financial Services Research, 4(4), December, 471–97. Huertas, T. F. (2014). Safe to Fail: How Resolution Will Revolutionise Banking (London: Palgrave Macmillan). Hume, N. (2011). “Protium’s Acid Reflux (updated),” FT Alphaville, April 28, available at: http://ftalphavilled.ft.com/2011/04/28/555611/protiums-acid-reflux/. King, M. (2010). “Banking from Bagehot to Basel, and Back Again,” Second Bagehot Lecture, Buttonwood Gathering, New York City, October 25, available at: https://www.bankofengland. co.uk/speech/2010/banking-from-bagehot-to-basel-and-back-again-speech-by-mervyn-king Laeven, L., Ratnovski, L., and Tong, H. (2014). “Bank Size and Systemic Risk,” IMF Staff Discussion Note, SDN/14/04, May. Scott, K. E. and Taylor, J. B. (2012). “Bankruptcy Not Bailout: A Special Chapter 14”, Hoover Institution. Wharton Financial Institutions Center (2016). “Resolution of Global Systemically Important Financial Institutions Under the Bankruptcy Code,” Briefing materials, available at: https:// fic.wharton.upenn.edu/resolution-under-bankruptcy/.

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chapter 5

Cor por ate G ov er na nce a n d Cu lt u r e i n Ba n k i ng Jens Hagendorff

5.1 Introduction Corporate governance deals with the ways in which outside investors and other stakeholders, such as government and employees, exercise control over senior management and other corporate insiders in order to protect their interests. The seminal work by Jensen and Meckling (1976) describes the frictions between corporate insiders and shareholders as well as between equity holders and external firm creditors over the desired level of firm risk. In a nutshell, since shareholders hold residual claims over a firm’s assets, they have incentives to increase firm risk. While shareholders benefit from pursuing risk-increasing policies (they benefit from any upside potential in the value of their equity), external firm creditors stand to bear losses without the prospect of wealth gains from higher risk. Banks differ from non-banking institutions in many important ways. The nature of their core activities is information-based and highly opaque, their capital structure is geared toward debt much more than any other major industry, and governments are an important stakeholder in banks, both as regulators and as a fiscal backstop, for instance, through the lender of last resort function (Calomiris and Carlson, 2016). This suggests that the corporate governance of banks should be different from that of non-financial firms to reflect the differences between banks and non-banking firms. Perhaps surprisingly, it is not the case that bank governance is greatly different from the corporate governance arrangements of other firms. While certain aspects of bank governance are unique for banks (for instance, there are restrictions on bank ownership or bank capital structure when regulators limit leverage in some countries), most key

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132   The Theory of Banking aspects such as the organization of the board of directors or the way in which senior executives are paid is more or less in line with that of non-financial firms. Hence, many governance devices in the banking sector mimic those of non-financial firms quite closely without taking the unique features of banks sufficiently into account. As this chapter will argue, this can be problematic if, for instance, overly shareholder-focused governance is applied to a highly leveraged industry such as banking. Before the financial crisis started in 2007, research into the nature and effects of corporate governance in banks was disparate and scattered across different journals and subdisciplines of finance, management, and economics (see Haan and Vlahu, 2016 for an overview of these different streams of research). With some exceptions, work on the corporate governance of banks rarely made it into the most prestigious academic journals, perhaps reflecting what, until recently, was a widespread view that the corporate governance of banks is a niche subject and that banks are not sufficiently different from other firms to warrant a separate investigation of their corporate governance arrangements. The result is that a coherent body of empirical findings, which advances our understanding of this subject area and serves as a basis for sound policy advice, has been missing to date. However, banking is increasingly becoming an industry with corporate governance standards that differ from those in place in other industries. This demonstrates that, from a policymaking view, a new consensus has emerged that the corporate governance of banking firms deserves special and separate attention because of its importance for bank creditors, the taxpayer, and the real economy. Some examples of recent governance rules and codes targeted at the banking industry include the following. In the UK, a review conducted by Sir David Walker regarding the corporate governance in UK banks and other financial institutions has made recommendations on board arrangements and the qualifications of board members as well as on the compensation arrangements of UK banks and financial firms. Partly following on from this, the 2009 UK Remuneration Code required executives of UK banks to defer a larger portion of their bonus compensation and introduced performance-vesting conditions for these bonuses. In February 2013, the UK Remuneration Code was followed by an EU-wide bonus cap for banks that restricted the variable part of total compensation to 100 percent of the fixed component (see Kleymenova and Tuna, 2017, for an overview of the UK and EU pay regulations for banks). Similarly, the Netherlands has had a Banking Code in place since 2010 that contains guidelines on the make-up of bank boards, including the qualification and training of board members and their remuneration. Additionally, US compensation guidelines for CEOs and other senior executives at large banks come close to dictating compensation structures in banking (Board of Governors et al., 2010, p. 33). The flurry of new bank governance rules has meant that in a number of countries, banks now have separate corporate governance codes from other industries. However, as this chapter will argue, there are reasons to rethink the corporate governance of banks more profoundly. This chapter will survey the key literature on the

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Corporate Governance and Culture in Banking   133 governance of banking institutions and argues that the differences between banks and non-financial firms necessitate governance arrangements that reflect these differences. Crucially, governance arrangements that do not sufficiently take the unique features of banks into account risk exacerbating existing agency conflicts that may have contributed to excessive risk-taking by banks before the global financial crisis of 2007–9. As an illustration of this, banks are highly leveraged firms. Equity funding in banking makes up the smallest proportion of the balance sheet of any major industry. However, equity holders control the key governance mechanisms of banks, such as the board of directors (shareholders enjoy the power to appoint and remove directors), and set remuneration of senior management just like in any other industry where equity makes up a much more substantial proportion of funding and where equity holders jointly have greater loss exposure (more “skin in the game”). As a result, with risk-based profits going to equity holders, equity holders have strong incentives to put in place monetary risktaking incentives that lead to higher payoffs for them at the expense of debtholders (and by extension, the deposit insurer or taxpayer that acts as a fiscal backstop in the event of bank failure). The divergent interests between equity- and debtholders as regards risk is just one example where, owing to the highly geared capital structure of banks, shareholderoriented corporate governance leads to risky strategies that may hurt the interests of other stakeholders in banks. Consistent with this, Beltratti and Stulz (2012) show that banks that underperformed during the crisis had “better” (i.e., more shareholder-focused) corporate governance arrangements in place before the crisis. Therefore, as this chapter will argue, banks warrant separate governance arrangements that take their unique features into account over and beyond what is currently being proposed. Further, it is an increasingly widespread view that that operational and other failures in banking are not isolated events that can be attributed to a small number of people who have not been incentivized or monitored effectively (Group of Thirty, 2015). For instance, large-scale improvements in bank governance have gone hand in hand with ever more cases of misconduct and operational failures in banks (Nguyen, Hagendorff, and Eshraghi,  2015a). Therefore, standard corporate governance arrangements seem unable to prevent operational and other bank failures. Instead, it seems probable that there are systematic issues, in some cases condoned and perhaps tacitly encouraged by the culture prevailing in some banks (Fahlenbrach, Prilmeier, and Stulz, 2012; Song and Thakor, forthcoming). Given the high leverage of banking firms and the concerns over excessive risk-taking incentives for shareholders, the culture prevailing in banks can be an important governance device. This chapter proceeds as follows. The next section discusses the manner in which banks differ from non-financial firms and why this matters for the corporate governance of banks. The sections after that discuss the literature on the compensation of senior executives, the independence, and the composition of the board of directors, the shareholder structure, and the risk culture of banks.

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134   The Theory of Banking

5.2  Why Banks are Different and the Implications for Bank Governance Banking theory explains that the nature of financial intermediation makes bank assets informationally opaque and difficult to assess and monitor for outsiders and banks vulnerable to runs (e.g., Diamond and Dybvig, 1983; Diamond and Rajan, 2001). While there are many factors that make banks different from non-financial firms, not all of these factors have corporate governance implications. However, two aspects that make banks special and that have implications for the corporate governance of banks are the capital structure of banks (banks are highly leveraged) and the tightly regulated nature of many of their activities. Why both of these aspects make banks different in terms of their governance is the focus of this section. One of the reasons why bank governance warrants separate analysis is that banks, by the standards of other industries, issue little equity. While equity investors are a lot less important than creditors in terms of the funding they provide to banks, equity investors still control key governance devices such as the board of directors, director appointments (and dismissals), and executive pay. Hence, it is shareholders that can put in place monitoring mechanisms and incentives designed to bring about shareholder-focused outcomes. This matters because shareholders have different risk preferences (they are risk neutral) from creditors (who are risk averse) and because the negative externalities caused by bank failures mean that bank risk-taking is clearly a policy-relevant issue. It is important to emphasize just how unusual banks are in terms of their levels of financial leverage. Figure 5.1 illustrates that the average listed US firm in 2007 (before the crisis) was funded by around 30 percent equity (relative to total assets). However, for banks it is not unusual to have a balance sheet where liabilities account for in excess of 90 percent of total assets. Some large European banks entered the global financial crisis of 2007–9 with equity accounting for less than 3 percent of total assets. As Figure 5.1 shows, no other major industry has leverage ratios as high as the banking industry. The high leverage of banks has two important corporate governance implications. The first implication is that high leverage can lead to excessive risk-taking if bank shareholders become too dominant in the governance of the bank. Going back to at least Jensen and Meckling (1976), it is well known that there are conflicts between equity holders and external firm creditors over the desired level of firm risk. Since shareholders hold residual claims over a firm’s assets, they have incentives to increase firm risk. While shareholders benefit from pursuing risk-increasing policies (they benefit from any upside potential in the value of their equity), external firm creditors stand to bear losses without the prospect of wealth gains from higher risk. The second implication from high leverage is that, in the banking industry, risktaking incentives linked to equity are further intensified by the presence of guarantees advanced by regulators and governments. Therefore, it is a widely held view that the financial safety net (and by extension regulators) is at least in part responsible for the high leverage of banks. The view is that regulators subsidize bank leverage and thus

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Corporate Governance and Culture in Banking   135

Banking Tobacoo Products Shipping Containers Utilities Printing and publishing Food Product Construction Restaurants, Hotels and Motels Transportation Communication Automibles and Trucks Real Estate Entertainment Shipbuilding, Railroad Equipment Whole sale supplies Business Supplies Candy & Soda Retail Aircraft Textiles Rubber ans Plastic Products Consumer goods Healthcare Chemicals Agriculture Steel works Beer & Liqour Machinery Construction materials Business Services Defense Toys Recreation Computers Electrical equipment Petroleum and Natural Gas Apparel Electronic equipment Pharmaceutical Products Medical equipment Measuring and Control equipment Precious Metals Non-metallic and Industrial Metal Mining

Firm Leverage [Liabilities/(Liabilites + Equity)], 2007 100.00% 90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00%

Figure 5.1  Firm Leverage [Liabilities/(Liabilities+Equity)], 2007.

induce banks to issue larger amounts of liabilities than they otherwise would. For instance, since the prospect of large externalities caused by bank failures raises the expectation of bank bailouts, banks may increase their implicit claim on the financial safety net through higher risk-taking. Both explicit deposit insurance and implicit bailout guarantees shield bank creditors from market discipline and induce banks to “lever up” at low costs. Consistent with public bank guarantees inducing higher leverage, Berger, Herring, and Szegö (1995) show drastic increases in the leverage of US banks since the midnineteenth century. The leverage increases coincide with various changes in regulation that made the financial safety net more generous. Examples are the Federal Reserve Act of 1914, which let banks obtain liquidity via discounting assets at the Federal Reserve, and the creation of deposit insurance in 1933, which guaranteed depositors’ repayments in the event of a bank failing.

5.3  Compensation in Banking Executive compensation policy may serve as a mechanism to reduce conflicts between managers and shareholders over the deployment of corporate resources and the riskiness of the firm (Jensen and Meckling, 1976). Public and academic interest in CEO

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136   The Theory of Banking compensation in the banking industry has increased exponentially in the aftermath of the financial crisis of 2007–8. While this is partly motivated by public outrage over the levels of CEO remuneration in an industry that has become increasingly reliant on public funds, the view that the structure of executive pay has given rise to socially harmful risk-taking by banks is gaining ground. Thus, the use of incentive pay in banking is widely believed to have motivated excessive risk-taking and to have acted as a contributory factor to the recent financial crisis (e.g., Bebchuk and Spamann, 2009; Federal Reserve Bank, 2010). This section critically reviews existing empirical work on the relationship between CEO pay and bank risk-taking and argues that previous work has been too narrow in its focus on equity-linked CEO compensation (mainly share and option grants) while neglecting common forms of CEO compensation that are not equity-linked and that could make a valuable contribution to promoting more socially optimal risk-taking by banks. Research that examines non-equity components of CEO compensation, particularly pensions and other forms of deferred compensation, is still in its infancy. However, many of the findings proffered by this stream of research are consistent with the view that, where equity-based pay encourages risk-taking, non-equity-linked pay makes CEOs more risk averse (see Edmans and Liu, 2011). This section argues that it is regrettable that not more is empirically known about the risk effects generated by non-equity (and essentially more debt-like) forms of compensation and calls for debt-like components of CEO compensation to be examined in greater detail.

5.3.1  Cash and Bonus Compensation Most of the extant literature largely overlooks the role of CEO cash bonuses as a ­risk-taking incentive. The lack of empirical work on CEO bonus plans on bank risk is unfortunate for two reasons. First, CEO cash bonuses are an important component of executive pay. CEO bonus payments make up around a third of total CEO compensation (Murphy,  2000). Second, the effect of bonus payments on managerial risk preferences is likely to differ from that exerted by option grants. Figure 5.2 illustrates the shape of a typical bonus function. CEO cash bonuses generally become payable once an earnings-based target over a one-year period has been met. After exceeding this threshold, the CEO payoffs from bonus plans increase in line with performance until capped at a maximum payout. Therefore, for earnings performances exceeding the threshold at which bonus payments become payable, CEO bonus plans do not provide convex payoffs (Smith and Stulz, 1985) and should not promote excessive risk-taking (see Noe, Rebello, and Wall, 1996; Duru, Mansi, and Reeb, 2005). This is in sharp contrast to CEO holdings of stock options. Since the payoffs from option holdings are convex functions of the volatility of stock returns, options incentivize CEOs to increase the volatility of share prices by engaging in riskier activities (Guay, 1999; Rajgopal and Shevlin, 2002; Coles, Daniel, and Naveen, 2006; Hagendorff and Vallascas, 2011).

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Corporate Governance and Culture in Banking   137 Annual Bonus Linear Payoff

Bonus Cap

Performance Measure Performance Threshold

Figure 5.2  A Typical Cash Bonus Function. Source: Adopted from Murphy (2000).

Theoretical work posits that CEO cash bonuses can play an important role in mitigating managerial incentives to engage in risk-shifting. In a theoretical model, Smith and Stulz (1985) show that as long as cash bonuses increase linearly with corporate performance, the payoffs linked to a bonus plan are non-convex and therefore not inherently risk-rewarding. However, when performance is below the earnings-based threshold at which bonuses become payable, bonus plans resemble a call option on the performance measure. In this case, bonus plan payoffs will be convex and offset the concavity of the CEO’s risk-averse utility function. By contrast, when performance is above the threshold at which bonuses become payable (and below the bonus cap), the slope of a bonus plan is linear with respect to performance and will not incentivize risk-averse CEOs to increase bank risk in order to secure higher bonus payments. Other work suggests that, rather than having no effect on risk-taking, bonuses may lower the risk preferences of the CEO. One such argument suggests that, because bonus payments can only be received in a state of solvency, they incentivize CEOs to avoid bankruptcy (John and John, 1993). Consistent with this, Duru, Mansi, and Reeb (2005) find that earnings-based cash bonuses make managers seek stable cash flows to meet contractual debt obligations. The authors show that the costs of debt financing decrease for firms that pay higher CEO cash bonuses and contend that this reflects the lower agency costs of debt and reduced risk-shifting incentives in these firms.

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138   The Theory of Banking In spite of the arguments above, claims that cash bonuses encourage banks to engage in “excessive” risk-taking continue to be made (for instance, in the Financial Stability Board, 2009). However, the case for bonuses increasing risk tends to rest on two assumptions, both of which have recently been challenged by empirical evidence. The first assumption is that cash bonus contracts do not sufficiently expose managers to downside risk and therefore reward managers for taking on more risk to achieve the performance goals underlying bonus contracts. In contrast to this, empirical studies have shown that bonus contracts tend to punish underperformance more than they reward strong performance (Indjejikian et al., 2014). The second assumption is that, by making bonus payments contingent on annual performance targets, shareholders design bonuses to affect short-term behavior and managers pursue higher risk-taking strategies to achieve these short-term goals. While some evidence exists that managers may ration productive effort in order to maximize bonus payments (Bouwens and Kroos, 2011), this does not rule out that bonuses can be designed as long-term compensation tools. In fact, Indjejikian et al. (2014) show that bonus plans provide managers with long-term incentives to exert effort. These studies document that companies consider a trade-off between bonuses and career incentives over time horizons of multiple years when devising managerial compensation packages. The narrow empirical evidence available for the banking industry reaches conflicting conclusions on the role of CEO bonus payments and bank risk. Harjoto and Mullineaux (2003) report a positive association between bonus payments and return volatility (risk). Balachandran, Kogut, and Harnal (2010) proffer some evidence that the sum of bonus and other cash incentives reduces the probability of bank default. Fahlenbrach and Stulz (2011) do not find that CEO cash bonus payments affected the performance of US banks during the global financial crisis of 2007–9. Looking at risk, Vallascas and Hagendorff (2013) show that increases in CEO cash bonuses lower the default risk of banks. They explain this finding by arguing that, because bonus payments are contingent on bank solvency, they lower the risk preferences of CEOs. They then demonstrate that the risk-reducing effect of cash bonuses disappears as banks move closer to the point of default. At the riskiest banks, the results show that bonus payments promote rather than mitigate bank risk-taking. Kleymenova and Tuna (2017) examine the influence of the UK and EU regulations that limited bonus compensation (the so-called “EU bonus cap”). They find the market reacted positively to the Remuneration Code but negatively to the EU bonus cap. This suggests equity market investors view regulating executive compensation at least in part as costly. Interestingly, the authors also show that bank compensation contracts increase in complexity after the bonus cap. The regulation of bonuses has therefore given rise to some unintended costs.

5.3.2  Equity-based Compensation Over recent decades, the use of equity-linked compensation has increased rapidly, both inside and outside the banking industry. Equity-linked CEO compensation takes the

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Corporate Governance and Culture in Banking   139 form of grants of the firm’s shares as well as call options on the firm’s equity. Option grants in particular make CEO wealth sensitive to risk-taking. Pay-based incentives that make compensation more sensitive to risk (vega) and paybased incentives that make compensation more sensitive to performance (delta) are captured by a method described in Guay (1999). The measure captures the partial derivative of the value of the CEO’s portfolio of options (estimated using the dividend-adjusted Black–Scholes value) or stock holdings, respectively.

vega =

∂value × .01 = e − dT N ′ ( Z ) S T × .01 (1) ∂σ

delta =



(

∂value S S = e − dT N ( Z ) (2) 100 ∂S 100

)

where Z =  ln ( S / X ) + rf − d + 0.5σ 2 T  / σ T . N´(·) and N(·) are the normal proba  bility density function and the cumulative normal distribution respectively. S is the closing stock price at the fiscal year end, X is the exercise price of the option, σ is the annualized standard deviation of daily stock returns, r is the risk-free rate for a maturity value equal to that of the option contract, d is the dividend yield, and T is the time to maturity of the option grant. DeYoung, Peng, and Yan (2013) show that the use of equity-linked compensation in US banking has increased so rapidly over the last decade that CEO payoffs linked to increases in firm risk (vega) are higher in the banking industry than in non-financial firms. DeYoung, Peng, and Yan (2013) calculate that the average bank CEO saw his or her wealth increase by around $300,000 in 2004 as a result of a 0.01 percent increase in stock return volatility. Previous evidence on vega and the investment decisions made by managers is equivocal. For instance, the non-financial literature finds that higher CEO vegas lead to riskier investment choices and bind corporate resources to riskier activities (Guay, 1999; Rajgopal and Shevlin, 2002; Coles, Daniel, Naveen, 2006). For the banking industry, Mehran and Rosenberg (2007) and DeYoung, Peng, and Yan (2013) show that high-vega banks engage in riskier types of activities. By contrast, Fahlenbrach and Stulz (2011) do not find that CEO vegas explain the performance of bank stocks (i.e., previous managerial risk-taking) during the recent financial crisis. Hagendorff and Vallascas (2011) find that CEOs are responsive to the vega embedded in their compensation when engaging in acquisitions. Thus, higher pay risk sensitivity causes CEOs to engage in risk-increasing deals. As regards the levels of pay-performance sensitivity (delta), delta may exacerbate managerial risk aversion (Amihud and Lev, 1981; Smith and Stulz, 1985). DeYoung, Peng, and Yan (2013) find some evidence that delta reduces the riskiness of bank activities, while Mehran and Rosenberg (2007) do not detect any robust influence of delta on bank risk-taking. As regards the effect of CEO delta on the riskiness of merger decisions, Datta, Iskandar-Datta, and Raman (2001) find that higher deltas lead to acquisitions that are associated with higher increases in stock return volatility after a merger. For the banking industry, Bliss and Rosen (2001) and Minnick, Unal, and Yang (2011) show

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140   The Theory of Banking that high-delta banks are less likely to engage in acquisitions, which is consistent with high-delta CEOs forgoing risky investment projects such as mergers and acquisitions. Berger, Imbierowicz, and Rauch (2016) examine the role of managerial stock holdings (the primary component of delta above) and bank failures during the crisis. The results show that stock holdings of lower-level management (such as vice presidents) increase default risk while the shareholdings of CEOs and other senior executives do not affect the probability of failure. Even though the authors focus on stock holdings rather than compensation, the findings raise the possibility that pay and other governance variables ought to be examined not only at the level of the board of directors but also at hierarchical levels below the board.

5.3.3  Debt-based Compensation Debt as a form of executive remuneration is widespread. It tends to take the shape of deferred compensation, most notably in the form of defined benefit pensions (see Sundaram and Yermack, 2007; Wei and Yermack, 2011). These company promises of fixed sums at some future point in time are unfunded and unsecured CEO claims. In the US and many other countries, the deferred compensation claims of executives take no priority over the claims of other unsecured creditors in the event of bankruptcy, effectively turning the holders of inside debt into unsecured firm creditors. The value of deferred compensation claims by CEOs—also known as “inside debt” (Jensen and Meckling, 1976)—can make up a substantial share of a CEO’s overall remuneration. Wei and Yermack (2011) report that out of the S&P 1500 firms, more than two-thirds of CEOs hold some form of inside debt and that for those who hold inside debt, the holdings were worth an average of $5.7 million in 2006. A small number of empirical studies report evidence consistent with inside debt curbing CEO risk-taking behavior. Sundaram and Yermack (2007) find that large inside debt positions by a CEO reduce the probability of default on a firm’s debt. More recently, Wei and Yermack (2011) examine the bond and share price reaction to the disclosure of inside debt holdings in 2007 as mandated by the Security and Exchange Commission (SEC). The authors find that large CEO pensions (as well as other forms of deferred payments to CEOs) are associated with gains for bond holders and losses for shareholders. Few studies have been conducted to examine the effects of inside debt on bank behavior. Tung and Wang (2012) show that bank CEOs with higher inside debt holdings engaged in less risk-taking before the financial crisis (as indicated by better stock market performance during the financial crisis). Bennett, Guntay, and Unal (2015) show that larger CEO inside debt holdings before the crisis are associated with lower bank default risk during the crisis. Finally, Srivastav et al. (2018) show that acquisitions announced by CEOs with high inside debt incentives are associated with a wealth transfer from equity to debt holders. After the completion of a deal, banks where acquiring CEOs have high inside debt incentives display lower market measures of risk and lower loss exposures for taxpayers.

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Corporate Governance and Culture in Banking   141

5.4  The Board of Directors and Shareholder-Oriented Governance In all economic sectors, the board of directors of publicly traded companies is among the most important internal control mechanisms for promoting and protecting shareholder interests due to the board’s role in providing expertise and monitoring managerial discretion. More specifically, boards have the authority to ratify or obstruct managerial initiatives, to assess the performance of top management, and to determine managerial compensation packages and career paths at a particular firm. For a board to be effective in mitigating self-serving managerial behavior, its independence from management needs to be ensured. A common assumption is that boards that are more independent (in the sense that a larger proportion of directors has no family, social, or business connections to management) are more likely to bring about shareholder-oriented outcomes such as higher risk or better performance. Adams and Mehran (2003) report that US bank boards between 1986 and 1999 were both larger and more independent than those of S&P 500 manufacturing firms: the average board size was twelve for manufacturing firms and eighteen for banks. Given shareholders are risk neutral and managers are risk averse with respect to firm-specific and idiosyncratic risk (managers’ human capital is invested in their own firm and cannot be diversified), banks that are more shareholder controlled should be riskier. Powerful bank boards should therefore be associated with increased risk-taking activities, while powerful bank CEOs who face a less shareholder-oriented board should be associated with less risk-taking. Consistent with shareholder-aligned boards increasing risk, Pathan (2009) shows that as the boards of bank holding companies reflect shareholder interests to a larger degree (e.g., when they are smaller and more independent), bank risk-taking increases. Similarly, Laeven and Levine (2009) show that bank risk-taking increases with the comparative power of shareholders within the corporate governance structure of a bank. Examining the global financial crisis of the 2007–9 period, the evidence is not consistent with the view that the crisis has roots in the “weak” corporate governance, if weakness is defined in terms of how aligned boards are with shareholders. Thus, Erkens, Hung, and Matos (2012) find that firms with more independent boards realized lower stock returns during the crisis period. Similarly, for an international sample of banks, Beltratti and Stulz (2012) show that banks that underperformed during the crisis had altogether more shareholder-oriented boards. Beltratti and Stulz offer an intriguing explanation for their results. The authors argue that better-governed banks outperformed before the crisis by engaging in a number of activities that at the time were value enhancing but later on turned out to be a source of underperformance. Hence, they suggest that shareholder-focused banks suffered from “bad luck” (rather than ill-intent). Beltratti and Stulz’s (2012) study demonstrates the pitfalls of overly shareholder-oriented corporate governance. Therefore, shareholder-focused

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142   The Theory of Banking governance should not be viewed as a major component in the regulatory response to the global financial crisis of 2007–9. Finally, Berger, Imbierowicz, and Rauch (2016) findings encourage future corporate governance research to shift toward middle and higher management levels situated below the board of directors. The authors find managerial ownership can be linked to bank failures during the crisis if ownership is measured for managers (e.g., vice presidents or treasurers) but not when ownership is measured for top executives (e.g., CEO or Chief Financial Officer).

5.5  Board Diversity: Does it Matter who Runs Banks? It is a widely accepted view that the composition of the board of directors could play a vital role in determining corporate performance (see, e.g., Hermalin and Weisbach,  2003). In the past decade, boards in and outside the banking sector have made an increasing number of appointments from a wider range of demographic, educational, and social backgrounds. Following the global financial crisis of 2007–9, the view has taken hold that the responsibility of bank boards to monitor managerial risk-taking should be improved and that board diversity can play an important part in improving board decision-making. This view has some traction with policymakers and the general public. For instance, following the aftermath of the global financial crisis of 2007–9, the quote that Lehman Brothers would not have collapsed if it had been “Lehman Sisters” has been attributed to European commissioner Viviane Reding and former UK minister Harriet Harman among others. This section seeks to make the case for and against board diversity based on theoretical grounds as well as the rather limited evidence to date that has examined the effects of more diverse bank boards in the banking industry.

5.5.1  Is There a Case for Board Diversity? The case for diversity in the boardroom essentially centers around two main types of arguments: ethical and economic. Ethical arguments regard board diversity as a desirable end in itself and emphasize that it is inequitable to exclude certain groups from corporate elites on the basis of gender, race, or other non-performance-related characteristics (Singh, Vinnicombe, and Johnson, 2001). In the same vein, promoting board diversity is one means to empower constituencies of society that have historically been excluded from positions of power. Therefore, the concept of board diversity is linked to the notion of equality of representation and, ultimately, to the ideal of “fair” outcomes in society

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Corporate Governance and Culture in Banking   143 (Brammer, Millington, and Pavelin, 2007). It follows from this that diverse boards create legitimacy and improve a firm’s bargaining power vis-à-vis its various stakeholders. As regards the economic case for board diversity, a central argument is that diversity enhances the functional abilities of a board, particularly its ability to engage in complex problem-solving, strategic decision-making, and management monitoring (Forbes and Milliken, 1999). Boards may be viewed as a knowledge-based asset that creates value for shareholders by linking an organization to its external environment (Pfeffer and Salancik,  1978). For example, board diversity expands the networks of existing board members and helps place firms in a network of other firms. This network may lead firms to benefit from improved access to their various external constituents (see Hillman, Cannella, and Paetzold, 2000). Specifically, board networks may provide access to capital, a nation’s business elite, and—in the case of a regulated industry such as banking—industry regulators (Macey and O’Hara, 2003). As well as placing a firm within a network of external contacts, board diversity may improve the internal workings of the board. Owing to their idiosyncratic experiences and values, diverse board members bring privileged economic resources to organizations that help them comprehend a firm’s dynamic industry context (Hambrick and Mason, 1984). For example, the presence of knowledge and specific skills that cater to a board’s specialized needs may further an organization’s understanding of its marketplace and thus improve corporate performance when a board matches its diversity with that of customers or suppliers. However, calls by policymakers to appoint directors with more sector-specific knowledge run contrary to recent attempts by banks to increase the diversity of their boards. However, there may also be costs associated with board diversity. The presence of different viewpoints on less homogeneous boards may cause coordination problems (Forbes and Milliken, 1999). Further, diversity may corrode group cohesion and lead to a board whose members are less cooperative, and experience increased emotional conflict. Consistent with this, Adams and Ferreira (2009) show that female board directors engage in more monitoring but are unable to improve performance. The authors argue that too much monitoring causes conflict and lowers overall performance.

5.5.2  Empirical Evidence on Board Diversity in Banking There is little empirical evidence as regards the effects of diversity in banking. However, the work that has been done to date is interesting because it shows that gender, education, and director characteristics do indeed affect performance and risk-taking in the banking industry. Since the banking sector is relatively opaque, complex, and skillintensive, education and other director characteristics that may correlate with abilities could be particularly important in the banking sector. Beck, Behr, and Guettler (2013) analyze gender differences in the performance of loan officers. Consistent with the view that female loan officers make more cautious

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144   The Theory of Banking decisions, the authors show that default rates for loans originated by female loan officers tend to be lower than for those originated by male loan officers. Berger, Kick, and Schaeck (2014) link changes in board composition to measures of bank portfolio risk. Specifically, the authors relate board-level measures of age, gender, and education (the latter measured by the fraction of directors on the board holding a PhD) to the proportion of risk-weighted assets on a bank’s balance sheet. The authors show that younger executive teams and teams with more females take more portfolio risks. The authors show this is due to female directors being on average less experienced than male appointments and less experienced directors taking on additional risks. As regards board diversity, Hagendorff and Keasey (2012) measure the value of board diversity in the US banking industry. They employ a sample of bank mergers and find positive announcement returns to mergers approved by boards whose members are diverse in terms of their occupational background. By contrast, Erkens, Hung, and Matos (2012) do not find a significant relationship between the financial experience of board members and firms’ stock returns during the crisis. Nguyen, Hagendorff, and Eshraghi (2015b) examine the announcement effects of new bank director appointments and find that age, education, and prior experience of executive directors create shareholder wealth in the US banking sector. In contrast, gender, experience outside the banking sector, and a PhD degree do not have measurable market returns. In addition, the appointment of directors who hold non-executive directorships with an unaffiliated firm at the time of the appointment attracts negative returns, consistent with the view that these directors are too busy to be effective monitors. In a rare glimpse at some of the more mixed results linked to board diversity, GarcíaMeca, García-Sánchez, and Martínez-Ferrero (2015) show that different measures of diversity produce different value effects. García-Meca et al. study the effects of diversity on boards in terms of gender and nationality in an international sample. The authors find that while diversity in gender is associated with higher bank valuations, diversity in terms of nationality is associated with lower valuations. In summary, while the ethical arguments for board diversity appear strong, the economic case for board diversity has yet to stand on more solid empirical grounds. Therefore, more work needs to be done to establish stronger causal links between who the members of the board are and corporate outcomes such as bank risk and returns.

5.6  Culture in Banks Much of the corporate governance literature sees the role of governance as incentivizing and monitoring the behavior of individual agents. However, it is a widely held view that bank failures are not isolated events that can be attributed to a small number of individuals. Instead, it seems probable that there are systematic issues, in some cases condoned and perhaps tacitly encouraged by the culture prevailing in some banks. In other words, institutional culture—whether good or bad—could be contagious (Song and Thakor, forthcoming).

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Corporate Governance and Culture in Banking   145 A Group of Thirty (2015) report explains that “culture . . . creates a consistent framework for behaviors and business practices.” Culture, like governance, shapes the behavior of economic agents but does so in ways that are less targeted. A bank’s culture will, therefore, affect large parts of a bank at the same time. Given the high leverage of banking firms and concerns over excessive risk-taking incentives for shareholders, a bank’s culture can be an important governance device. Studying culture is also important because of a number of high-profile misconduct cases that have put pressure on the reputation of the sector for professional and ethical conduct. For instance, regulators have taken record numbers of enforcement actions against banks in recent years to require them to take corrective measures against misconduct cases (see Nguyen, Hagendorff, and Eshraghi, 2015a). Among the banks engulfed in misconduct cases are various high-profile institutions. For instance, JPMorgan faced several enforcement actions related to credit card fraud, money laundering, and internal accounting controls over the past few years. This also matters because misconduct cases are costly to bank investors with the fines imposed often outweighed by substantial reputational losses for offending banks. In many ways, the recent surge in bank misconduct cases is surprising. One explanation for misconduct holds that when a CEO has too much authority within the firm, misconduct is one potential outcome. However, by most accounts, oversight of CEO decision-making has improved markedly in recent years. Data from Riskmetrics show that eight out of ten members of US bank boards are classified as independent in 2012, up from around half in 2000. With increasing levels of independence, one would expect bank boards to be more effective in preventing a culture that is linked to misconduct. However, far from a declining trend, the average annual number of enforcement actions has increased from 5 to 28 over the same period. The rise in bank misconduct cases under increasingly more independent boards is consistent with the view that salient factors around culture are important in shaping risk-taking. However, the focus on culture (whether based on theory or empirical work) is relatively new to the literature. The discussion below distinguishes between the effects of culture at an institutional level and the personally held cultural values of individuals.

5.6.1  Institutional Culture Song and Thakor (forthcoming) develop a model in which bank culture has two primary effects. Culture helps match managers to banks with similar risk attitudes, and culture is contagious. That is, a safety-oriented culture in some banks causes other banks also to adopt a more safety-oriented culture. On an empirical level, measuring bank culture and linking it to some observed outcome is challenging. However, even where culture is not the focus of existing research, the results of a number of studies already point to the existence of a persistent risk culture within some banks (e.g., Fahlenbrach, Prilmeier, and Stulz, 2012; Ellul and Yerramilli, 2013). Fahlenbrach, Prilmeier, and Stulz (2012) show that a bank’s stock return performance during the 1998 crisis predicts its stock return performance and probability of failure

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146   The Theory of Banking during the Great Recession. Intriguingly, this finding is independent of whether or not banks have the same CEO during both crisis periods, suggesting the presence of a risk culture that is persistent across time. Ellul and Yerramilli (2013) study the relationship between risk culture practices and tail risk for the largest 100 US banks between 1995 and 2010. They develop a risk management culture index based on five variables related to the strength of a bank’s risk management. Their findings show that banks with higher index values in 2006 were less risky and performed better while they also had better operating and stock return performance during the financial crisis years. Further, Popadak (2014) and Fiordelisi and Ricci (2014) are part of an emerging stream of literature that attempts to quantify corporate culture outside the banking industry. Popadak uses employee reviews collected by career intelligence firms where employees self-report aspects of corporate culture, firm values, and the workplace environment. Fiordelisi and Ricci apply textual analysis to financial (10-K) filings. They adopt Cameron et al.’s (2006) four dimensions of corporate culture by measuring what the authors call the “semantic content” in financial filings. The authors identify the frequency of synonyms in 10-K statements that connote collaboration, competition, control, and creation. In an application of Fiordelisi and Ricci’s (2014) framework for corporate culture to the banking industry, Nguyen, Nguyen, and Sila (2019) find that banks with a corporate culture that emphasizes aggressive competition are associated with riskier lending practices. That is, these banks display higher loan approval rates, lower borrower quality, and fewer covenant requirements. Such banks also incur larger loan losses and make larger contributions to systemic risk. Nguyen, Nguyen, and Sila (2019) therefore provide direct empirical evidence of the importance of culture for banks’ policy choices and risk.

5.6.2  Cultural Values of Senior Managers Corporate culture matches managers to banks with similar risk attitudes (Song and Thakor, forthcoming). The values held by senior management should, therefore, be closely aligned with those of the banks that managers choose to work for. In the empirical literature on personally held cultural attitudes, the general view is that cultural values are deeply rooted and slow moving. For instance, studies document that the descendants of immigrants show a degree of cultural distinctiveness over several subsequent generations (e.g., Fernández, and Fogli, 2009). For instance, US immigrants’ family living arrangements or views on the role of women in society parallel those found in the home countries of their ancestors for several generations. Nguyen, Hagendorff, and Eshraghi (2018) conduct a study that identifies the cultural values of senior managers in US banks. The authors track the family trees of US CEOs and focus on CEOs who are the children or grandchildren of immigrants. While these CEOs are exposed to the same legal, social, and institutional influences as other US-born

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Corporate Governance and Culture in Banking   147 CEOs, they possess a cultural heritage that is different from those of other CEOs. Specifically, the cultural preferences and beliefs of these CEOs are likely to bear the cultural mark of the countries from which their parents or grandparents have emigrated. Nguyen, Hagendorff, and Eshraghi (2018) find banks led by CEOs who are second- or third-generation immigrants are associated with higher profitability compared with the average firm. This effect weakens over successive immigrant generations and cannot be detected for top executives apart from the CEO. Additional analysis attributes this effect to various cultural values that prevail in a CEO’s ancestral country of origin. Nguyen, Hagendorff, and Eshraghi (2018) trace the performance effect linked to “immigrant CEOs” to the cultural values that prevail in the country of a CEO’s ancestors. Using a broad range of sixteen cultural values, they find that most cultural dimensions explain competitive performance. Specifically, cultural values that enter their analysis significantly broadly contrast group- versus self-oriented cultures and how comfortable members of a culture are with uncertain future outcomes. When competition intensifies, bank performance is positively related to the cultural dimensions restraint, long-term orientation, and uncertainty avoidance. The key finding of Nguyen, Hagendorff, and Eshraghi (2018)—that personally held values are reflected in the actions and performance of banks—confirm the view that the risk culture of banks and the individuals who work for them are closely aligned (see Song and Thakor, forthcoming).

5.7  Policy Implications and Conclusions This chapter surveys the literature on the corporate governance of banking firms with a particular focus on the compensation arrangements of bank executives, the composition of the board of directors, and the risk culture in banks. One of the main conclusions of this chapter is that the unique features of banks should lead to unique governance arrangements for the banking industry. For instance, given the high leverage of banks, pay incentives should align managers more with creditors than shareholders in the banking industry compared with other sectors. However, US-based evidence suggests that, compared with CEOs in non-financial firms, CEOs in the banking industry have been more aligned with equity holders than debtholders. Equally, and as a direct result of the high leverage and the resulting importance of bank creditors in the financing of banks, creditors should be given a more prominent role in the corporate governance of banks. At present, equity holders control the key governance mechanisms of banks such as the board of directors (shareholders have the exclusive power to appoint and remove directors) and set the remuneration of senior management just like in any other industry. One possibility would be to allow for creditor representation on bank boards. The intuition behind such an initiative would be

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148   The Theory of Banking that, if the capital structure of banks is different from non-financial firms, the governance structure within a bank should reflect this. While creditor representation on bank boards is at odds with the principle of proportional shareholder representation on boards (“one share one vote”), it is important to bear in mind that a number of companies have long represented stakeholders other than shareholders on the board. For instance, Germany’s Mitbestimmungsgesetz (Codetermination Act) mandates that half of the board seats at large German corporations are reserved for employee representatives. One possibility would be to allow for a sliding scale of creditor representation starting beyond a threshold level of leverage and increasing with higher leverage up to a certain point. This would ensure that creditor representation would increase in line with bank leverage and give creditors the opportunity to exert more influence over governance aspects such as executive director appointments, risk management, and remuneration policy. Overall, the evidence surveyed does not back the conclusion that the global financial crisis of 2007–9 has been brought about by a lack of shareholder-oriented corporate governance and that, following this line of argument, future banking crises can be prevented by improving the influence that shareholders have on the corporate governance of banks. If anything, the literature surveyed in this chapter shows that shareholder-oriented governance leads to risky outcomes and has therefore contributed to unsustainable bank policies that played a major role in the build-up of the crisis. This chapter also highlights two important lines for future research into the corporate governance of banks. First, future research should do more to understand the effectiveness of individual directors and their characteristics. Empirical work has only recently begun to examine issues around individual director characteristics and board heterogeneity. Some findings are consistent with the view that it matters who runs banks, but not all these findings are in line with current policy discussions around board composition. For instance, empirical support for the view that female board participation or more banking sector experience lowers risk (as is often asserted) is weak at best. Second, research into the corporate governance of banks has so far been overly focused on the board of directors. While no doubt a key governance device, there are other institutions outside the board that are important for reducing agency conflict over bank risk. For instance, studying the risk culture inside banks or studying middle- and high-ranking management instead of the board level of executives can provide useful avenues for further research. The corporate governance of banks is an important topic both for investors and for policymakers. However, much of what is known about the governance of banks has relied on replicating research based on the non-financial sector without adequately taking the unique features of banks into account. However, these unique features of banks call for a more profound rethink of the corporate governance of banks, one that centers around debtholders rather than equity holders, to bring forward the literature on this topic and to base the impending regulatory changes to the banking sector on a solid empirical footing.

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Corporate Governance and Culture in Banking   149

References Adams, R. and Mehran, H. (2003). “Is Corporate Governance Different for Bank Holding Companies?” Economic Policy Review, 9, 123–42. Adams, R.  B. and Ferreira, D. (2009). “Women in the Boardroom and Their Impact on Governance and Performance,” Journal of Financial Economics, 94, 291–309. Amihud, Y. and Lev, B. (1981). “Risk Reduction as a Managerial Motive for Conglomerate Mergers,” Bell Journal of Economics, 12, 605–17. Balachandran, S., Kogut, B., and Harnal, H. (2010). “The Probability of Default, Excessive Risk, and Executive Compensation: A Study of Financial Services Firms from 1995 to 2008,” Unpublished Working Paper, Columbia University. Bebchuk, L. A. and Spamann, H. (2009). “Regulating Bankers’ Pay,” Georgetown Law Journal, 98, 247–87. Beck, T., Behr, P., and Guettler, A. (2013). “Gender and Banking: Are Women Better Loan Officers?” Review of Finance, 17, 1279–321. Beltratti, A. and Stulz, R. M. (2012). “The Credit Crisis Around the Globe: Why did Some Banks Perform Better During the Credit Crisis?” Journal of Financial Economics, 105(1), 1–17. Bennett, R., Guntay, L., and Unal, H. (2015). “Inside Debt, Bank Default Risk and Performance During the Crisis,” Journal of Financial Intermediation, 24, 487–513. Berger, A.  N., Herring, R.  J., and Szegö, G.  P. (1995). “The Role of Capital in Financial Institutions,” Journal of Banking & Finance, 19, 393–430. Berger, A., Imbierowicz, B., and Rauch, C. (2016). “The Roles of Corporate Governance in Bank Failures During the Recent Financial Crisis,” Journal of Money, Credit and Banking, 48, 729–70. Berger, A., Kick, T., and Schaeck, K. (2014). “Executive Board Composition and Bank Risk Taking,” Journal of Corporate Finance, 28, 48–65. Bliss, R. and Rosen, R. (2001). “CEO Compensation and Bank Mergers,” Journal of Financial Economics, 61, 107–38. Board of Governors of the Federal Reserve System, Federal Deposit Insurance Corporation, Office of the Comptroller of the Currency, Treasury, and Office of Thrift Supervision. (2010). “Guidance on Sound Incentive Compensation Policies,” June 25, available at: http:// www.fdic.gov/news/news/press/2010/pr10138a.pdf. Bouwens, J. and Kroos, P. (2011). “Target Ratcheting and Effort Reduction,” Journal of Accounting and Economics, 51, 171–85. Brammer, S., Millington, A., and Pavelin, S. (2007). “Gender and Ethnic Diversity Among UK Corporate Boards,” Corporate Governance: An International Review, 15(2), 393–403. Calomiris, C. W. and Carlson, M. (2016). “Corporate Governance and Risk Management at Unprotected Banks: National Banks in the 1890s,” Journal of Financial Economics, 119, 512–32. Cameron, K.  S., Quinn, R.  E., DeGraff, J., and Thakor, A.  V. (2006). Competing Values Leadership: Creating Value in Organizations. Cheltenham: Edward Elgar Publishing. Coles, J. L., Daniel, N. D., and Naveen, L. (2006). “Managerial Incentives and Risk-taking,” Journal of Financial Economics, 79, 431–68. Datta, S., Iskandar-Datta, M., and Raman, K. (2001). “Executive Compensation and Corporate Acquisition Decisions,” Journal of Finance, 56, 2299–336. DeYoung, R., Peng, E., and Yan, M. (2013). “Executive Compensation and Business Policy Choices at US Commercial Banks,” Journal of Financial and Quantitative Analysis, 48, 165–96.

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150   The Theory of Banking Diamond, D. and Dybvig, P. (1983). “Bank Runs, Deposit Insurance, and Liquidity,” Journal of Political Economy, 99, 689–721. Diamond, D. and Rajan, R. (2001). “Liquidity Risk, Liquidity Creation, and Financial Fragility: A Theory of Banking,” Journal of Political Economy, 109, 287–327. Duru, A., Mansi, S. A., and Reeb, D. M. (2005). “Earnings-Based Bonus Plans and the Agency Costs of Debt,” Journal of Accounting and Public Policy, 24, 431–47. Edmans, A. and Liu, Q. (2011). “Inside Debt,” Review of Finance, 11, 75–102. Ellul, A. and Yerramilli, V. (2013). “Stronger Risk Controls, Lower Risk: Evidence from US Bank Holding Companies,” Journal of Finance, 68, 1757–803. Erkens, D.  H., Hung, M., and Matos, P. (2012). “Corporate Governance in the 2007–2008 Financial Crisis: Evidence from Financial Institutions Worldwide,” Journal of Corporate Finance, 18(2), 389–411. Fahlenbrach, R. and Stulz, R. (2011). “Bank CEO Incentives and the Credit Crisis,” Journal of Financial Economics, 99, 11–26. Fahlenbrach, R., Prilmeier, R., and Stulz, R. (2012). “This Time is the Same: Using Bank Performance in 1998 to Explain Bank Performance During the Recent Financial Crisis,” Journal of Finance, 67, 2139–85. Federal Reserve Bank. (2010). “Guidance on Sound Incentive Compensation Policies,” Board of Governors of the Federal Reserve System, Washington, DC. Fernández, R. and Fogli, A. (2009). “Culture: An Empirical Investigation of Beliefs, Work, and Fertility,” American Economic Journal: Macroeconomics, 1, 146–77. Financial Stability Board (2009). “Principles for Sound Compensation Practices,” Basel, Switzerland, available at: http://www.financialstabilityboard.org/publications/r_0904b.pdf. Fiordelisi, F. and Ricci, O. (2014). “Corporate Culture and CEO Turnover,” Journal of Corporate Finance, 28, 66–82. Forbes, D. P. and Milliken, F. J. (1999). “Cognition and Corporate Governance: Understanding Boards of Directors as Strategic Decision-Making Groups,” The Academy of Management Review, 24(3), 489–505. García-Meca, E., García-Sánchez, I. M., and Martínez-Ferrero, J. (2015). “Board Diversity and its Effects on Bank Performance: An International Analysis,” Journal of Banking & Finance, 53, 202–14. Group of Thirty (2015). “Banking Conduct and Culture: A Call for Sustained and Comprehensive Reform,” monograph, Washington, DC, July. Guay, W.  R. (1999). “The Sensitivity of CEO Wealth to Equity Risk: An Analysis of the Magnitude and Determinants,” Journal of Financial Economics, 53, 43–71. Haan, J.  De, and Vlahu, R. (2016). “Corporate Governance of Banks: A Survey,” Journal of Economic Surveys, 30, 228–77. Hagendorff, J. and Keasey, K. (2012). “The Value of Board Diversity in Banking: Evidence from the Market for Corporate Control,” The European Journal of Finance, 18, 41–58. Hagendorff, J. and Vallascas, F. (2011). “CEO Pay Incentives and Risk-Taking: Evidence from Bank Acquisitions,” Journal of Corporate Finance, 17, 1078–95. Hambrick, D. C. and Mason, P. A. (1984). “Upper Echelons: The Organization as a Reflection of its Top Managers,” Academy of Management Review, 9, 193–206. Harjoto, M. A. and Mullineaux, D. J. (2003). “CEO Compensation and the Transformation of Banking,” Journal of Financial Research, 26, 341–54. Hermalin, B. and Weisbach, M. (2003). “Boards of Directors as an Endogenously Determined Institution: A Survey of the Economic Literature,” Economic Policy Review, 9, 7–26.

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Corporate Governance and Culture in Banking   151 Hillman, A. J., Cannella, A. A., and Paetzold, R. L. (2000). “The Resource Dependence Role of Corporate Directors: Strategic Adaptation of Board Composition in Response to Environmental Change,” Journal of Management Studies, 37, 235–56. Indjejikian, R., Matějka, M., Merchant, K., and Van Der Stede, W. (2014). “Earnings Targets and Annual Bonus Incentives,” The Accounting Review, 89, 1227–58. Jensen, M. C. and Meckling, W. H. (1976). “Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure,” Journal of Financial Economics, 3, 305–60. John, T.  A. and John, K. (1993). “Top-management Compensation and Capital Structure,” Journal of Finance, 48, 949–74. Kleymenova, A. and Tuna, I. (2017). “Regulation of Compensation and Systemic Risk: Evidence from the UK,” Chicago Booth Research Paper No. 16–07, University of Chicago, Chicago, IL. Laeven, L. and Levine, R. (2009). “Bank Governance, Regulation, and Risk-taking,” Journal of Financial Economics, 93, 259–75. Macey, J. R. and O’Hara, M. (2003). “The Corporate Governance of Banks,” Economic Policy Review—Federal Reserve Bank of New York, 9(1), 91–107. Mehran, H. and Rosenberg, J.  V. (2007). “The Effect of Employee Stock Options on Bank Investment Choice, Borrowing, and Capital,” Federal Reserve Bank of New York Staff Report No. 305. Minnick, K., Unal, H., and Yang, L. (2011). “Pay for Performance? CEO Compensation and Acquirer Returns in BHCs,” Review of Financial Studies, 24, 439–72. Murphy, K. J. (2000). “Performance Standards in Incentive Contracts,” Journal of Accounting and Economics, 30, 245–78. Nguyen, D. D., Hagendorff, J., and Eshraghi, A. (2015a). “Can Bank Boards Prevent Misconduct?” Review of Finance, 20, 1–36. Nguyen, D. D., Hagendorff, J., and Eshraghi, A. (2015b). “The Value of Executive Director Heterogeneity in Banking: Evidence from Appointment Announcements,” Corporate Governance: An International Review, 23, 112–28. Nguyen, D. D., Hagendorff, J., and Eshraghi, A. (2018). “Does a CEO’s Cultural Heritage Affect Performance Under Competitive Pressure?” Review of Financial Studies, 31, 97–141. Nguyen, D. D., Nguyen, L., and Sila, V. (2019). “Does Corporate Culture Affect Bank RiskTaking? Evidence from Loan-Level Data,” British Journal of Management, 30(1), 106–33. Noe, T. H., Rebello, M. J., and Wall, L. D. (1996). “Managerial Rents and Regulatory Intervention in Troubled Banks,” Journal of Banking & Finance, 20, 331–50. Pathan, S. (2009). “Strong Boards, CEO Power and Bank Risk-taking,” Journal of Banking & Finance, 33, 1340–50. Pfeffer, J. and Salancik, G.  R. (1978). The External Control of Organizations: A Resource Dependence Perspective (New York: Harper & Row). Popadak, J. (2014). “A Corporate Culture Channel: How Increased Shareholder Governance Reduces Firm Value,” Working Paper, Duke University. Rajgopal, S. and Shevlin, T. (2002). “Empirical Evidence on the Relation Between Stock Option Compensation and Risk-taking,” Journal of Accounting and Economics, 33, 145–71. Singh, V., Vinnicombe, S., and Johnson, P. (2001). “Women Directors on Top UK Boards,” Corporate Governance: An International Review, 9, 206–16. Smith, C.  W. and Stulz, R.  M. (1985). “The Determinants of Firms’ Hedging Policies,” The Journal of Financial and Quantitative Analysis, 20, 391–405. Song, F. and Thakor, A. (forthcoming). “Bank Culture,” Journal of Financial Intermediation.

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152   The Theory of Banking Srivastav, A., Armitage, S., Hagendorff, J., and King, T. (2018). “Better Safe Than Sorry? CEO Inside Debt and Risk-taking in Bank Acquisitions,” Journal of Financial Stability, 36, 208–24. Sundaram, R. K. and Yermack, D. L. (2007). “Pay Me Later: Inside Debt and its Role in Managerial Compensation,” Journal of Finance, 62, 1551–88. Tung, F. and Wang, X. (2012). “Bank CEOs, Inside Debt Compensation, and the Global Financial Crisis,” Working Paper. Vallascas, F. and Hagendorff, J. (2013). “CEO Bonus Compensation and Bank Default Risk: Evidence from the US and Europe,” Financial Markets, Institutions & Instruments, 22, 47–89. Wei, C. and Yermack, D. (2011). “Investor Reactions to CEOs’ Inside Debt Incentives,” Review of Financial Studies, 24, 3813–40.

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chapter 6

Pr i vate I n for m ation a n d R isk M a nagem en t i n Ba n k i ng Linda Allen and Anthony Saunders

6.1 Introduction If you open the vaults of any bank, you might think you would know what you would find there. You would be wrong. What is really there, hidden behind the stacks of currency, is the bank’s inventory of risk. The bank exists to take on the risks of its customer base. By offering its clients risk management products, the bank absorbs an inventory of risk that is contributed with each transaction. The bank prices those products by estimating its costs of managing the risks inherent in each transaction. Financial institutions are specialists in risk management. Indeed, their primary expertise stems from their ability to both measure and manage risk exposure on their own behalf and on behalf of their clients—either through the evolution of financial market products to shift risks or through the absorption of their clients’ risk into their risk inventory on their own balance sheets. Because financial institutions are risk intermediaries, they maintain an inventory of risk that must be measured carefully so as to ensure that the risk exposure does not threaten the intermediary’s solvency. Thus, accurate measurement of risk is an essential first step for proper risk management, and financial intermediaries, because of the nature of their business, tend to be leading developers of new risk measurement and risk-pricing techniques. When financial institutions misprice risk, however, as was the case of subprime mortgage securities, the size of the risk inventory may overwhelm the financial system’s capacity to absorb risk, thereby resulting in global market failures such as the credit crisis of 2007. For example, banks provided equity and backup lines of credit to the Structured Investment Vehicles (SIVs) that they formed during the build-up of the subprime mortgage

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154   The Theory of Banking securitization bubble. The SIV is a structured operating company that invests in assets that are designed to generate higher returns than the SIV’s cost of funds. Rather than selling the asset-backed securities directly to investors in order to raise cash (as Special Purpose Vehicles (SPVs) do in standard securitizations), the SIV sells bonds or commercial paper to investors in order to raise cash. The SIV then holds the loans purchased from originating banks on its own balance sheet until maturity. These loan assets held by the SIV back the debt instruments issued by the SIV to investors. Thus, in essence the SIV itself becomes an asset-backed security, and the SIV’s short-term commercial paper liabilities are considered an asset-backed commercial paper. Investors buy the SIV’s liabilities (most often, asset-backed commercial paper, ABCP), providing the proceeds for the purchase of longer-term loans from originating banks. The SIV’s debt is backed by the loan portfolio held by the SIV. However, the SIV does not simply pass through the payments on the loans in its portfolio as in a traditional CMO (collateralized mortgage obligation). Indeed, investors have no direct rights to the cash flows on the underlying loans in the portfolio. They are entitled to the payments specified on the SIV’s debt instruments. The SIV’s ABCP obligations carry interest obligations that are independent of the cash flows in the underlying loan portfolio. Thus, in the traditional form of securitization, the SPV only pays out what it receives from the underlying loans in the pool of assets backing the asset-backed securities. In the newer form of securitization, the SIV is responsible for payments on its ABCP obligations, whether or not the underlying pool of assets generates sufficient cash flow to cover those costs. Of course, if the cash flow from the asset pool exceeds the cost of ABCP liabilities, then the SIV keeps the spread and makes a profit. However, if the assets in the underlying pool do not generate sufficient cash flows, the SIV is still obligated to make interest and principal payments on its debt instruments. Further, if investors become concerned about the SIV’s ability to meet their short-term ABCP obligations, they may engage in a “run,” thereby generating what has been often called “rollover risk” or more generally, liquidity risk. The SIV’s operating methodology should seem very familiar to bankers. SIVs are essentially banks minus the regulations, or so-called “shadow banks.” The SIV acts in a similar way to a traditional bank—holding loan assets until maturity and issuing debt instruments (such as ABCP) to fund its asset portfolio. The major difference between an SIV and a traditional bank is that the SIV cannot issue deposits to fund its asset base (i.e., it is not technically a “bank”). However, to the extent that many of these SIVs used commercial paper and interbank loans (such as repurchase agreements)1 to finance their asset portfolios, then they were subject to even more liquidity (or rollover) risk than are traditional banks. This is because in the modern world of banking, sophisticated lenders (so-called suppliers of “purchased funds”) are prone to “run” at the first sign of trouble, whereas depositors are slower to react. That is, interbank lenders and commercial paper 1  A repurchase agreement allows a bank to borrow against collateral (securities) transferred to a counterparty. This transaction is typically reversed within a short time period—from a week to three months. Moreover, the collateral is marked-to-market on a daily basis.

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Private Information and Risk Management in Banking   155 buyers will withdraw funds (or refuse to renew financing) quicker than traditional “core” depositors, who may rely on their bank deposits for day-to-day business dealings or may be protected by government deposit insurance. Thus, the well-publicized problems of the UK’s Northern Rock Bank in August of 2007 were precipitated by the withdrawal of funds by interbank lenders and other purchased fund suppliers. Core depositors represented only approximately 25 percent of Northern Rock’s funded assets. The liquidity risk problem is exacerbated when the SIV relies on short-term sources of funding, such as commercial paper, which must be renewed within nine months, and repurchase agreements, which must be fully backed by collateral at all points in time. Thus, if the value of the portfolio declines due to credit conditions worsening, for example, then the SIVs are forced to sell long-term, illiquid assets at fire-sale prices in order to meet the SIVs’ shortterm debt obligations. Many SIVs were sponsored and originated by banks anxious to remove the risky subprime mortgages (and other obligations) from their balance sheets. The banks and bank regulators believed that these off-balance-sheet SIVs posed little risk to the bank itself. However, most of these SIVs had ABCP programs that were backed with bank lines of credit. When the ABCP market seized up during the summer of 2007, the SIVs took down their lines of credit and, all of a sudden, the risks that were believed to be off the balance sheet came back to haunt the banks. Indeed, one large bank found its assets expanded. The banks were exposed to the risks associated with the poorly underwritten subprime mortgage securities because they were forced to lend to SIVs that had no assets other than these risky securities. Bank shareholders and stakeholders suffered, top executives lost their jobs, global credit markets dried up and the SIV experiment ended—all because risk was improperly measured and priced in the mortgage securities market. Unfortunately, SIVs have recently been resurrected under a different name. In China, “wealth management products” employ a SIV-like structure, and are subject to the same risks. Acharya, Qian, and Yang (2016) document the extreme rollover risks inherent in this shadow-banking activity. Moreover, the implicit guarantees offered to investors in these SIV-like structures increase the fragility of the entire Chinese banking system. Estimates of the size of this unofficial shadow-banking activity are hard to come by. The Bank of China estimated that as of 2012 there were 20,000 wealth management accounts with a total value of 12.14 RMB (Elliott and Yan, 2013). A more conservative estimate puts the aggregate value at 7.1 trillion RMB, which still represented 14 percent of China’s GDP (Xia et al., 2013). Given the contribution of SIVs to the global financial crisis of 2007–9, the continued proliferation of such risky structures in China is cause for concern. Although risk is amorphous and often changes its shape from one form to another, we can delineate several major sources of risk. The first, market risk, includes interest rate risk. Thus, if, for example, interest rates increase unexpectedly, the bank’s cost of funds may increase and the value of its longer-term assets may fall, to the detriment of both the bank’s profitability (net interest margin) and the market value of the bank’s equity. A second source of risk is credit risk. Since the most substantial asset classification on the bank’s balance sheet consists of loans (whether to businesses, residential households, or

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156   The Theory of Banking even sovereign governments), banks face the risk of default or deterioration in the borrower’s credit quality.2 As many of the subprime mortgages in the pools originated in 2005 and 2006 began to show delinquencies as early as one year or less after origination, there were concerns in the market about the credit risk exposure of the securities, despite their AAA and AA credit ratings. A third source of risk, described above in the context of the 2007 credit crisis, is liquidity (or rollover) risk. Banks transform short-term, liquid liabilities (such as demand deposits) into longer-term, illiquid assets (such as loans). If there is a sudden demand for liquidity, the bank will be unable to meet all withdrawal demands because of the costs of selling an illiquid portfolio at fire-sale prices. Another source of risk is operational risk. Banks undertake clearing and custodial transactions on behalf of their customers. Fraud, mismanagement, computer failure, and human error can result in losses to customers, which the bank may have to reimburse in order to protect its reputation. Strategic business errors cause catastrophic losses that may threaten the bank’s viability. Loss of reputation may spell the end of the firm’s independence for a financial institution—as in the case of the venerable Barings Bank. In the context of the credit crisis of 2007, HSBC absorbed $45 billion in assets from its SIVs in order to protect its reputation in the market. Moreover, firms such as Citi, Merrill Lynch, UBS, Bear Stearns, etc. have all had their reputations tarnished by their participation in the subprime mortgage debacle. This brief thumbnail survey of risk exposures highlights the importance of measuring the amount of risk in the bank’s risk inventory on a continual basis. Thus, before we can even talk about risk management, we first have to discuss risk measurement. Section 6.2 of this chapter will describe commonly used models of risk measurement for banks— Value at Risk (VaR) and Expected Shortfall (ES). Only after the bank’s risk exposure is measured can we discuss how to manage that risk. It is a common perception that it was models such as VaR that led to, if not caused, the global financial crisis that began in 2007–8. Flaws in risk measurement models presumably misled banks and other financial institutions, thereby reassuring them by obscuring the actual risk levels in the system. Undoubtedly, there are flaws in the models. However, there is evidence that banks were aware of their extreme risk exposures in 2006. For example, Goldman Sachs actively hedged its mortgage risk exposure months before the crisis broke during the summer of 2007. Most financial institutions, however, ignored the red alert future risk signals sent by their internal models in favor of the lucrative prospects immediately in front of them. Rather than the models failing the financial community, it could be said that it was the financial community that failed the models by failing to respond to signals sent by the models. Indeed, in this chapter, we will show how financial professionals blithely ignored warning signals and took actions that actually exacerbated risk exposure. What if, upon measuring the amount of risk in the bank’s risk inventory, we find that the exposure is too high from the perspective of top management’s risk tolerance? Can banks simply refuse to take on more risk? The answer is no. The business of banking 2  For example, in July 1998, Russia defaulted on its debt, followed by Argentina in 2001.

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Private Information and Risk Management in Banking   157 requires that banks stand ready to absorb the risks of their customers at a price. If customers are willing to pay that price, it is bad business practice to refuse it. Customers will be forced to go elsewhere and it may be impossible to win them back. Instead, the bank should continue to take on their customers’ risk exposures—whether by making loans with credit risk, or absorbing currency risk by offering import/export firms crosscurrency letters of credit, or by executing trust agreements, thereby exposing the bank to operational risk. However, once that risk is placed into inventory, the bank’s risk management team can then decide whether to hold that risk or resell it in the global marketplace. This “risk reselling” is accomplished using financial derivatives. Banks can manage their risk inventory using financial futures, forward contracts, options, and swaps. This is a much more efficient way for the bank to manage risk than disappointing long-standing customers. Thus, risk management takes place almost exclusively using derivatives transactions, rather than balance-sheet adjustments. After reviewing the risk management opportunities available to banks in the derivatives markets in section 6.3, it should be clear that risk measurement and management requires prodigious amounts of information. Section 6.4 discusses the exploitation of private information produced in the course of banking activity. Finally, the chapter concludes in section 6.5 with a discussion of the economic importance of banking sector risk.

6.2  Risk Measurement Risk measurement has preoccupied financial market participants since the dawn of financial history. However, many past attempts have proven to be impractically complex. For example, upon its introduction, Harry Markowitz’s Nobel Prize-winning theory of portfolio risk measurement was not adopted in practice because of its onerous data requirements.3 Indeed, it was Bill Sharpe who, along with others,4 made portfolio theory the standard of financial risk measurement in real world applications through the adoption of the simplifying assumption that all risk could be decomposed into two parts: systematic, market risk and the residual, company-specific or idiosyncratic risk. The resulting Capital Asset Pricing Model theorized that since only undiversifiable market risk is relevant for securities pricing, only the market risk measurement β is necessary, thereby considerably reducing the required data inputs. This model yielded a readily measurable estimate of risk that could be practically applied in a real-time market environment. The

3  Modern portfolio theory is based on Markowitz’s insight that diversification can reduce, but not generally eliminate, risk, thereby necessitating a risk-reward guide to portfolio selection. To estimate the efficient investment frontier in a mean-variance world requires data on expected returns, standard deviations of returns and correlations between returns for every possible pair of financial securities. On the occasion of the fiftieth anniversary of the publication of the seminal Markowitz (1952) paper, Rubinstein (2002) offers an interesting discussion of the development of modern portfolio theory by Markowitz and others. 4  For example, Sharpe’s (1963) paper was followed by Mossin (1968).

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158   The Theory of Banking only problem was that β proved to have only a tenuous connection to actual security returns, thereby casting doubts on β’s designation as the true risk measure.5 With β questioned, and with asset pricing in general being at a bit of a disarray with respect to whether the notion of “priced risk” is really relevant, market practitioners searched for a replacement risk measure that was both accurate and relatively inexpensive to estimate. Despite the consideration of many other measures and models, Value at Risk (VaR) has been widely adopted and subject to considerable criticism. Part of the historical reasons leading to the widespread adoption of VaR was the decision of JP Morgan in 1994 to create a transparent VaR measurement model, called RiskMetrics, in response to Basel’s add-on market adjustment to the 8 percent risk-based capital requirement for credit risk which fully came into effect in 1992. RiskMetrics was supported by a publicly available database containing the critical inputs required to estimate the model.6 In the past, many of the risk measurement models were private, internal models, developed in-house by financial institutions. Internal models were used for risk management in its truest sense. Indeed, the VaR tool was complementary to many other internal risk measures—such as RAROC, developed by Bankers Trust in the 1970s.7 However, market forces during the late 1990s created conditions that led to the evolution of VaR as a dominant risk measurement tool for financial firms. The US financial environment during the 1990s was characterized by the de jure separation of commercial banking and investment banking that dating back to the Glass– Steagall Act of 1933.8 However, these restrictions were undermined in practice by Section 20 affiliates (that permitted commercial bank holding companies to engage in investment banking activities up to certain limits), mergers between investment and commercial banks, and commercial bank sales of some “insurance” products, especially annuities. Thus, commercial banks competed with investment banks and insurance companies to offer financial services to clients in an environment characterized by globalization, enhanced risk exposure, and rapidly evolving securities and market procedures. Con­ cerned about the impact of the increasing risk environment on the safety and soundness of the banking system, bank regulators instituted (in 1992) risk-adjusted bank capital requirements that levied a capital charge for both on- and off-balance-sheet credit risk exposures. 5  Dissatisfaction with the β measure began as early as Douglas (1969), with mounting doubts leading to Roll’s (1977) paper. The practitioner world closely followed the academic debate with articles such as Wallace’s (1980). Beta’s death knell was sounded by Fama and French’s (1992) paper that found that after controlling for firm size and the market-to-book ratio, the firm’s β had no statistically significant power to explain returns on the firm’s equity. 6  In their introduction, Mina and Xiao (2001) stress that RiskMetrics is not strictly a VaR model, although it can be used to estimate a VaR model. RiskMetrics’ critical role in the dissemination of VaR among financial market practitioners stems in large part from the availability of real time data on financial market fluctuations provided freely in the public domain. Recognizing that value added, RiskMetrics has currently formed a separate data service, DataMetrics which covers almost 100,000 data series. 7  RAROC (risk-adjusted return on capital) models are risk-sensitive measures of economic performance that can be used to allocate risk capital within the firm. See chapter 11 of Saunders and Allen (2010). 8  The Gramm–Leach–Bliley Act of 1999 permitted the creation of financial service holding companies that could include commercial banking, investment banking, and insurance subsidiaries under a single corporate umbrella, thereby effectively repealing the Glass–Steagall Act.

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Private Information and Risk Management in Banking   159 Risk-adjusted capital requirements initially applied only to commercial banks, although insurance companies9 and securities firms had to comply with their own reserve and haircut regulations as well as with market forces that demanded capital cushions against insolvency based on economic model-based measures of exposure—so-called economic capital. Among other shortcomings of the BIS capital requirements were their neglect of diversification benefits, in measuring a bank’s risk exposure. Thus, regulatory capital requirements tended to be higher than economically necessary, thereby undermining commercial banks’ competitive position vis-à-vis largely unregulated investment banks. To compete with other financial institutions, commercial banks had the incentive to track economic capital requirements more closely, notwithstanding their need to meet regulatory capital requirements. The more competitive the commercial bank was in providing investment banking activities, for example, the greater its incentive to increase its potential profitability by increasing leverage and reducing its capital reserves. JP Morgan was one of a handful of globally diversified commercial banks that were in a special position relative to the commercial banking sector on the one hand and the investment banking sector on the other. These banks were caught in between, in a way. On the one hand, from an economic perspective, these banks could be thought of more as investment banks than as commercial banks, with large market risks due to trading activities, as well as advisory and other corporate finance activities. On the other hand, this group of globally diversified commercial banks was holding a commercial banking license, and, hence, was subject to commercial bank capital adequacy requirements. This special position gave these banks, JP Morgan being a particular example, a strong incentive to come out with an initiative to remedy the capital adequacy problems that they faced. Specifically, the capital requirements for market risk in place were not representative of true economic risk, due to their limited account of the diversification effect. At the same time, competing financial institutions, in particular investment banks such as Merrill Lynch, Goldman Sachs and Salomon Brothers, were not subject to bank capital adequacy requirements. As such, the capital they held for market risk was determined more by economic and investor considerations than by regulatory requirements. This allowed these institutions to bolster significantly more impressive ratios such as return on equity (ROE) and return on assets (ROA) compared with banks with a banking charter. In response to the above pressures, JP Morgan took the initiative to develop an open architecture (rather than in-house) methodology, called RiskMetrics. RiskMetrics quickly became the industry benchmark in risk measurement. The publication of RiskMetrics was a pivotal step, moving regulators toward adopting economic capital-based models in measuring a bank’s capital adequacy. Indeed, bank regulators worldwide allowed (sophisticated) commercial banks to measure their market risk exposures using internal models that were often VaR-based. The market risk amendments to the Basel accord made in-house risk measurement models a mainstay in the financial sector. Financial institutions worldwide moved forward with this new approach and never looked back. 9  Insurance regulators in the US adopted their own risk-based capital requirements for life and propertycasualty insurers in the mid-to-late 1990s.

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160   The Theory of Banking The question that is the basis for VaR as we know it today is “how much can we lose on our trading portfolio by tomorrow’s close?” Note that this is a risk measurement, not a risk management question. Also, it is not concerned with obtaining a portfolio position to maximize the profitability of the bank’s traded portfolio subject to a risk constraint, or any other optimization question. Instead, this is a pure question of risk measurement. VaR takes a statistical or probabilistic approach to answering Mr. Weatherstone’s question of how much could be lost on a “bad day.” That is, we define a “bad day” in a statistical sense, such that there is only an x percent probability that daily losses will exceed this amount given a distribution of all possible daily returns over some recent past period. That is, we define a “bad day” so that there is only an x percent probability of an even worse day. Moreover, VaR models can be used to estimate the expected average loss on such bad days (the expected shortfall). Implementing VaR models requires estimation of a probability distribution of returns (or losses) so that we can measure the cut-off point that designates the loss that will be exceeded with an x percent probability on any given day. The simplest forms of RiskMetrics, for example, the Rule 415 model, assume that financial securities are normally distributed. This makes estimation of VaR quite easy because all we have to do is estimate the mean and standard deviation of securities prices using historical data. Unfortunately, it is often the case that the simplicity of the VaR measures used to analyze the risk of the equity portfolio, for example, is in large part obtained with assumptions not supported by empirical evidence. The most important (and problematic) of these assumptions is that daily equity returns are normally distributed, ignoring the asymmetric payoff structures of many financial instruments such as options and the “fat-tailed” risk (i.e., enhanced probabilities of extreme losses) observed in the financial crisis. In general, there is a tradeoff between the accuracy of assumptions and ease of calculation, such that greater accuracy is often accompanied by greater complexity.10 This problem of complexity is exacerbated when there is a paucity of data available to be used to estimate the model’s fundamental assumptions. Market risk exposure arises from unexpected security price fluctuations, estimated using long histories of daily price fluctuations. Unfortunately, measuring a loan’s credit risk exposure, for example, is far more difficult. Since loans are not always traded, and even when traded they trade infrequently, there is often no history of daily price fluctuations available to build a (loan) loss distribution. Moreover, credit events such as default or rating downgrades are rare, often non-reoccurring events. Thus, we often have insufficient statistical power to estimate a daily VaR for credit risk exposure; that is, data limitations create special challenges in adapting VaR techniques to estimate credit risk exposure. However, we can use VaR techniques to estimate losses due to credit events if the time interval we consider is longer. Indeed, the convention in the new generation of credit risk models is to assume that the credit risk time horizon is one year, thereby estimating losses during the next year if it is a “bad” year, defined according to a specified VaR level; for example, a 99.5 percentile VaR (i.e., x percent equals 0.5 percent) estimates the minimum losses in the 10  For specific methodologies used to estimate VaR models, see Allen, Boudoukh, and Saunders (2004).

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Private Information and Risk Management in Banking   161 worst five years out of a 1,000. A VaR model, such as CreditMetrics, measures the probability that the credit rating of any given debt security will change over the course of the one year credit horizon. The tabulation of potential changes in credit ratings— known as the credit migration matrix—considers the entire range of credit events, including upgrades and downgrades as well as actual default. Historical migrations of publicly traded debt instruments, such as corporate bonds, are used to tabulate the annual probability of any given change in credit risk. These loss probabilities are then applied to specific debt instruments, such as untraded loans, to calculate the loan portfolio’s VaR. Because of the problems in applying the VaR model to credit risk assessment, banks often use other credit risk measurement models. There has been widespread adoption of credit scoring models in all arenas of bank lending—mortgage lending, commercial lending, credit card and revolving debt, etc. Credit scoring models (e.g., FICO scores) apply discriminant analysis to a class of borrowers by identifying certain key factors that determine the probability of default (as opposed to repayment), and combine or weight them into a quantitative score. In some cases, the score can be literally interpreted as a probability of default; in others, the score can be used as a classification system: it places a potential borrower into either a good or a bad group, based on a score and a cutoff point. VaR models also have the potential to measure operational risk exposure. VaR measures losses from unexpected, extreme shocks that are in the tail of the probability distribution (i.e., at the end of outcomes that are extremely unlikely to occur). Thus, the probability of a VaR-sized event (x percent) is very small (i.e., 5 percent or 1 percent or 0.5 percent). However, when these improbable events occur, they are catastrophic for the firm and typically result in insolvency. Indeed, Allen and Bali (2007) find that operational risk events are likely to be the cause of large unexpected catastrophic losses. They use a comprehensive approach to measuring operational risk that includes reputational risk and strategic business risk and shows that approximately 18 percent of financial institutions’ returns represent compensation for operational risk. Finally, it should be noted that because of the fat-tailed risks (in violation of assumptions of normality) with observed returns falling in the range of between six to nine standard deviations from the mean, the Basel III regulations adopted in 2012 have incorporated the expected shortfall as the appropriate measure of market risk for capital requirements. Conceptually, the bank looks at the worst daily returns earned on an asset over the previous 100 days, and the worst daily returns in the 100 days prior (101 to 200 days before the present) and the worst daily returns in the 100 days prior (201 to 300 days before the present). A simple measure of the expected shortfall is simply the average of these three worst returns. For example, if the worst daily return in the past 100 days was –3 percent; and the prior 100 days’ worst return was –3 percent; and the prior 100 days’ worst return was –6 percent, then the expected shortfall would average these three returns for a value of –4 percent. Often, because of the fatness of tails in the return distribution, the losses associated with this expected shortfall measure will be greater than the losses associated with the 99 percent VaR. In the illustration, therefore, the loss of –4 percent from the expected shortfall exceeds the VaR loss of –3 percent. Thus, the

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162   The Theory of Banking expected shortfall is a more conservative measure of bank risk than VaR under the normal probability distribution assumption.

6.3  Risk Management Suppose that the VaR or expected shortfall model implemented by the bank provides a measure of risk exposure that is enormous—even in excess of the bank’s capital position. What can be done? The first thing is not to panic. The second is to fire up the derivatives traders. The bank can manage its risk position by trading in derivatives markets. If the initial risk inventory is too high, the bank can undertake hedging transactions to reduce its risk exposure without turning away profitable and long-standing customers. On the other hand, if the initial risk inventory is too low, and therefore not profitable enough, the bank can undertake speculative transactions to increase its risk exposure. Derivatives markets are the thermostat used by the bank to control its risk temperature. Warren Buffett has termed derivatives “financial weapons of mass destruction.”11 He has decried the “daisy chain of risk” that is facilitated by derivatives that require little payment up front, but can represent large and uncertain obligations in the future. This point of view has led some to call for a ban on certain derivatives, although Warren Buffett admits that “the derivatives genie is out of the bottle, and these instruments will almost certainly multiply in variety and number until some event makes their toxicity clear.” However, the fundamental question is whether derivatives are the cause of this “toxic” behavior, or merely the vehicle for excessive risk-taking. If it is the latter, there will always be financial players who exploit the system for personal gain, whether or not they have derivatives to accomplish their nefarious goals. In either extreme, pure hedging or pure speculating, the derivatives transaction is tied to, indeed motivated by, another transaction, or series of transactions that constitute the underlying cash position. The Commodity Futures Trading Commission (CFTC) estimates that up to 85 percent of all futures trades are explicitly linked to other transactions. If the cash flows on the derivatives transaction are opposite to those of the underlying cash position, we consider the derivatives trade to be a hedge. If, on the other hand, the cash flows move in the same direction, we consider the derivatives trade to be speculative. The cash flows on derivatives are determined by fluctuations in interest rates, exchange rates, equity prices, default probabilities, etc. That is, derivatives can be used to manage all types of risk exposure.12 Suppose, for example, the bank has an underlying cash position that is exposed to interest rate increases. This is a very common position for a bank as a result of the ­process of “borrowing short to lend long.” Thus, the bank’s assets have a longer maturity (duration) than the bank’s liabilities, leading to a positive duration gap. Under these 11  Warren Buffett’s quotes have been taken from the 2002 Berkshire Hathaway annual report. 12  However, under Dodd–Frank Act regulations passed in 2010 in the US, banks cannot engage in speculative trades as specified by the Volcker Rule subsection of the Act.

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Private Information and Risk Management in Banking   163 circumstances, the underlying cash position (the bank’s portfolio) will decline in value and profitability will fall if interest rates go up. To hedge that risk, the bank can undertake a derivatives position that generates positive (offsetting) cash flows when interest rates go up—that is, a short position. Short positions can be implemented by selling interest rate futures or forwards, buying put options on interest rate sensitive instruments and/or buying fixed-for-floating swaps. We examine each of these markets briefly.

6.3.1  Financial Futures and Forwards The concept of a forward contract originated in sixteenth-century Japan when landowners raised money by selling rice in advance of delivery to rice merchants. A more formal, exchange-based contract, the precursor to the modern futures contract, originated in the US Midwest during the early nineteenth century. In 1848, some eighty-two merchants met above a flour store on Chicago’s South Water Street and formed the Chicago Board of Trade (CBOT). Today, merged with the Chicago Mercantile Exchange (CME), the CBOT trades millions of futures contracts, as well as options and swaps. Financial futures or forwards are obligations to make (sell) or take (buy) delivery of some underlying financial asset at a predetermined price (i.e., futures or forward price) on a specified delivery date. The counterparty that buys the contract agrees to buy the underlying financial asset and holds a long position. The counterparty that sells the contract is obligated to sell the underlying financial asset and holds a short position. The long position gains if the price upon delivery date is higher than the predetermined price, whereas the short position gains if the price declines below the predetermined price. Typically, there is no actual delivery of the underlying financial asset in financial futures/ forward contracts (in contrast to commodity futures/forwards). Instead of physical delivery, the contracts are usually cash settled, with the losing party paying the winning party for the difference between the spot price upon delivery minus the predetermined futures/forward price. For example, if the bank has a positive duration gap and wants to hedge its exposure to rising interest rates, it may take a short position in an interest rate futures contract, such as the US Treasury bills futures contract or the 3-month Eurodollar futures contract.13 If interest rates go up, the price of the contract falls and the short (selling) counterparty gains. For each basis point increase in interest rates, the Treasury bill and Eurodollar futures contracts gain $25 per $1 million face value. This cash inflow would offset some (or all) of the losses on the underlying cash position emanating from the bank’s positive duration gap.14 13  The Eurodollar CD is not related to the currency named the euro. Eurodollar CDs refer to US dollar-denominated deposits held by banks outside of the US or in international banking facilities within the US. LIBOR (the London Interbank Offered Rate) is the offer rate on interbank loans of Eurodollar deposits. See chapter 12, Allen (1997). 14  If all of the losses are hedged, we consider that a “perfect” or “naïve” hedge. In practice, we do not observe such hedges because (1) they are difficult to get exactly right and (2) they are undesirable since while a “perfect” futures/forward hedge eliminates all possibility of loss, it also eliminates all possibility of gain.

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164   The Theory of Banking Banks can hedge interest rate risk, currency risk, equity price risk, commodity risk, credit risk and operational risk using futures and forward contracts. The methodology is the same as illustrated above; that is, short futures/forwards positions hedge underlying cash exposures to price declines and long futures/forwards positions hedge underlying cash exposures to price increases. The only difference is the identity of the reference security. Thus, when hedging currency risk, the reference security’s value must fluctuate with shifts in foreign exchange rates. When hedging credit risk, the derivative’s underlying security fluctuates with shifts in default risk.

6.3.2  Financial Options Financial futures and forwards are useful tools to protect an underlying cash position from losses due to risk exposure. However, because of their symmetric cash flow payout, they also protect an underlying cash position from gains. That is, when the positive duration gap bank puts on a short futures position, and interest rates decline rather than increase, the bank’s portfolio will make money, but the hedge will lose money. Thus, there was a demand for a hedging instrument that would protect against losses, but not against gains—that is, an insurance policy against losses. This insurance policy is an options contract. An options contract is a derivative that gives the holder the right, not the obligation, to buy (call option) or sell (put option) an underlying reference financial asset at a predetermined price (the exercise or strike price) for a time period up until the specified expiration date.15 The buyer (holder) of the option retains the right to exercise the option if it is worthwhile. That is, if the holder has a call option, they will benefit when prices increase above the exercise price. If prices do not exceed the exercise price at expiration date, the option expires worthless. Thus, if the bank wants to use an option to hedge its exposure to rising interest rates, it would purchase a put option on an interest rate sensitive instrument (such as a Eurodollar futures contract),16 which would generate positive cash flows if interest rates increase (and prices fall), thereby offsetting the bank’s loss due to its underlying cash position with a positive duration gap. If, however, interest rates decline, the positive duration gap bank generates positive cash flows and the option hedge expires worthless, thereby allowing the bank to keep its gains.

15  An American option can be exercised at any time up until expiration date, whereas a European option cannot be exercised prior to expiration date. Unless there are interim cash flows (such as dividend payments), it would not be desirable to exercise an American option prior to expiration since the option is worth more alive than dead because of its time value. Therefore, in practical terms, there is no difference between American and European options on financial securities with no interim cash flows (e.g., zero coupon bonds). 16  In general, financial options on futures contracts tend to be more liquid than financial options on cash instruments. Thus, for example, we see more activity in the market for US Treasury bill futures options than in the market for US Treasury bill (cash) options.

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Private Information and Risk Management in Banking   165 The exception to this is that the options buyer must pay an upfront cost—the ­ remium—which is non-refundable to the buyer if the option expires worthless.17 Options p premiums are quite substantial. Therefore, we have seen the development of compound options positions, such as straddles, collars, butterflies, etc. that were originated in order to reduce the upfront premium cost of options trades. As market participants experimented with these “lower cost options hedges,” however, they found that they were viable products in their own right. Therefore, today, collars are sold as stand-alone risk management products to the customers of financial institutions. Alternatively, they can be packaged with other financial products, as in adjustable-rate mortgages that contain collars.

6.3.3 Swaps It did not take long for financial market professionals to see the extension to fixedfor-floating rate swaps (to hedge interest rate risk) and credit default swaps (to hedge credit risk exposure). A swap is essentially a portfolio of forward contracts with predetermined payment dates, called reset dates, and predetermined prices. In a fixed-for-floating rate swap, for example, the buyer of the swap exchanges floating rate payments (say, tied to LIBOR) for fixed rate payments. If interest rates increase, the swap buyer gains because, instead of paying the higher LIBOR payments, the swap buyer pays the lower, predetermined fixed rate. Thus, the positive duration gap bank can purchase fixed-for-floating rate swaps in order to hedge its exposure against increasing interest rates. Upon reset dates (which can occur monthly, quarterly, semi-annually, annually) for the life of the swap (which can last for up to five or ten years), the swap intermediary calculates the payments required, nets them out and supervises the transfer of the net cash flow (the difference between the fixed and floating rate as of the reset date) between the counterparties. Thus, if interest rates have increased, the swap seller pays the swap buyer an amount equal to the difference between the fixed rate minus the floating rate times the notional value of the swap, and vice versa if interest rates have declined. The swap intermediary also acts as the guarantor to insure that each swap counterparty meets its obligations. In exchange for setting up the transaction, monitoring its cash flows and guaranteeing the counterparty credit risk, the swap intermediary receives a fee that is paid on each reset date. The dominant credit derivative to date has been the credit default swap (CDS). Credit default swaps (CDS) are essentially insurance policies on the face value (notional value) of corporate debt (bonds or loans) such that the CDS buyer pays a premium in exchange for protection against loss from credit events (e.g., default) on the underlying (reference) 17  In contrast, futures contracts require an upfront margin (paid to the exchange’s clearing corporation, which acts as third party guarantor) which is a good faith deposit and is refunded to the contract holders (both buyer and seller) upon fulfillment of their obligations under the futures contract. Because forward markets are limited to financial intermediaries with reputations to uphold, there is no margin or third-party guarantor in the forward market.

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166   The Theory of Banking debt instrument.18 That is, in the event of default, the CDS seller must pay the CDS buyer either some cash amount or transfer physical securities, depending upon the method of settlement. CDS are customizable, over-the-counter (OTC) contracts, although standardization enhances the tradability (liquidity) of the contract.19 Thus, five-year CDS contracts are most prevalent, although 1-, 3-, 7- and 10-year contracts are also traded.20 In contrast to actual insurance policies, there is no requirement that the CDS buyer actually own the underlying reference securities, and therefore the notional value of CDS contracts has at times exceeded the total value of the outstanding debt instruments.21 For example, Helwege et al. (2009) report that the number of General Motors outstanding debt was $20 billion less than the $65 billion CDS notional value outstanding. As of the end of 2006, the Bank of England estimated total global corporate debt instruments (bonds plus loans) outstanding at $17.1 trillion. In contrast, the BIS reported that single name CDS outstanding during the first half of 2007 had a total notional value exceeding $20 trillion.22 This had implications both for settlement of the CDS contract and systemic risk exposure. The credit derivatives market has grown from its roots as an ad hoc attempt by banks to transfer their risk exposure.23 As of December 2016, OTC derivatives’ notional value 18  The credit event can be specified as default, failure to pay, restructuring, etc. However, the use of restructuring as a credit event is ambiguous when the reference security is a loan, since loan restructuring is a fairly common occurrence that may be triggered by something other than the borrower’s financial distress. Thus, restructuring is known as a “soft” credit event. Repudiation or moratorium is used as a credit event for credit derivatives based on government obligations. 19  There have been several proposals to move credit derivatives trading to organized exchanges. It is unclear whether the benefits of exchange trading (enhanced transparency and liquidity) will be offset by the costs of basis risk and lack of customization as the standardized contracts diverge from the underlying risks to be hedged. 20  The increased presence of hedge funds led to an agreement that enhanced the liquidity of the CDS market in 2006. Liquidating a CDS position typically required either offsetting transactions or an agreement by both counterparties to terminate (tear up) the transaction. However, hedge funds preferred to transfer their shares via assignment—a process known as novation. However, there were problems in coordinating novation agreements and getting confirmation. In September 2006, the ISDA Novation Protocol was announced to standardize novation procedures requiring parties to obtain prior consent, which could be communicated electronically. The results were to dramatically reduce confirmation backlogs. 21  In contrast to the notional value of OTC derivatives in mid-2008 of $680 trillion, as of December 2016, the total value was only $483 trillion. This may be related to Dodd–Frank Act regulations restricting bank proprietary trading activity. 22  Single name CDS specify a single reference security. In contrast, multi-name CDS reference more than one name, as in a portfolio or basket CDS or CDS index, such as the Dow Jones CDX. Baskets are credit derivatives based on a small portfolio of loans or bonds, such that all assets included in the underlying pool are individually listed. In contrast, the contents of larger portfolios are described by their characteristics. A basket credit default swap, also known as a first-to-default swap, is structured like a regular CDS, but the reference security consists of several securities. The first reference entity to default triggers a default payment of the par value minus the recovery value and then all payments end. As of the first half of 2007, there was an additional $20 trillion notional value in multi-name CDS. 23  See Smithson (2003) and Mengle (2007) for a discussion of the stages of development of the market for credit derivatives. The standardized contracts, terms and dispute resolution provided by the International Swap and Derivatives Association (ISDA) played a role in that evolution.

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Private Information and Risk Management in Banking   167 totaled $483 trillion, a decline from $553 trillion as of June 2016. Out of this, CDS represented a notional value of $9.9 trillion as of year-end 2016, substantially reduced from pre-crisis levels exceeding $40 trillion. The gross market replacement value amounted to $292 billion as of December 2016. Historically, the OTC derivatives markets have been dominated by dealers who limit the flow of information to buy-side investors by requiring trade-by-trade bilateral negotiation and preventing the release of real-time quote and trade information. Prompted by regulators and litigation, centralized trading via electronic exchanges has spread throughout financial markets, thereby slowly moving OTC derivatives have slowly moved toward a more transparent centralized system. Indeed, the use of a centralized clearing system for derivatives trading gets favorable treatment under Basel III capital requirements. Another critical component of this transition has been the development of a centralized clearing counterparty that acts as a clearinghouse on all trades. Thus, the decline in OTC derivatives activity was concentrated in the segment that is not centrally cleared as a result of high margin requirements. In contrast, the share of centrally cleared CDS increased to 44 percent as of December 2016. In OTC interest rate derivatives markets, 76 percent were booked against centralized counterparties, with 92 percent of forward rate agreements and 81 percent of interest rate swaps as of December 2016. Thus, the OTC derivatives markets are in transition as they move slowly toward a more transparent trading mechanism. Any perceived impediment to centralized clearing as a result of confidential information requirements is negated by the development of multi-name and index contracts. For example, in September 2003, the Dow Jones CDX (DJ CDX) North American Investment Grade Index was introduced. In November 2004, Markit initiated a credit index data service, which included the DJ CDX (which also includes indexes covering emerging market credit derivatives) and the International Index Company’s (IIC) iTraxx (which covers the EU, Japan, and non-Japan Asia). Both sets of indexes are made up of 125 of the most liquid, investment-grade credits in the form of CDS. For example, the DJ CDX consists of a basket of 125 CDS contracts on US firms with liquid, investment grade corporate debt. The identity of the components in the index changes every six months—every March and September for the DJ CDX. Companies may be dropped from the index if they are downgraded or become illiquid. For example, Ford and General Motors were dropped from the DJ CDX in September 2005 when their debt fell below investment grade. The index is equally weighted, and so each CDS component makes up 0.8 percent of the index value. Using indexed CDS to hedge credit risk may be less expensive because of the liquidity of these instruments, although it does expose the hedger to basis risk.24 Synthetic collateralized debt obligations (CDO) are comprised of

24  Basis risk results when the fluctuations in the value of the reference security underlying the derivative do not move in lock step with the hedge position. For example, there is basis risk if indexed CDS is used to hedge a portfolio of loans to firms that are not identical to the 125 firms in the index.

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168   The Theory of Banking tranches of indexed CDS. Thus, CDS are used as building blocks in financial securities design as well as risk management.25 Similar to options, but different from non-credit-related swaps, the risks on a credit swap are not symmetrical. That is, the protection buyer receives a payment upon the occurrence of a credit event trigger, but the swap “expires worthless” if no trigger occurs.26 In that event, the protection seller keeps the periodic premiums paid for the swap, similar to the convex cash flows that characterize options. Thus, the protection buyer transfers the credit risk to the protection seller in exchange for a premium. The size of the premium, known as the swap spread, is the internal rate of return that equates the periodic premium payments to the expected payments in the event of a credit event trigger. The spread is quoted per annum, but paid quarterly throughout the year.27 Although the credit protection buyer hedges exposure to default risk, there is still counterparty credit risk in the event that the seller fails to perform their obligations under the terms of the contract (as was the concern in September 2008 with regard to AIG, an active CDS seller).28 A pure credit default swap is similar to buying credit insurance and/or a multiperiod credit option. The growth in trading of these credit derivatives has facilitated a net overall transfer of credit risk from banks to non-banks, principally insurance companies. Banks, securities firms, and corporations are net buyers of credit protection, whereas insurance companies, hedge funds, mutual funds, and pension funds are net sellers. Insurance companies view credit derivatives as an insurance product, in which their relatively high credit ratings can be used to insure the buyers of credit protection (e.g., banks) against risk exposure to their loan customers. Credit derivatives such as CDS allow a bank to alter the risk-return tradeoff of a loan portfolio without having to sell or remove loans from the balance sheet. Apart from avoiding an adverse customer relationship effect, the use of credit derivatives (rather than loan sales or other portfolio methods for reducing the bank’s credit risk exposure) may allow a bank to avoid adverse timing of tax payments, as well as liquidity problems related to buying back a similar loan at a later date if risk-return considerations so dictate. Thus, for customer relationship, tax, transaction cost, and liquidity reasons, a bank may prefer the credit derivative

25  The most popular CDS indexes consist of 125 corporate entities. Multi-name, or basket CDS contain more than one reference security, most commonly between three and ten. The most common form of multi-name CDS is the first-to-default CDS, which compensates the protection buyer for losses on the first default among the basket of reference entities, after which the swap automatically terminates. Tranched synthetic CDOs comprised of indexed CDS also prioritize credit protection, but are more flexible than first-to-default swaps. 26  In contrast, an interest rate swap (fixed for floating rate swap) will entail symmetric payments such that the swap buyer (the fixed rate leg of the swap) earns positive cash flows when interest rates increase and the swap seller (the floating rate leg) earns positive cash flows when interest rates decrease. 27  OTC CDS have standardized spread payment dates on March 20, June 20, September 20 and December 20. The spread is constant for the life of the swap, with the exception of a constant maturity CDS in which the spread is reset periodically to the market rate for newly issued CDS. 28  Swap spreads incorporate counterparty credit risk. For example, Hull and White (2001) find a range of around 50 basis points when they simulate the impact of counterparty credit risk exposure.

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Private Information and Risk Management in Banking   169 solution to loan portfolio optimization rather than the more direct (loan trading) portfolio management solution.

6.4  Private Information Within Large Complex Banking Organizations Information is at the heart of finance and economics. This is particularly true for financial institutions that specialize in risk measurement and management. The business of financial intermediation involves the gathering of information that is aggregated and mobilized to allocate capital on behalf of customers who range from businesses to governments to households. Bank screening and monitoring activity in the course of a lending relationship involves the production of private information about the bank’s customers. Although the bank’s monopoly power over its own information set may lead to conflicts of interest and abuse (e.g., via front-running of customer orders, manipulative and deceptive structured financial transactions, and insider trading), one cannot abolish these information monopolies that are fundamental by-products of all intermediation activity. To do so would eliminate any value in the intermediation function as the information and skill set of each financial institution is its fundamental value-creating resource, thereby impairing the bank’s ability to measure and manage risk. Thus, each financial intermediary is endowed with a unique information set comprised of the sum of information obtained from each of the bank’s individual interactions with its customers. The value of this information hinges on two basic characteristics: the information’s exclusivity and reusability. That is, monopoly rents are higher, the more exclusive or the fewer the number of competing banks possessing the information set (see Petersen and Rajan, 1994; Bolton and Scharfstein, 1996; Hubbard, Kumar, and Palia, 2002). Alternatively, information is more valuable the more reusable and generally applicable the information for financial market transactions (e.g., Holmstrom and Tirole (1997) model synergies between monitored bank debt and arms-length debt issuance). Informationally intensive relationship banking benefits both borrower and lender. Repeated borrowing from the same relationship bank reduces borrowing costs, thereby benefiting borrowers (see Bharath et al., 2011). Further, utilizing a relationship bank as advisor increases the price paid to the target firm in an acquisition (see Allen et al., 2004). In addition, deposit-taking provides important information that can be used by the relationship bank to monitor and advise customers (see Mester, Nakamura, and Renault,  2007). Stockholders also benefit from the approval of bank loans as shown by positive stock price reactions (see Li and Ongena, 2014). Finally, and perhaps most importantly, relationship banks themselves also benefit from the ongoing, informationally intensive interaction with their customers. Banks are more likely to win additional business (lending or other services) from past borrowers (see Bharath et al., 2007) as a result of their information advantage.

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170   The Theory of Banking There is a natural tension between informational exclusivity and reusability since the reuse of private information undermines the information’s exclusivity. Reusing its private information in many different markets and activities would most intensively generate returns from the bank’s information set. However, the more actively the lender reuses its private information in trading the borrowing company’s securities, the greater the dissipation in the bank’s information monopoly. Trading may reveal the lender’s private information and impact securities prices, thereby signaling the information content to competing financial institutions and undermining its exclusivity (e.g., Leland and Pyle, 1977; James, 1987; Lummer and McConnell, 1989). Moreover, the borrower may develop less costly alternatives to bank debt as the firm’s equity and publicly traded debt markets (e.g., bonds) become more liquid. Thus, the bank faces a tradeoff between trading returns from the reuse of information against the economic rents from maintaining private control of the information (i.e., restricting activity via bank hoarding of information), thereby endogenizing the bank’s solution to the classic hold-up problem (Rajan, 1992). This may be manifest in a tradeoff between bank returns on lending and investment returns on publicly traded equity and debt securities. Indeed, informed equity market traders preserve their comparative advantage from private information by obscuring their information from non-informed traders via stealth and gradual trading strategies (e.g., see Kyle, 1989; Boulatov, Hendershott, and Livdan, 2013; Dong and Massa, 2013; Kyle, Obizhaeva, and Wang, 2014; Foucault, Hombert, and Rosu, 2016). Similarly, it is reasonable to expect that relationship banks would judiciously trade on their private information in ways similar to equity market traders so as to protect their informational advantage. The potential loss from the dissemination of private information is even more severe for bank lenders than for equity market traders since the dissipation of the relationship bank’s informational advantage may jeopardize the bank’s monopoly loan rents, as well as erode potential equity trading gains. However, there is an amount of academic literature that suggests that relationship banks aggressively utilize private information from new lending in order to manage equity portfolios in affiliated mutual funds (see Massa and Rehman, 2008; Dass and Massa,  2011). This literature is limited to the US case in which US banks utilize private information generated in the course of new lending to US borrowing firms in order to earn positive abnormal returns on their affiliated equity mutual funds by increasing their equity holdings. Allen et al. (2017) show that this result does not apply in the cross-border international context. In contrast to domestic US studies, they find that mutual funds affiliated with US lending banks have lower equity holdings in non-US borrowing firms during the quarter of new loan initiation, as compared to non-lending or non-affiliated mutual funds. Further, Allen et al. (2017) show that banks focus on lending to non-US repeat borrowers with lower levels of equity investment by affiliated mutual funds, consistent with Phelan (2017) who shows that correlated lending increases loan payoffs. Similarly, Dang et al. (2017) show that opaque banks limit their trading in financial markets in order to prevent the dissemination of secret information about bank borrowers, thereby maintaining the bank’s monopoly rents on lending. Indeed, Allen et al. (2017) find that loan rates increase as bank mutual fund equity holdings decrease, illustrating

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Private Information and Risk Management in Banking   171 the benefit to the lending bank from the strategic use of their private information. That is, as banks reduce their equity investment in borrowing firms, they reap the benefits of higher loan rates. This result is consistent with other studies that show how banks exploit creditconstrained borrowers. For example, Santos and Winton (2008) find that bank-dependent firms pay higher interest rates than firms with access to public debt and equity markets. Hale and Santos (2009) show that banks reduce loan rates after their relationship borrower issues publicly traded bonds, thereby breaking the relationship bank’s monopoly. They find that both the granting of a credit rating and a bond IPO undermines the bank’s lending monopoly by providing public information about a firm’s creditworthiness and providing access to debt markets other than bank loans. Thus, banks are forced to reduce interest rates as their informational rents are reduced. Schenone (2010) also finds that dissemination of private information in the course of an IPO reduces loan spreads. To prevent this, banks may voluntarily limit their trading on private information obtained from relationship borrowers. Thus, insider trading restrictions may actually exacerbate informational frictions and exploitation of credit-constrained borrowers in opaque markets. Failure to utilize private loan information in equity market trading activity is more pronounced for borrowing firms located in emerging nations. Since emerging equity markets tend to be less developed and thinly traded, any attempt to utilize the bank’s private information in equity investing would be quickly detected, thereby raising equity prices and eroding the potential returns to equity market trading as the informational advantage is dissipated. Indeed, Nguyen and Rugman (2015) show that over 90 percent of financing in British subsidiaries located in Southeast Asia come from internal sources in order to circumvent the thinly traded, inefficient local equity markets. Moreover, monopoly loan rents tend to be higher in emerging countries because of information asymmetries and institutional frictions. Thus, the lending bank has more to lose in the context of emerging markets as a result of the loss of its monopoly rents if private information seeps out via equity market trading. Therefore, during the quarter of new loan initiation by non-US firms, Allen et al. (2017) find that mutual funds affiliated with lending banks reduce equity market turnover in borrowing firms, particularly if they are located in emerging nations. Since lending bank trading in equity markets improves liquidity and reduces equity market spreads (see Allen et al., 2012), reductions in equity turnover by lending banks reduces equity market liquidity, thereby acting as the mechanism to raise the cost of equity to non-US borrowing firms. That is, the withdrawal of informed traders such as lending banks from equity markets impairs price discovery and raises the illiquidity premium embedded in borrowing firms’ equity prices. Thus, reductions in international equity turnover make non-US borrowing firms dependent on bank loans rather than equity as sources of financing. Phelan (2017) shows that bank investment in correlated loans acts as a monitoring commitment mechanism that enables banks to earn monopoly rents. By knowing each project’s returns, the bank obtains information about the state of all correlated project returns. Thus, correlations across loans provide the bank with additional private

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172   The Theory of Banking information about aggregate states of the world and their impact on the bank’s investment portfolio. In the presence of costly enforcement (as in Krasa and Villamil, 2000), this private information makes it more likely that the bank will diligently enforce ex post payment obligations via monitoring of borrowers. For example, information obtained from a diversified portfolio of correlated loans enables the bank to better distinguish between borrower distress and strategic default. The ability of the bank to keep this information secret is critical, as shown in Dang et al. (2017). Thus, although information obtained in the course of relationship lending may be valuable in directing equity market trading, opaque banks may prevent that information from reaching financial markets by restricting their trading activity. The optimal exploitation of information gathered over different subsidiaries of large, far-flung financial intermediaries operating across financial markets has been understudied in the academic literature. Kahn and Winton (2004) describe complex subsidiary structures as a centralized response to risk, shifting moral hazard concerns within financial intermediaries. That is, a decentralized subsidiary structure can be an optimal response to intra-firm managerial agency problems, thereby increasing the entire firm’s enterprise value. Brown and Wu (2016) find evidence of learning within fund families. Chuprinin, Massa, and Schumacher (2015) find that international mutual funds managed by in-house managers outperform funds that outsource the portfolio management function, thereby demonstrating within-firm benefits. Massa and Zhang (2015) find that banks use private information obtained from foreign lending to respond to global liquidity shocks, thereby reducing returns. Hao and Yan (2012) and Golez and Marin (2015) find that bank-affiliated mutual funds hold disproportionately large amounts of the parent bank’s IPO or SEO, thereby underwriting the parent bank’s equity. Ferreira, Matos, and Pires (2016) conjecture that the poor performance of bank-affiliated mutual funds emanates from the lending bank’s implicit support of the stock price of the bank’s borrowing firm (which restricts investing opportunities, thereby reducing equity returns), in order to increase the likelihood of repeat lending business. However, Allen et al. (2017) show that bank-affiliated mutual funds reduce their equity holdings at the time of syndicated bank loan initiations. There may be a spectrum of possible equilibrium outcomes ranging from full exploitation of lending information in all possible trading venues (thereby, stressing the reusability of lending information in equity investing) all the way to complete embargoing of all private lending information (to maximize monopoly rents). Further academic research into the role of private information in bank management is needed to formalize the nature of this continuum of equilibria. The optimal utilization of the relationship bank’s private information set is particularly relevant in the wake of the global financial crisis of 2007–8. The contagious spread of distress across large financial institutions has since generated calls to break up these behemoths into manageable pieces so as to limit systemic risk. However, this policy may generate other risks to the financial system as a result of the loss of private information produced by multifaceted banks. A careful analysis of this public policy issue brings us to the last source of risk in this chapter: systemic risk.

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Private Information and Risk Management in Banking   173

6.5  Why Do We Care About Risk In The Banking Sector? Until this point, we have focused on the risks inherent within individual financial firms that impact the bank’s shareholders and other stakeholders. However, we have not considered the risk that financial institutions impose on the economic system at large. That is, we have neglected systemic risk. Viewing the economic wreckage in the aftermath of the financial debacle that began in 2007, it is almost self-evident that systemic risk is important. For this reason, bank regulators have focused in recent years on ways to measure systemic risk. Focus has been on correlations among pairs of financial firms to determine the most interconnected banks, since these “systemically important” banks can set off a chain reaction of financial contagion when they become distressed. These “micro-level” systemic risk measurements measure the contribution of each bank to overall systemic risk. There have been many proposed micro-level estimates of systemic risk that can accomplish this.29 In this chapter, we briefly describe two measures: Adrian and Brunnermeier’s (2016) CoVaR, and the Systemic Expected Shortfall (SES) or SRISK of Acharya et al. (2017) and Brownlees and Engle (2017). Adrian and Brunnermeier’s (2016) delta CoVaR measures the marginal contribution of an individual bank i to overall systemic risk at time period t. Delta CoVaR is defined as the difference between the VaR of the financial system conditional on the distress of bank i minus the VaR of the banking system conditional on bank i’s median financial condition. That is, CoVaRit measures the impact on the VaR of the entire financial system of an event at bank i, whereas Delta CoVaRit measures the difference between CoVaR if bank i is in distress compared to non-distress (median) conditions at bank i. Thus, CoVaRit measures the expected impact of individual bank i on the system-wide value at risk, whereas Delta CoVaRit measures bank i’s marginal contribution to system-level risk in the event of distress. In contrast, Acharya et al. (2017) focus on the expected shortfall rather than value at risk in their derivation of a micro-level systemic risk measure. They develop a constrained optimization model to determine the impact of overall system-wide aggregate declines on each bank’s risk exposure. They advocate setting a tax that charges banks ex ante for both their institutional risk-taking and their contribution to potential systemic risk externalities. This specification must incorporate a measure of the probability of a systemic crisis so as to differentiate between macroeconomic downturns and individual 29 Micro-level systemic risk proposals include Marginal Expected Shortfall (MES) (see Acharya et al., 2017); CoVaR (Adrian and Brunnermeier, 2016); conditional tail risk (CTR) (Kelly, 2011); co-risk (Chan-Lau,  2009); a contingent claims approach (Gray and Jobst,  2009); Shapely values (Tarashev, Borio, and Tsatsaronis, 2009); and the IMF risk budgeting and standardized approaches (Espinosa-Vega, Kahn, and Sole, 2010). See Giglio, Kelly, and Pruitt (2016) for an excellent comparison of various systemic risk measures.

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174   The Theory of Banking bank distress. To do this, they specify that a crisis occurs when aggregate bank capital falls below a fixed percentage (z) of aggregate banking assets, where z is often set to equal the 8 percent capital requirement. To empirically define a systemic crisis, Brownlees and Engle (2017) specify a market decline of 10 percent or more within a month. This would cause aggregate capital levels to fall below the threshold z percent of aggregate banking assets. Both the SES and SRISK measures are computed as each bank’s expected undercapitalization in the event of a systemic crisis.30 Micro-level measures of systemic risk concentrate on the contribution of each bank to overall undercapitalization in the banking system. However, systemic risk is important because of the external effects on macroeconomic activity as the impact of each bank’s risk-taking spills over past the bank itself to the broader economy. Brownlees and Engle (2017) show that aggregate SRISK forecasts declines in unemployment and industrial production up to twelve months in advance of declines. Allen, Bali, and Tang (2012) develop a macro-level index of systemic risk that predicts future real economic downturns six to eight months in advance. The index (denoted CATFIN) measures the aggregate level of systemic risk in the entire financial sector (rather than an individual bank’s systemic risk exposure), and is calculated using a cross-sectional analysis of equity returns of financial firms in the US, Europe, and Asia. A macro-level measure of systemic risk complements micro-level systemic risk measures focusing on direct interbank connections, because systemic risk can emerge through general economic factors that cause financial markets to freeze up and/or banks to substantially reduce the supply of credit. Kashyap, Berner, and Goodhart (2011) and Korinek (2011) describe financial amplification effects resulting from fire sales of financial assets by individual banks, which trigger the catastrophic declines in asset prices and reduced liquidity that accompany a systemic crisis. These effects transcend pairwise interconnections between banks (particularly if many bank portfolios are overly invested in assets exposed to rollover risk; see Acharya, Gale, and Yorulmazer, 2011). Indeed, Bekaert et al. (2011) show that international contagion during the 2007–8 crisis did not spread through direct trade and financial linkages, but rather through a generalized “wake-up call” that “provides new information that may prompt investors to reassess the vulnerability of other market segments or countries, which spreads the crisis across markets and borders.” More generally, financial institutions are “special” since when they are in distress, banks tend to cut back on all of their activities, including lending to their customers (see Ivashina and Scharfstein, 2010 for evidence of this in 2008). Rejected business borrowers, in turn, reduce their investment activity and hiring, thereby negatively impacting employment and expenditure on a macroeconomic level. If there is only a limited number of troubled banks at any one point in time, competitor banks may overcome the 30  Although both measures estimate the conditional capital shortfall of financial firms, the computation of SES and SRISK differs. The computation of SES requires the realization of a systemic crisis, whereas SRISK is predictive in that it utilizes a GARCH-DCC model to forecast catastrophic events. See Brownlees and Engle (2017).

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Private Information and Risk Management in Banking   175 information destruction inherent in these disruptions in bank–customer relationships, and meet the demands of customers formerly served by a distressed bank. However, as more banks enter into crisis, these spillover effects become substantial and competitor banks are unable to prevent macroeconomic contagion (e.g., Jermann and Quadrini (2009) link reductions in credit availability to macroeconomic downturns). This chain reaction of systemic effects extends beyond the web of individual interbank relationships and impacts the entire macroeconomic system. Further, systemic risk could conceivably bubble up from widespread catastrophic risk among smaller, less directly interrelated banks with common risk factors. Indeed, Kashyap and Stein (2000) find that aggregate declines in loan supply are driven by smaller banks (in the bottom 95th percent of the size distribution) that are liquidity constrained. Thus, focus on the largest financial firms omits an important potential source of systemic risk.31 Banks, large and small, tend to take on excessive risk since they do not consider the external costs of their risk-taking on non-financial firms and on society at large. That is, financial contagion is spread through risk and illiquidity in the financial sector (Longstaff, 2010), as liquidity constrained banks transmit financial shocks to the real economy (Duchin, Ozbas, and Sensoy, 2010), thereby creating systemic risk (e.g., through bank transmission of fluctuations in investor sentiment as in Shleifer and Vishny, 2010). Indeed, it is because of the risk of macroeconomic contagion that regulators and governments are so concerned about systemic risk. Thus, regulators require a systemic risk measure that determines the macroeconomic implications of aggregate risk-taking in the financial system. Bank regulators around the world have responded to concerns about systemic risk by imposing higher capital requirements on systemically important banks (classified as G-SIBs). As a result of their impact on macroeconomic conditions and global financial markets, G-SIBs are subjected to more stringent requirements on higher capital buffers, total loss absorbing capacity (such as bail-in bonds and contingent capital instruments designed to automatically convert debt into equity),32 resolvability plans in the event of insolvency, and higher supervisory expectations. The Financial Stability Board and the Basel Committee on Banking Supervision publish a list of G-SIBs every November. Table 6.1 presents the list as of November 2016, comprised exclusively of large banks. However, Allen, Bali, and Tang (2012) demonstrate that systemic risk originates at small and medium-sized banks as well as the largest banks. Thus, regulations limited 31  In May 2018, Dodd–Frank regulations were amended to define systemically important financial institutions (SIFIs) as those with assets above $250 billion, up from the former threshold of $50 billion. Systemic capital add-ons and other regulatory interventions are imposed exclusively upon SIFIs. However, this regulatory approach has no preventative mechanisms against future systemic crises that may emanate from smaller institutions (as shown in Allen, Bali, and Tang, 2012). 32  Bail-in bonds such as CoCos (contingent convertible bonds) are designed to convert debt into equity when a trigger of bank insolvency or systemic risk is breached. However, current CoCos specify a trigger that would not have been breached by any of the banks during the 2007–8 crisis. Allen and Tang (2016) propose a CoCo trigger that would have automatically recapitalized both Bear Stearns and Lehman during November 2007.

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176   The Theory of Banking

Table 6.1  List of G-SIBs, November 2017 Bucket*

G-SIBs in alphabetical order within each bucket

5 (3.5%)

(Empty)

4 (2.5%)

JP Morgan Chase

3 (2.0%)

Bank of America Citigroup Deutsche Bank HSBC

2 (1.5%)

Bank of China Barclays BNP Paribas China Construction Bank Goldman Sachs Industrial and Commercial Bank of China Limited Mitsubishi UFJ FG Wells Fargo

1 (1.0%)

Agricultural Bank of China Bank of New York Mellon Credit Suisse Groupe Crédit Agricole ING Bank Mizuho FG Morgan Stanley Nordea Royal Bank of Canada Royal Bank of Scotland Santander Société Générale Standard Chartered State Street Sumitomo Mitsui FG UBS Unicredit Group

Note: The bucket* approach is defined in Table 2 of the Basel Committee document Global systemically important banks: updated assessment methodology and the higher loss absorbency requirement, July 2013. The numbers in parentheses are the required level of additional common equity loss absorbency as a percentage of risk-weighted assets that each G-SIB will be required to hold in 2019. Source: Financial Stability Board, press release, November 21, 2017.

to the largest thirty banks in the world will not mitigate the systemic risk inherent in other institutions. The crisis of 2007–8 demonstrates that we still have a lot to learn about risk measurement and risk management. However, no system will be effective if financial institutions ignore the warning signals flashed by their risk measurement models in their rush to join in the latest market frenzy—whether it is subprime mortgage-backed securities,

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Private Information and Risk Management in Banking   177 high tech, international government securities, or whatever will be the next mania. Risk measurement and management requires a steady eye and a firm hand as well as effective quantitative and analytical tools. Indeed, macroeconomic conditions around the world will be improved if the banking sector controls its systemic risk.

References Acharya, V., Gale, D., and Yorulmazer, T. (2011). “Rollover Risk and Market Freezes,” Journal of Finance, 66, 1177–209. Acharya, V., Pedersen, L., Philippon, T., and Richardson, M. (2017). “Measuring Systemic Risk,” The Review of Financial Studies, 30(1), 2–47. Acharya, V., Qian, J., and Yang, Z. (2016). “In the Shadow of Banks: Wealth Management Products and Issuing Banks’ Risk in China,” Working Paper, November 5. Adrian, T. and Brunnermeier, M. K. (2016). “CoVaR,” American Economic Review, 106(7), 1705–41. Allen, L. (1997). Capital Markets and Institutions: A Global View (New York: John Wiley and Sons). Allen, L. and Bali, T. (2007). “Cyclicality in Catastrophic and Operational Risk Measures,” Journal of Banking and Finance, 31(4), 1191–235. Allen, L. and Tang, Y. (2016). “What’s the Contingency? A Proposal for Bank Contingent Capital Triggered by Systemic Risk,” Journal of Financial Stability, 26, 1–14. Allen, L., Bali, T., and Tang, Y. (2012). “Does Systemic Risk in the Financial Sector Predict Future Economic Downturns?” Review of Financial Studies, 25(10), 3000–36. Allen, L., Boudoukh, J., and Saunders, A. (2004). Understanding Market, Credit and Operational Risk: The Value at Risk Approach (Oxford: Blackwell Publishing). Allen, L., Chakraborty, S., Hazarika, S., and Su, D. (2017). “The Role of Information from International Bank Lending in Mutual Fund Equity Investing,” Working Paper. Allen, L., Jagtiani, J., Peristiani, S., and Saunders, A. (2004). “The Role of Bank Advisors in Mergers and Acquisitions,” Journal of Money, Credit and Banking, 36(2), 197–224. Bekaert, G., Ehrmann, M., Fratzscher, M., and Mehl, A. (2011). “Global Crises and Equity Market Contagion,” Columbia University, Working Paper. Berkshire Hathaway Annual Report (2002). SEC Edgar online database. Bharath, S., Dahiya, S., Saunders, A., and Srinivasan, A. (2007). “So What Do I Get? The Bank’s View of Lending Relationships,” Journal of Financial Economics, 85, 368–419. Bharath, S., Dahiya, S., Saunders, A., and Srinivasan, A. (2011). “Lending Relationships and Loan Contract Terms,” Review of Financial Studies, 24(4, April), 1141–203. Bolton, P. and Scharfstein, D. (1996). “Optimal Debt Structure and the Number of Creditors,” Journal of Political Economy, 104(1), 1–25. Boulatov, A., Hendershott, T., and Livdan, D. (2013). “Informed Trading and Portfolio Returns,” Review of Economic Studies, 80(1), 35–72. Brown, D. and Wu, Y. (2016). “Mutual Fund Flows and Cross-Fund Learning Within Families,” Journal of Finance, LXXI(1, February), 383–424. Brownlees, C. and Engle, R. (2017). “SRISK: A Conditional Capital Shortfall Measure of Systemic Risk,” The Review of Financial Studies, 30(1), 48–79. Chan-Lau, J. (2009). “Regulatory Capital Charges for Too-Connected-To-Fail Institutions: A Practical Proposal,” IMF Working Paper, November.

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178   The Theory of Banking Chuprinin, O., Massa, M., and Schumacher, D. (2015). “Outsourcing in the International Mutual Fund Industry: An Equilibrium View,” Journal of Finance, October, LXX(5), 2275–308. Dang, T. V., Gorton, G., Holmstrom, B., and Ordonez, G. (2017). “Banks as Secret Keepers,” American Economic Review, 107(4), 1005–29. Dass, N. and Massa, M. (2011). “The Impact of a Strong Bank–Firm Relationship on the Borrowing Firm,” Review of Financial Studies, 24(4), 1204–60. Dong, X. and Massa, M. (2013). “Excess Autocorrelation and Mutual Fund Performance,” January. Douglas, G. W. (1969). “Risk in Equity Markets: An Empirical Appraisal of Market Efficiency,” Yale Economic Essays, IX, Spring. Duchin, R., Ozbas, O., and Sensoy, B. A. (2010). “Costly External Finance, Corporate Investment and the Subprime Mortgage Credit Crisis,” Journal of Financial Economics, 97, 418–35. Elliott, D. and Yan, K. (2013). “The Chinese Financial System: An Introduction and Overview,” Brookings Institute Monograph Series No. 6, July. Espinosa-Vega, M. A., Kahn, C. M., and Sole, J. (2010). “Systemic Risk and the Redesign of Financial Regulation,” IMF Global Financial Stability Report, Chapter 2, April. Fama, E. F. and French, K. R. (1992). “The Cross-Section of Expected Stock Returns,” Journal of Finance, 47(June), 427–65. Ferreira, M., Matos, P., and Pires, P. (2016). “Asset Management Within Commercial Banking Groups: International Evidence,” Working Paper, February. Foucault, T., Hombert, J., and Rosu, I. (2016). “News Trading and Speed,” Journal of Finance, LXXI(1, February), 335–81. Giglio, S., Kelly, B., and Pruitt, S. (2016). “Systemic Risk and the Macroeconomy: An Empirical Evaluation,” Journal of Financial Economics, 119(3), 457–71. Golez, B. and Marin, J. (2015). “Price Support by Bank-Affiliated Mutual Funds,” Journal of Financial Economics, 115, 614–38. Gray, D. and Jobst, A.  A. (2009). “New Directions in Financial Sector and Sovereign Risk Management,” Journal of Investment Management, 8, 22–38. Hale, G. and Santos, J. (2009). “Do Banks Price Their Information Monopoly?” Journal of Financial Economics, 93, 185–206. Hao, Q. and Yan, X. (2012). “The Performance of Investment Bank-Affiliated Mutual Funds: Conflicts of Interest or Informational Advantage?” Journal of Financial and Quantitative Analysis, 47(June), 537–65. Helwege, J., Maurer, S., Sarkar, A., and Wang, Y. (2009). “Credit Default Swap Auctions,” Federal Reserve Bank of New York Staff Report No. 372, May. Holmstrom, B. and Tirole, J. (1997). “Financial Intermediation, Loanable Funds, and the Real Sector,” Quarterly Journal of Economics, 112(3), 663–91. Hubbard, R. G., Kumar, K., and Palia, D. (2002). “Are There Bank Effects in the Borrowers’ Cost of Funds? Evidence from a Matched Sample of Banks and Borrowers,” Journal of Business, 75(4, October), 559–81. Hull, J. and White, A. (2001). “Valuing Credit Default Swaps II: Modeling Default Correlations,” Journal of Derivatives, 8(3, Spring), 12–21. Ivashina, V. and Scharfstein, D. (2010). “Bank Lending During the Financial Crisis of 2008,” Journal of Financial Economics, 97, 319–38. James, C. (1987). “Some Evidence on the Uniqueness of Bank Loans,” Journal of Financial Economics, 19, 217–35.

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Private Information and Risk Management in Banking   179 Jermann, U. and Quadrini, V. (2009). “Macroeconomic Effects of Financial Shocks,” NBER Working Paper Series No. 15338. Kahn, C. and Winton, A. (2004). “Moral Hazard and Optimal Subsidiary Structure for Financial Institutions,” Journal of Finance, 59, 2531–75. Kashyap, A. K. and Stein, J. C. (2000). “What a Million Observations on Banks Say About the Transmission of Monetary Policy?” American Economic Review, 90, 407–28. Kashyap, A. K., Berner, R. B., and Goodhart, C. A. (2011). “The Macroprudential Toolkit,” IMF Economic Review, 59. Kelly, B. (2011). “Tail Risk and Asset Prices,” Working Paper, University of Chicago. Korinek, A. (2011). “Systemic Risk-taking: Amplification Effects, Externalities, and Regulatory Responses,” European Central Bank Working Paper Series, No. 1345. Krasa, S. and Villamil, A. (2000). “Optimal Contracts when Enforcement is a Decision Variable,” Econometrica, 57, 197–221. Kyle, S. A. (1989). “Informed Speculation with Imperfect Competition,” Review of Economic Studies, 56, 317–56. Kyle, S. A., Obizhaeva, A., and Wang, Y. (2014). “Smooth Trading with Overconfidence and Market Power,” October 30. Leland, H. and Pyle, D. (1977). “Informational Asymmetries, Financial Structure, and Financial Intermediation,” Journal of Finance, 32, 371–87. Li, C. and Ongena, S. (2015). “Bank Loan Announcements and Borrower Stock Returns Before and During the Financial Crisis,” Journal of Financial Stability, 21(December), 1–12. Longstaff, F.  A. (2010). “The Subprime Credit Crisis and Contagion in Financial Markets,” Journal of Financial Economics, 97, 436–50. Lummer, S. L. and McConnell, J. J. (1989). “Further Evidence on the Bank Lending Process and the Capital-Market Response to Bank Loan Agreements,” Journal of Financial Economics, 15, 31–60. Markowitz, H. (1952). “Portfolio Selection,” Journal of Finance, 7, 77–91. Massa, M. and Rehman, Z. (2008). “Information Flows Within Financial Conglomerates: Evidence from the Bank–Mutual Fund Relation,” Journal of Financial Economics, 89, 288–306. Massa, M. and Zhang, L. (2015). “Fire Sales and Information Advantage: When Informed Investor Help,” Working Paper, March. Mengle, D. (2007). “Credit Derivatives: An Overview,” Federal Reserve Bank of Atlanta Economic Review, Fourth Quarter, 92(4), 1–24. Mester, L., Nakamura, L., and Renault, M. (2007). “Transaction Accounts and Loan Monitoring,” Review of Financial Studies, 20(3), 529–56. Mina, J. and Xiao, J. Y. (2001). Return to RiskMetrics: The Evolution of a Standard (New York: RiskMetrics). Mossin, J. (1968). “Optimal Multiperiod Portfolio Policies,” Journal of Business, 41, 215–29. Nguyen, Q. and Rugman, A. (2015). “Internal Equity Financing and the Performance of Multinational Subsidiaries in Emerging Economies,” Journal of International Business Studies, 46, 468–90. Petersen, M. and Rajan, R. (1994). “The Benefits of Lending Relationships: Evidence from Small Business Data,” Journal of Finance, 49, 3–37. Phelan, G. (2017). “Correlated Default and Financial Intermediation,” Journal of Finance, LXXII(3, June), 1253–84.

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180   The Theory of Banking Rajan, R. (1992). “Insiders and Outsiders: The Choice Between Informed and Arm’s-Length Debt,” Journal of Finance, 47(September), 1367–400. Roll, R. (1977). “A Critique of the Capital Asset Theory Tests: Part I: On Past and Potential Testability of the Theory,” Journal of Financial Economics, 4. Rubinstein, M. (2002). “Markowitz’s ‘Portfolio Selection’: A Fifty-Year Retrospective,” Journal of Finance, LVII(3, June), 1041–5. Santos, J. and Winton, A. (2008). “Bank Loans, Bonds and Information Monopolies Across the Business Cycle,” Journal of Finance, 63(June), 1315–59. Saunders, A. and Allen, L. (2010). Credit Risk Measurement: New Approaches to Value at Risk and Other Paradigms, 3rd edn (New York: John Wiley and Sons). Schenone, C. (2010). “Lending Relationships and Information Rents: Do Banks Exploit Their Information Advantages?” Review of Financial Studies, 23(3), 1149–99. Sharpe, W. F. (1963). “A Simplified Model for Portfolio Analysis,” Management Science, 9, 277–93. Shleifer, A. and Vishny, R. W. (2010). “Unstable Banking,” Journal of Financial Economics, 97, 306–18. Smithson, C. (2003). Credit Portfolio Management (Hoboken, NJ: John Wiley & Sons). Tarashev, N., Borio, C., and Tsatsaronis, K. (2009). “The Systemic Importance of Financial Institutions,” BIS Quarterly Review, September, 75–87. Wallace, A. (1980). “Is Beta Dead?” Institutional Investor, 14(July), 22–30. Xia, L., Schwarz, S., and Herrero, A. (2013). “Banking Watch: An Update on China’s Shadow Banking Activity,” BBVA, March 8.

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chapter 7

Cr eation a n d R egu l ation of Ba n k Liqu idit y Christa H. S. Bouwman

7.1 Introduction This chapter examines key issues related to “liquidity creation” by banks, including prudential regulation. The questions addressed are: How do banks create liquidity and how does this improve welfare? What risks does liquidity creation generate for banks? How do banks cope with these risks in the traditional originate-to-hold (OTH) model and in the originate-to-distribute (OTD) model that is closely linked to the shadowbanking system? Does managing these risks call for regulation in the form of capital requirements and regulatory reserve/liquidity requirements? “Liquidity creation” is a commonly used term but it has come to have at least two distinct connotations in the theoretical literature. One refers to the different liquidities on the asset and liability sides of the bank’s balance sheet. Banks typically make illiquid loans financed largely with liquid deposits that give depositors the ability to withdraw funds at par value at a moment’s notice. In this view, exemplified in the papers of Bryant (1980) and Diamond and Dybvig (1983), liquidity creation is synonymous with banks providing depositors with improved risk sharing when they are subject to shocks.1 1  Some view the fact that the bank gives depositors access to instant interim liquidity through a demand deposit contract in these models as an aspect of liquidity creation. However, depositors in these models have liquidity anyway, even without a bank—this is the money they have in their pockets that they could keep to meet a future liquidity need even without depositing it in a bank. This liquidity is invested in a bank deposit account because it provides better consumption smoothing than without a bank. So it is not merely giving the depositor access to instant liquidity through the deposit account that creates liquidity per se. Rather, it is that the deposit contract provides better risk sharing while giving the depositor access to a liquid claim that is viewed as liquidity creation in these models.

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182   The Theory of Banking Another view of liquidity creation is that it is funding liquidity creation. That is, banks are able to expand investments in real projects in the economy that, in the aggregate, exceed the entire initial endowment of the economy. This view, in which bank liquidity creation is linked to banks creating private money, is presented in the theory of “warehouse banking” developed by Donaldson, Piacentino, and Thakor (2018). These theories of liquidity creation deal with what banks do on the balance sheet. Of course, banks also create liquidity through their off-balance-sheet activities, like loan commitments and similar claims to liquid funds (e.g., Boot, Greenbaum, and Thakor, 1993; Holmstrom and Tirole, 1998; Kashyap, Rajan, and Stein, 2002; Thakor, 2005). Apart from extensive theoretical literature on bank liquidity creation, there is now emerging literature on its empirical measurement (e.g., Berger and Bouwman, 2009, 2016). Bank liquidity creation is important for the macroeconomy (e.g., Bernanke,  1983; Dell’Ariccia, Detragiache, and Rajan,  2008; Berger and Bouwman,  2016; Berger and Sedunov, 2017). However, the creation of liquidity exposes the bank to a variety of risks, including liquidity risk. This risk can be mitigated to some extent by holding liquid assets like cash.2 This is the most basic rationale for liquidity requirements that mandate that banks hold a minimum level of liquid assets. But cash-asset reserves are not sufficient if depositors withdraw simply because they are afraid that the bank will shut down due to a deposit run by others. They will also be useless if the withdrawal decisions of depositors are not due to coordination failures but due to depositors’ concerns about the solvency of the bank, as the empirical evidence suggests is typically the case (see Gorton, 1988; Boyson, Helwege, and Jindra, 2014; Perignon, Thesmar, and Vuillemey, 2018). A regulatory safety net (including deposit insurance and the discount window) can deal with such fears, but its existence gives rise to moral hazard: it gives the bank incentives to be overleveraged and increase asset risk at the expense of the deposit insurer (Merton, 1977). This can increase the risk of future asset-value impairment, and if the safety nets are less than complete, the risk of bank failures can perversely increase due to these safety nets (e.g., Thakor, 2014, 2015). To improve the bank’s asset portfolio choices and risk management, regulatory monitoring and capital requirements can be used. This suggests that both liquidity requirements and capital requirements can potentially be useful as part of the regulation of banks’ liquidity creation. Before the subprime lending crisis, regulation was largely microprudential (ensuring the safety and soundness of individual banks) and focused on capital requirements. The same holds for the theories and empirical work. After the subprime lending crisis, macroprudential regulation (ensuring the safety and soundness of the financial system) became important and introduced liquidity requirements as one of its tools. Theoretical and empirical work on liquidity requirements is nascent, as is work that tries to combine capital and liquidity 2  Requiring banks to hold more liquid assets, however, reduces the amount of liquidity banks create (e.g., Berger and Bouwman, 2009) and may be wasteful. Thakor (2018) points out that JPMorgan Chase invested 38 percent of its deposits ($524 billion/$1.38 trillion) in liquid securities, and this liquidity hoarding was in part due to Basel III liquidity requirements and stress test results. If it had held only 10 percent in liquid securities and had lent the remainder to corporations, it would have created $772 billion more in liquidity.

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Creation and Regulation of Bank Liquidity   183 requirements. This chapter discusses the past, present, and future of both capital and liquidity regulation, implementation issues, and how they should be regulated. To properly understand the roles of capital and liquidity requirements in influencing bank liquidity creation, we also take a closer look at the economics of traditional banking (which focuses on relationship lending and the originate-to-hold model) and its evolution to modern-day banking, characterized by a mix of the originate-to-hold and the originate-to-distribute models, and a rapid growth of the shadow-banking system. We describe this system and how it interacts with traditional banking in its liquidity creation role. One could argue that the absence of bank runs in US commercial banking indicates the effectiveness of the regulatory safety net and the possible redundancy of liquidity requirements. But the rapid drying up of liquidity in the shadow-banking system during the recent subprime lending crisis suggests that regulators need to look beyond the traditional boundaries of deposit-based banking when thinking about capital and liquidity requirements. Basel III requires banks to operate with more and higher-quality capital, and introduces liquidity ratios. We discuss these new standards, how they are adopted in the US and Europe, and how they may affect liquidity creation. We also turn to the possible theoretical linkages between liquidity requirements and capital requirements, how one should think about these requirements for both traditional deposit-funded banks and for shadow banks, and identify open research questions.

7.2  Banks as Liquidity Creators 7.2.1 Theories Standard textbooks on financial intermediation (e.g., Freixas and Rochet,  2008; Greenbaum, Thakor, and Boot, 2015) explain that banks are institutions that make loans funded by a combination of deposits from the public and equity supplied by the banks’ shareholders. More formally, banks engage in “liquidity creation,” which is a form of “qualitative asset transformation.” To understand liquidity creation, picture a firm in need of long-term financing in a world without banks. In such a world, savers would directly finance the funding needs of the firm, and would have an illiquid claim against the firm. In contrast, in a world with banks, it is the bank that provides the long-term loan to the firm, and the bank is able to offer savers demand deposits.3 So it is the bank that holds the illiquid claim against the 3  There are alternative theories as to why banks fund with so much short-term debt. Some argue that short-term debt has a disciplining role in that the threat of non-renewal of funding makes bank managers behave (Calomiris and Kahn, 1991; Dewatripont and Tirole, 1994; Diamond and Rajan, 2001). Others argue it may be the outcome of a maturity rat race (Brunnermeier and Oehmke, 2013) or debt overhang problem (Admati et al., 2018).

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184   The Theory of Banking firm and savers end up with a liquid claim against the bank. Because of this difference in liquidity between what banks do with their money (their assets) and the way they finance their activities (their liabilities), banks are said to create liquidity. Inherent in the liquidity creation in these models is maturity transformation (see Bhattacharya and Thakor, 1993; Hellwig, 1994). Formal models of banks as liquidity creators in this sense were developed by Bryant (1980) and Diamond and Dybvig (1983). In those models, depositors can suffer interim liquidity shocks, so being able to hold liquid (demand) deposit claims improves welfare. In Diamond and Dybvig (1983), this liquidity creation exposes banks to withdrawal risk.4 Fear that other depositors may rush in to withdraw their deposits prematurely, even though they may not have liquidity needs, can cause all depositors to withdraw, precipitating a bank run as one of two possible equilibria.5,6 It is impossible for the bank to “provision” for such an event, short of practicing 100 percent reserve banking, that is, keeping all deposits as cash in vault. But such an institution would be merely a safe-deposit box, rather than a bank that creates liquidity. Diamond and Dybvig (1983) argue that federal deposit insurance can eliminate bank runs, thereby ridding banks of the prospect of the large-scale deposit withdrawals that characterize such runs.7 But of course, the intent of deposit insurance is to help banks deal with panic runs, not substitute for the liquidity banks need to keep on hand to meet day-to-day routine deposit withdrawals. Thus, even with deposit insurance, banks need to worry about having enough liquidity on hand to meet the normal liquidity needs of depositors.

4  In practice, it also exposes banks to credit risk and interest rate risk (both are absent in Diamond and Dybvig, 1983) related to maturity transformation. Hellwig (1994) discusses the relation between both in a model of maturity transformation. 5  In Diamond and Dybvig (1983), a bank run is a “sunspot” phenomenon caused by a coordination failure among depositors, not attributable to any specific economic trigger in the real economy. Chari and Jagannathan (1988) show that a bank run can arise as a unique equilibrium that is triggered by adverse fundamental information. Gorton’s (1988) evidence indicates that bank runs are preceded by declining fundamentals and stresses in the real sector, and thus do not appear to be caused by sunspots. It is thus more consistent with Chari and Jagannathan (1988). The recent evidence of Perignon, Thesmar, and Vuillemey (2018) suggests that the subprime lending crisis was one in which European banks did not suffer a liquidity shortage due to coordination failures. Rather, it was linked to bank solvency—banks with better assets and higher capital were able to obtain more liquidity at the expense of banks with worse assets and lower capital. 6  Diamond and Dybvig (1983) take the sequential servicing constraint (SSC: first-come, first-served rule) as a given. Calomiris and Kahn (1991) provide an endogenous rationale. They show that demandable debt disciplines the manager because depositors can vote with their feet, and that the SSC gives depositors an incentive to monitor (avoids free-riding). Jacklin (1987, 1993) shows that the allocation achieved by the deposit contract in Diamond and Dybvig (1983) can be replicated by traded dividendpaying equity, so bank runs can be avoided this way, without relying on deposit insurance. 7  Kane, Laeven, and Demirgüç-Kunt (2008) examine deposit insurance in 170 countries from 1960–2003. They document that explicit deposit insurance schemes were not available in most countries before 1960. The number of countries with such schemes had grown to forty-five by the beginning of 1995 and to eighty-seven by year-end 2003. They argue that countries that do not have explicit schemes typically have some form of implicit deposit insurance.

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Creation and Regulation of Bank Liquidity   185 Because the level of even routine withdrawals on any given day is stochastic, the liquidity reserves a bank keeps may either be too high or too low in light of the realized level of withdrawals. Moreover, absent panic runs and financial crises, the daily withdrawal levels across banks will not be perfectly correlated, suggesting gains from diversification. To take advantage of these diversification gains, an interbank market in trading cash reserves emerged, called the federal funds market. The federal funds rate is the rate at which banks borrow and lend on an overnight basis in this market in the US.8 Banks with excess reserves are lenders and those with reserve deficiencies are borrowers.9 In addition to the fed funds market, banks can also avail of short-term borrowing at the discount window to meet their short-term liquidity needs. The Federal Reserve’s willingness, in its role as Lender of Last Resort (LOLR), to provide banks with discount window access is an important potential source of liquidity for banks. Banks face costs in accessing the federal funds market and in borrowing at the discount window. Eligible collateral must be posted and accessing the discount window may be associated with a stigma: such borrowing may be perceived as a sign of weakness and may make banks reluctant to obtain funds.10,11 Banks thus have an incentive to keep cash on hand to deal with the liquidity risk that is an unavoidable companion to the bank’s basic economic function of being a liquidity creator. In the funding liquidity creation theory of Donaldson, Piacentino, and Thakor (2018), banks have a technological advantage in storage or safekeeping (for example, due to economies of scale in safeguarding), so they receive deposits from individuals who wish to take advantage of the more efficient safekeeping provided by the bank. These banks also make loans, but do not limit themselves to only lending out their deposits, as in the usual banking models. Rather, they write “fake warehouse receipts”—which are indistinguishable from authentic warehouse receipts given to depositors as proof of their deposits—and also lend these out. This means that if all of the economy’s endowment is 8  In the UK, the analogous rate is LIBOR, the London InterBank Offered Rate. 9  Allen, Peristiani, and Saunders (1989) show that small banks tend to act as lenders while large banks tend to act as borrowers in this market. They argue this may be because small banks: prefer to use deposits to fund their activities; can attract deposits more cheaply due to local monopoly power; and face greater information asymmetries which makes fed funds more expensive for them than for large banks. 10  In the words of the Chairman of the Federal Reserve, Bernanke (2008): “ . . . the efficacy of the discount window has been limited by the reluctance of depository institutions to use the window as a source of funding. The “stigma” associated with the discount window, which if anything intensifies during periods of crisis, arises primarily from banks’ concerns that market participants will draw adverse inferences about their financial condition if their borrowing from the Federal Reserve were to become known.” Ennis and Weinberg (forthcoming) provide a theoretical model on the origin and implications of stigma. Furfine (2001) provides some empirical evidence on stigma by examining data on a special Y2K Federal Reserve liquidity facility. In an attempt to quantify the costs associated with stigma using data from the recent subprime lending crisis, Armantier et al. (2015) show that banks were on average willing to pay a 37-basispoint premium over a similar funding source (term auction facility) during the height of the crisis. 11  Information on who obtains funds from the central bank is generally not available. However, data on access during the recent subprime lending crisis were recently made available. Berger et al. (2017) examine which kinds of banks obtained such funds from the Federal Reserve. Drechsler et al. (2016) instead focus on banks that used funds from the European Central Bank.

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186   The Theory of Banking deposited in banks, the total lending by banks exceeds this total initial endowment of the economy. Every fake warehouse receipt represents a depository obligation of the bank (on the liability side of its balance sheet), and when it is loaned out it is also a corresponding asset entry. Thus, loans create deposits in their model. But, unlike authentic deposits, the fake receipts are not backed by tangible collateral (e.g., gold or fiat money). The amount of funding liquidity created equals the total lending by the bank (both fake and authentic receipts) minus the total initial deposits, that is, liquidity creation equals the volume of fake receipts issued. These fake receipts essentially function as private money. In their model, there is no uncertainty and the number of fake receipts is constrained by an incentive compatibility constraint that ensures that the bank does not create excess liquidity. However, it is easy to imagine that if there is an uncertain interim withdrawal need for depositors, then the bank in this model would face withdrawal risk because of deposits that are withdrawable on demand. While Donaldson, Piacentino, and Thakor (2018) cast their model in the context of ancient commodity warehouses that evolved into modern-day banks, their notion of fake receipts and private money creation as being central to bank liquidity creation are even more relevant today than historically. Most of the money in a modern economy is actually not fiat money, but rather what Donaldson, Piacentino, and Thakor call “fake receipts.” For example, in Switzerland, the total amount of money in circulation is 645 billion Swiss francs, of which only 85 billion Swiss francs is fiat money (notes and coins), with the rest being fake receipts. That is, over 90 percent of the money in Switzerland is fake receipts issued by banks (Wall Street Journal, 2018). We can compare these two views of liquidity creation. In Diamond and Dybvig (1983), the aggregate amount of investment in real projects in the economy is exactly the same with banks as it is without. This is because all of the initial endowment of the economy (and no more) is invested in real projects, whether there are banks or not. If there are interim withdrawals, projects can be liquidated to recover the initial investment and pay off depositors.12 Hence, there is no funding liquidity creation in the model. The welfare contribution of banks comes from improved consumption insurance for risk-averse depositors. In contrast, in the Donaldson, Piacentino, and Thakor (2018) model, there is no risk aversion, so consumption insurance plays no role, and the welfare contribution of banks comes from funding liquidity creation and the expansion of aggregate investment in real projects. Another important difference is that there is no bank capital in Diamond and Dybvig (1983), so one cannot examine how bank capital affects bank liquidity creation. By contrast, in Donaldson, Piacentino, and Thakor (2018), bank liquidity creation increases with bank capital up to a point, and then the relationship flattens out. One takeaway from these papers is that loans and deposits are intertwined when it comes to liquidity creation. In both, the bank cannot create liquidity without both loans 12  Sometimes the Diamond and Dybvig (1983) model is characterized as a model of maturity transformation, since long-maturity projects are financed with demandable (shorter maturity) deposits. However, this seems to be incorrect because the loans in the model are also demandable—the bank can demand repayment at the interim date when deposits are withdrawn. That is, it is more appropriately viewed as a model of demandable loans financed with demandable deposits.

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Creation and Regulation of Bank Liquidity   187 and deposits. In Diamond and Dybvig (1983), deposits create loans, whereas in Donaldson, Piacentino, and Thakor (2018), loans create deposits, and deposits also create loans. This is consistent with the notion in Mester, Nakamura, and Renault (2007) that banks use information on deposit flows in making loans.13 While the financing of banks through liquid demand deposits leads to withdrawal risk for banks, it also provides an opportunity for banks to provide liquidity to borrowers off the balance sheet. The link between deposit-taking and loan commitments was first formalized by Kashyap, Rajan, and Stein (2002),14 who argued that banks face a demand for liquidity from their depositors as well as from customers who purchase loan commitments that can be exercised in the future, thereby obligating the bank to lend when customers exercise these commitments. This means that a pool of liquid assets that the bank keeps on hand can serve two purposes—meeting the liquidity needs of borrowers as well as those of depositors. There are diversification benefits associated with this costly holding of liquidity if the liquidity needs of borrowers and depositors are not perfectly correlated.15 This is a novel twist on the point made above that deposits and loans are intertwined in the sense that in Kashyap, Rajan, and Stein (2002), it is loan commitments and deposits that are intertwined. The fact that banks make loan commitments is related to the seminal contributions of Diamond (1984) and Ramakrishnan and Thakor (1984), which provided the microfoundations of banks as specialists in screening credit information and monitoring borrowers.16 Thus, banks as primary lenders make commitments to lend in the future. Such commitments create liquidity as they provide borrowers (partial) insurance against being rationed in the spot credit market (James, 1981; Blackwell and Santomero, 1982;

13  The Donaldson, Piacentino, and Thakor (2018) model does not have asymmetric information, so the bank is not learning anything from deposit flows. But the natural and endogenous synergy between deposits and lending in their model is consistent with the idea that there are multiple ways in which deposits and loans in a bank are intimately linked. This perspective points out that proposals, such as Gorton’s (1988), that deposit-taking and lending can be separated by having mutual funds replace deposits and having finance companies make loans, necessarily imply a loss in economic efficiency. 14 Thakor, Hong, and Greenbaum (1981) and Thakor (1982) pioneered theories on bank loan commitments. 15  As evidence, they report that loan commitments and transaction deposits are positively correlated across banks. Gatev, Schuermann, and Strahan (2009) test whether this leads to a diversification benefit and find it does: bank risk (stock return volatility) increases in unused commitments except for banks with high deposit levels. Building on this, Gatev, Schuermann, and Strahan (2006) argue that transaction deposits and loan commitments may be negatively correlated during crises since banks enjoy deposit inflows and greater demand for loan commitments during such times. Such inflows occur because banks are viewed as a safe haven given explicit government guarantees, access to the discount window and other emergency liquidity facilities, and additional support for too-big-to-fail banks (e.g., O’Hara and Shaw, 1990). 16  See also Leland and Pyle (1977), Millon and Thakor (1985), and Allen (1990). Coval and Thakor (2005) provide a theory of financial intermediation as a “beliefs bridge” between optimists and pessimists in which screening by the bank plays a role in the service the bank provides as an intermediary; higher bank capital leads to more screening.

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188   The Theory of Banking Morgan, 1994; Thakor, 2005), so that a commitment can give a borrower access to future liquidity even when it is unavailable in the spot credit market.17 Boot, Greenbaum, and Thakor (1993) show that loan commitments improve welfare ex ante, even though they represent only “illusory promises” in that the bank may choose not to honor its commitment when the borrower attempts a takedown. They model the bank’s choice as a tradeoff between reputational and financial capital. When the bank honors a loan commitment, it provides liquidity for the borrower but uses up its financial capital. When it does not honor a commitment (it invokes the “material adverse change” or MAC clause), it “liquefies” its illiquid reputation capital and preserves its financial capital. In Thakor (2005), a bank’s reputational concerns induce it to under-invoke the MAC clause during booms, resulting in over-lending (and excessive liquidity creation).

7.2.2  Empirical Evidence Comprehensive empirical measures of liquidity creation were non-existent until recently. To measure the output of the banking sector, studies typically focused on total assets, total lending, or different types of lending. Taking a cue from the theories, Berger and Bouwman (2009) develop several measures of liquidity creation.18 Using data on banks in the US, they show that large banks (assets over $1 billion) create over 80 percent of the banking sector’s liquidity despite accounting for only a small percent of all banks. They also document that banks create almost half of their liquidity off the balance sheet through loan commitments and similar claims to liquid funds. While many banks create positive liquidity, some create negative liquidity—these banks are liquidity absorbers. Most of the empirical studies in this area examine the relationship between capital and liquidity creation (see “Key Issue #1: Effect of Higher Capital Requirements on Bank Output” in this chapter for a discussion of those papers). Notable exceptions include: Berger and Bouwman (2017), who study the effect of monetary policy on liquidity creation and also show that excessive liquidity creation helps to predict crises; and Jiang, Levine, and Lin (2019), who examine the relation between competition and liquidity creation. More recently, Bai, Krishnamurthy, and Weymuller (2018) develop a liquidity mismatch index (LMI), which measures the mismatch between the market liquidity of an institution’s assets and the funding liquidity of its (on- and off-balance-sheet) liabilities. The LMI aims to identify the bank’s exposure to liquidity risk, in contrast to Berger and Bouwman’s (2009) measure, which focuses on bank liquidity creation. Liquidity creation obviously exposes the bank to liquidity risk, so these measures are related, but they are measuring different things. LMI works well as a measure of liquidity risk; it uses time-varying weights that incorporate market conditions and repo haircuts. In contrast, 17  Other explanations for the existence of loan commitments include: they provide a mechanism for optimal risk sharing (Campbell, 1978; Ho and Saunders, 1983), and they ameliorate informational frictions between the borrower and the bank (Berkovitch and Greenbaum, 1991; Boot, Thakor, and Udell, 1991). 18  Quarterly data on liquidity created by virtually every bank in the US from 1984:Q1 until “now” are available for research purposes on my website (updated regularly).

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Creation and Regulation of Bank Liquidity   189 Berger and Bouwman’s (2009) measures work well as measures of bank liquidity creation, and their preferred measure appropriately uses fixed weights. Berger et al. (2018) develop a measure of bank “liquidity hoarding,” which attempts to measure the amount of liquidity stockpiled by the bank, liquidity that could perhaps be productively deployed in lending. This is different from measuring either liquidity creation or liquidity risk exposure of the bank. Liquidity hoarding is higher when banks hold more liquid assets, fewer illiquid assets, and fewer off-balance-sheet loan commitments. Empirical studies on the use of loan commitments generally focus on corporate customers and document that over 80 percent of commercial and industrial lending is in the form of drawdowns under commitments. Melnik and Plaut (1986), Shockley and Thakor (1997), and Sufi (2009) provide detailed descriptions of loan commitment contracts and their specific features. Berger and Udell (1992) and Morgan (1994) document that credit lines reduce the risk of credit rationing during downturns. Consistent with this, Ivashina and Scharfstein (2010) show that after Lehman collapsed during the subprime lending crisis, there was a “run” by borrowers who drew down their loan commitments. There is also evidence, however, that banks renegotiated the terms for credit lines in their own favor during the crisis (Campello et al., 2011).

7.2.3  The Need for Regulation Given the demand for liquidity by both its (on- and off-balance-sheet) borrowers and depositors, the bank will trade off the costs and benefits of keeping liquidity on hand in deciding how much cash and other liquid assets to hold. However, just as deposit insurance lessens the bank’s need to worry about events that might induce depositors to run the bank, the discount window can cause banks to keep too low a level of liquidity to meet routine withdrawal risk. Why keep cash and other liquid assets lying around earning little or nothing if you know you can borrow at the discount window at a cost lower than the return you would earn by investing the cash?19 Of course, the central bank can eliminate this moral hazard by removing the deposit insurance and discount window safety nets. But this entails social costs because it could result in disruptive banking panics.20 Moreover, it might even disrupt the bank’s relationship loans if core deposits are withdrawn in large amounts, and this can add to the welfare losses (Song and Thakor, 2007). Rather than throwing out the baby with the bathwater, the central bank can deal with the moral hazard ­created by these back-stop liquidity safety nets by imposing a minimum cash-asset reserve. 19  This assumes that the return earned exceeds the costs associated with posting eligible collateral and the possible stigma associated with borrowing from the discount window mentioned above. 20  Merton and Thakor (forthcoming) point out another cost of removing deposit insurance: it exposes the bank’s depositors to bank-specific credit risk, which is socially inefficient.

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190   The Theory of Banking We now discuss these cash reserve requirements. Since the focus of regulators later shifted to capital requirements, we then examine the Basel I and Basel II capital requirements. It is only after the subprime lending crisis of 2007–9 that regulators as part of Basel III imposed both capital and liquidity requirements, so it is only toward the end of this chapter that we return to liquidity requirements.

7.2.4  Cash Reserve Requirements Feinman (1993) documents that cash reserve requirements have been imposed in the US as early as 1820, when commercial banks were state-chartered and did not have large amounts of deposits. However, they did issue bank notes which were often used as a medium of exchange. This initially only happened locally because it was challenging to gauge the solvency of far-away banks. To facilitate their usage over greater distances, banks voluntarily agreed to accept each other’s notes, provided that the issuing bank kept enough liquid funds at the redeeming bank as backing. A few states subsequently mandated that banks hold reserves against their notes and deposits. Reserve requirements were launched nationally in 1863 with the passage of the National Bank Act, which enabled banks with national charters to issue national bank notes and required them to hold a 25 percent reserve against notes and deposits.21 In 1864, this was reduced to 15 percent for banks located outside the largest cities. In 1874, reserve requirements on bank notes were replaced with a required redemption fund: banks were required to hold 5 percent of the value of the notes as a deposit with the Treasury (Champ, 2010).22 Reserve requirements did stay in place for deposits, which replaced bank notes as the preferred medium of exchange. Various bank runs and panics in the late nineteenth and early twentieth centuries demonstrated that reserve requirements could not safeguard the convertibility of deposits for the entire banking system (e.g., Calomiris and Gorton, 1991), in essence because a dollar of reserves could not concurrently meet a customer’s demand for cash and also satisfy reserve requirements. To maintain stability of the financial system, the Federal Reserve System was created in 1913; in it, Reserve Banks could act as lenders of last resort by accommodating banks’ temporary liquidity needs. While this seemingly eliminated the need for reserve requirements, they continued to be imposed on transaction and time deposits, albeit at lower levels than during the national banking era. Starting in 1917, banks could only satisfy these requirements by keeping non-interest-bearing balances at the Federal Reserve. By 1931, reserves were not only viewed as a source of liquidity for deposits, but also as a monetary policy tool used by the central bank to influence the expansion of bank 21  They also had to deposit 111 percent of (the lesser of) the face or market value of these notes in US government bonds with the US Treasury. In 1900, this was reduced to 100 percent. 22  Calomiris and Mason (2008) argue that this created economies of scope between note issuance and deposit-taking because banks that issued notes had lower marginal costs of maintaining reserves associated with deposit-taking.

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Creation and Regulation of Bank Liquidity   191 lending (Federal Reserve, 1933). To reduce the burden on small banks, which tended to hold high cash balances, banks were able to count vault cash to meet reserve requirements from 1950 onward. In the late 1960s, new liabilities that were functionally equivalent to deposits also became subject to reserve requirements. In the 1970s, rising interest rates increased the cost that banks incurred for satisfying reserve requirements, since the Federal Reserve paid no interest on reserves. This caused banks to leave the Federal Reserve System (Feinman, 1993). To stop this trend, Congress adopted the Depository Institutions Deregulation and Monetary Control Act (DIDMCA or MCA) of 1980 which mandated that all depository institutions—regardless of membership status—be subject to reserve requirements and be given access to the discount window. Regulation D of the Act specifies the reserve requirements. Initially, they were set at 3 percent on the first $25 million of transaction deposits and 12 percent on the rest, and 3 percent on non-transaction deposits. Over time, these percentages have declined, possibly to avoid disintermediation due to non-payment of interest on reserves. The Garn–St. Germain Act of 1982 introduced an exemption amount for transaction deposits, initially set at $2 million. The reserve requirement on non-transaction accounts was lowered to 0 percent in December 1990 and has been at that level ever since. In April 1992, the 12 percent rate was reduced to 10 percent and has stayed at that level. As of January 2019, the exemption amount is $16.3 million, a 3 percent rate is imposed on transaction deposits between $16.3 million and $124.2 million, and amounts above are subject to a 10 percent rate. Figure 7.1 Panel A shows the dollar amounts of required reserves and vault cash for the US banking sector from January 1960 to July 2018. While both required reserves and vault cash have increased over time, the banking system’s cash balances exceeded the reserve requirements from the late 1990s until the beginning of 2009, suggesting that depository institutions were able to satisfy their entire reserve requirement with vault cash during that period. Panel B contrasts the dollar amounts of required reserves with the total amount of reserves held by the US banking sector. The picture is striking. Before the subprime lending crisis, total reserves of the banking sector showed a steady increase (from $18.8 billion in January 1960 to $42.9 billion in July 2007) and were on average a mere 2.0 percent higher than required reserves. During the initial phase of the crisis, total reserves increased somewhat, but they exploded after the collapse of Lehman Brothers in September 2008, reaching a level of $860.2 billion by January 2009 (almost fourteen times the required level of $63.4 billion). Total reserves peaked at a record $2,842.0 billion by July 2014 (twenty times the required level of $142.9 billion) and had dropped to $2,014.6 billion (over ten times the required level of $190.5 billion) by July 2018. The dramatic increase in reserves during the crisis coincided with the Federal Reserve’s decision to pay interest on reserve balances for the first time in its history.23 23  The Financial Services Regulatory Relief Act (FSRRA) of 2006 authorized the Federal Reserve to pay interest on balances held by, or on behalf of, depository institutions starting October 1, 2011. Section 128 of the Emergency Economic Stabilization Act (EESA) of 2008 moved the effective date forward to

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192   The Theory of Banking Panel A: Required Reserves and Vault Cash in $ Billion (January 1960–July 2018)

200 180

Required reserves

160

Vault cash

140 120 100 80 60 40 20

1960-01 1962-01 1964-01 1966-01 1968-01 1970-01 1972-01 1974-01 1976-01 1978-01 1980-01 1982-01 1984-01 1986-01 1988-01 1990-01 1992-01 1994-01 1996-01 1998-01 2000-01 2002-01 2004-01 2006-01 2008-01 2010-01 2012-01 2014-01 2016-01 2018-01

0

Panel B: Total Reserves and Required Reserves in $ Billion (January 1960–July 2018) Total reserves Required reserves

1960-01 1962-01 1964-01 1966-01 1968-01 1970-01 1972-01 1974-01 1976-01 1978-01 1980-01 1982-01 1984-01 1986-01 1988-01 1990-01 1992-01 1994-01 1996-01 1998-01 2000-01 2002-01 2004-01 2006-01 2008-01 2010-01 2012-01 2014-01 2016-01 2018-01

3,000 2,750 2,500 2,250 2,000 1,750 1,500 1,250 1,000 750 500 250 0

Figure 7.1  Total Reserves, Required Reserves, and Vault Cash Over Time. Note: This figure focuses on reserves of the US banking sector from January 1960—July 2018. Panel A shows both the dollar amounts of required reserves and vault cash, while Panel B contrasts the dollar amounts of required reserves with the total amount of reserves held. Source: Aggregate Reserves of Depository Institutions and the Monetary Base, Not Seasonally Adjusted—H.3 Table 2.

October 1, 2008. While the interest rate on required reserves is intended to get rid of the implicit tax that reserve requirements used to impose on depository institutions, the interest rate on excess reserves gives the Federal Reserve an extra monetary policy tool. The Federal Reserve initially set the interest rate on required (excess) reserves at 10 (75) basis points below the average target fed funds rate over the reserve maintenance period. From December 18, 2008 onward, it has instead paid a fixed rate on both required and excess reserves. Through December 16, 2015, it paid a fixed rate of 25 basis points on both. Since then, both rates have steadily increased to: 0.50 percent on December 17, 2015; 0.75 percent December 15, 2016; 1.00 percent on March 16, 2017; 1.25 percent on June 15, 2017; 1.50 percent on December 14, 2017; 1.75 percent on March 22, 2018; and 1.95 percent on June 14, 2018.

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Creation and Regulation of Bank Liquidity   193 This has led many (e.g., Barrons, 2009; Edlin and Jaffee, 2009; Huffington Post, 2010) to conclude that banks are simply “parking” funds at the Federal Reserve—they do not want to lend since earning a sure return by sitting on funds kept at the Federal Reserve is more lucrative.24 Others (e.g., Keister and McAndrews, 2009) suggest that this perspective is incorrect, arguing that the increase in reserves merely mirrors the unprecedented scale of the Federal Reserve’s liquidity facilities and other credit programs. In Donaldson, Piacentino, and Thakor (2018), liquidity requirements reduce funding liquidity creation. Empirically, this raises an interesting question that deserves further investigation. For now, from a theoretical perspective at least, it seems that liquidity requirements and their limiting case of narrow banking (100 percent reserves) are both bad ideas when it comes to promoting funding liquidity creation.

7.2.5  Capital Requirements Prior to the Subprime Lending Crisis As discussed above, safety nets can facilitate liquidity creation. But these safety nets give rise to moral hazard in that the bank has a perverse incentive to increase risk at the expense of the deposit insurer—see Merton’s (1977) analysis showing that deposit insurance gives the bank a put option on its assets, and that the value of this option is decreasing in the bank’s capital. The observation that safety nets induce banks to lower their capital ratios is supported by the sharp drop in capital ratios (measured as aggregate book equity normalized by aggregate book assets of the banking sector) after the adoption of federal deposit insurance in the US in 1934 (see Figure 7.2). To increase bank capital and reduce the bank’s risk-taking appetite, regulatory monitoring and capital requirements can be used (e.g., Campbell, Chan, and Marino, 1992; Chan, Greenbaum, and Thakor, 1992; Merton and Bodie, 1992; Bhattacharya and Thakor, 1993; Thakor, 1996; Hellmann, Murdock, and Stiglitz, 2000).25 Formal capital requirements were introduced in the US only in 1981. Prior to the 1980s, supervisors merely applied informal and subjective measures, including managerial capability and loan portfolio quality, because they could not agree on a framework (FDIC, 2003). Starting in 1981, banks were subject to a leverage ratio of primary capital (mainly equity and loan loss reserves) to average total assets. The minimum requirements were not uniform across the three regulators (the Federal Reserve, the Office of the Comptroller of the Currency, and the Federal Deposit Insurance Corporation) but ranged from 5 percent to 6 percent. There were also differences internationally. Over the 24  To curb this, excess reserves may have to be subject to a maximum (Dasgupta,  2009) or taxed (Sumner, 2009). 25 Higher capital requirements may increase portfolio risk in certain circumstances (Koehn and Santomero, 1980; Kim and Santomero, 1988; Genotte and Pyle, 1991; Besanko and Kanatas, 1996). Mailath and Mester (1994) examine the regulator’s incentive to close banks and how that affects its ability to influence the riskiness of banks’ asset portfolios.

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194   The Theory of Banking 14%

12%

10%

8%

6%

4%

2%

2012

2015

2009

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2003

2000

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1991

1988

1985

1982

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1973

1976

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1967

1964

1961

1958

1955

1952

1949

1946

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0%

Figure 7.2  Capital Ratios Over Time (1934–2017). Note: This figure shows capital ratios of all insured commercial banks in the US from 1934–2017. The capital ratios are measured as aggregate book equity normalized by aggregate book assets of the banking sector. Source: Table CB14 of FDIC’s Historical Statistics on Banking

next few years, regulators worked together to devise a uniform capital framework necessary to ensure that banks around the world had adequate capital and were operating on a level playing field. The Basel Capital Accord (commonly referred to as Basel I), adopted in 1988, became partially effective for all US banks and thrifts at year-end 1990, and was fully implemented at year-end 1992. Basel I made three important advances: (i) it recognized that not all assets have equal risk and therefore introduced risk weights; (ii) it enforced capital requirements on off-balance-sheet activities for the first time; and (iii) it harmonized capital requirements across countries to eliminate artificial comparative advantages. Basel I primarily focused on credit risk and forced banks to risk-weight their assets and off-balance-sheet items based on their perceived credit risk. While loans to private borrowers and standby letters of credit serving as financial guarantees for loans were risk-weighted at 100 percent, residential mortgages and long-term loan commitments were weighted at 50 percent, claims on, or guarantees by, qualifying banks were weighted at 20 percent, and low-risk assets (e.g., cash, US government debt, and short-term loan commitments) were weighted at 0 percent. So banks had to hold more capital if they chose riskier assets. Banks were required to hold tier 1 capital of at least 4 percent of risk-weighted assets and total capital of at least 8 percent of risk-weighted assets.26 Tier 1 26  They had to meet interim minimum standards of 3.625 percent (tier 1 capital) and 7.25 percent (total capital) by year-end 1990.

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Creation and Regulation of Bank Liquidity   195 capital is comprised of shareholders’ equity and non-redeemable non-cumulative preferred stock. Total capital also includes capital/debt hybrids such as long-term subordinated debt (which counts as capital because it is at risk before deposits and other bonds). In 1991, US bank regulators (OCC, FRB, FDIC, and OTS) also passed the Federal Deposit Insurance Corporation Improvement Act (FDICIA), which introduced an additional leverage requirement and specified that to operate without regulatory restrictions, a bank must be adequately or well-capitalized. To be adequately (well-) capitalized, it must have a tier 1 leverage ratio of at least 4 percent (5 percent), a tier 1 risk-based ratio of at least 4 percent (6 percent), and a total risk-based capital ratio of at least 8 percent (10 percent). Soon after the introduction of Basel I, shortcomings became apparent. For example, capital requirements were the same on loans to highly-rated corporations and much riskier distressed firms. Furthermore, capital requirements were typically higher for onbalance-sheet loans than for off-balance-sheet exposures to the same borrowers even when the risks to the bank were similar. These shortcomings gave banks incentives to engage in regulatory capital arbitrage, that is, they tried to find ways to reduce their riskweighted assets without truly lowering risk. Basel II, initially published in June 2004, aimed to better align the minimum capital required with the underlying risks and focused on the denominator of the capital ratios. Credit ratings play a critical role: the risk weights used to calculate risk-weighted assets (the denominator in several capital ratios) depend on the credit assessments assigned by external rating agencies.27 Investment grade borrowers are subject to lower capital requirements than sub-investment grade or unrated borrowers. In contrast to Basel I, Basel II consists of three pillars. Pillar 1 encompasses risk-based capital requirements for credit risk, market risk, and operational risk (risks arising from people, systems, or processes). Unlike Basel I, it does not prescribe one approach, but offers banks three approaches for credit risk (the standardized approach, the foundation internal ratingsbased approach (F-IRB), and the advanced IRB approach (A-IRB))28 and for operational risk (the basic indicator approach, the standardized approach, and the advanced measurement approach (AMA)). The A-IRB for credit risk and the AMA for operational risk together are called the “Advanced Approaches.” Pillar 2 involves a supervisory review of banks’ internal assessments of capital and risk, giving regulators discretion to impose higher capital requirements. Pillar 3 promotes market discipline by mandating banks to increase public disclosure of capital and risk.

27  Credit ratings have their limitations because they are coarse indicators of default risk (e.g., Goel and Thakor, 2015). 28  The standardized approach groups exposures into several risk categories (as Basel I does), but the risk weights for loans to corporates, sovereigns, and banks depend on external credit ratings assigned to the borrower instead of being fixed. The F-IRB approach allows banks to use their own models to estimate probability of default (PD), while relying on the supervisor to provide estimates of loss given default (LGD), exposure at default (EAD), and maturity (M). The A-IRB approach allows banks with the most advanced risk management and modeling skills to provide all the estimates (PD, LGD, EAD, and M) needed to determine their capital requirement.

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196   The Theory of Banking The European Parliament approved Basel II for all banks in the EU in 2005 and formally adopted it in 2006 (European Parliament,  2011).29 While most banks in Europe can choose any of the three approaches, many member states require the very largest banks to adopt at least the A-IRB. In contrast to the EU, the US never fully implemented Basel II. US banking regulators adopted a final regulation only in late 2007 (Federal Reserve, 2007). It required the very largest banks (eleven or twelve “core banks” with consolidated total assets of at least $250 billion or with consolidated total on-­ balance-sheet foreign exposure of at least $10 billion) to apply the Advanced Approaches; other banks could obtain authorization to use those approaches (“opt-in banks”) or had to stay on Basel I. The rule stipulated that banks would first be subject to a one-year parallel run of Basel I and Basel II, and would then start a three-year transition period. However, the subprime lending crisis occurred and the Dodd–Frank Act outlawed the use of credit ratings in regulations, which made it impossible to implement Basel II since it relied heavily on such ratings. The focus thus shifted to Basel III (discussed in section 7.4.1.1).

7.3  From Originate-To-Hold (OTH) to a Mix of OTH and Originate-To-Distribute (OTD) and the Emergence of the Shadow-Banking System As discussed above, cash-asset reserve requirements steadily declined in the US until the subprime lending crisis for two main reasons. First, as a tool of prudential regulation, they simply became too costly since the Federal Reserve did not pay interest on reserves, and market interest rates—the shadow price of holding reserves—spiked up dramatically in the 1970s. Second, as a tool of monetary policy, reserve requirements were hardly ever used because they represented a rather blunt instrument compared to other tools like the discount window and fed funds borrowing rates. Thus, before Basel III, reliance on reserve requirements had fallen over the years and we were in a period in which banks were largely subject to capital requirements. Yet, as discussed below, there may be a role for both in moderating bank liquidity creation in the present-day economy. To properly understand these issues, we first need to step back and take a closer look at the economics of traditional banking and its evolution to modern-day banking.

29 Benink and Benston (2005) provide a more detailed discussion on changes in EU banking regulation.

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Creation and Regulation of Bank Liquidity   197

7.3.1 Originate-To-Hold The research on financial-intermediary existence implied that banks generate proprietary information about their borrowers.30 This then suggested that banks could use their information to resolve informational frictions and increase the surplus generated by the bank–borrower relationship. This insight paved the way for the emergence of literature on relationship banking which highlights the benefits of deep relationships between banks and their borrowers. The pioneering theoretical contributions in this area are Greenbaum, Kanatas, and Venezia (1989), Sharpe (1990), Rajan (1992), and Boot and Thakor (1994, 2000). Boot (2000) defines relationship banking as “the provision of financial services by a financial intermediary that: (i) invests in obtaining customer-specific information, often proprietary in nature; and (ii) evaluates the profitability of these investments through multiple interactions with the same customer over time and/or across products.” The first part highlights that banks obtain information while providing screening and/or monitoring services. The second part emphasizes the fact that information can be used in multiple interactions with the same customer, which allows the bank to reuse information. To address whether relationships benefit borrowers, empirical studies have typically included measures of duration, scope, distance, and/or the number of bank relationships in regressions to explain the cost and availability of credit. While the international evidence is at times mixed, most US studies tend to find clear benefits: stronger relationships result in lower cost, lower collateral requirements, loser covenants, and better access to credit (e.g., Petersen and Rajan, 1994; Berger and Udell, 1995; Prilmeier, 2017; for a review, see Degryse, Kim, and Ongena, 2009, and Chapter 14 in this volume).31 Consistent with this, bank loan announcements are associated with significantly positive abnormal returns (e.g., James, 1987; Billett, Flannery, and Garfinkel, 1995).32 Banks benefit as well—stronger lending relationships are associated with a higher probability of winning SEO underwriting business (Drucker and Puri, 2005)33 and future lending and investment banking business (Bharath et al., 2007). Small banks tend to form stronger relationships with customers than large banks, likely because they are better at processing soft information (Berger et al., 2005). Relationship banking involves the bank making the loan and holding it on its balance sheet, with bank monitoring and collateral requirements (Boot and Thakor, 1994, 2000). 30  Using unique data on small business borrowers, Mester, Nakamura, and Renault (2007) show that transaction accounts provide banks with ongoing information regarding borrowers’ activities, thereby facilitating bank monitoring. 31  The benefits of relationships seem stronger during or after bad times (e.g., Bolton et al., 2016; Beck et al., 2018). 32  In contrast to the short-run effect, Billett, Flannery, and Garfinkel (2006) find significant long-run underperformance after firms have obtained bank loans. 33  In contrast to evidence provided by Drucker and Puri (2005), Calomiris and Pornrojnangkool (2009) show that banks may charge higher prices when combining lending and underwriting.

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198   The Theory of Banking This is the so-called “originate-to-hold” model, in which banks fund relationship loans with core deposits. The loans are illiquid—banks keep them on their balance sheets until maturity. This reduces moral hazard on the side of the bank—the fact that the loans stay on the balance sheet gives the bank incentives to perform upfront screening and then monitor on an ongoing basis. Relationships can lose value if they have to be liquidated prematurely due to a bank run; often, a bank’s failure will result in the resolution authority arranging for the bank to be acquired by another institution, which results in a loss of the original relationship and its associated economic surplus, even if the loan is not liquidated.34 To prevent such runs and protect the value of relationships, deposit insurance and lender-of-last-resort facilities were introduced.

7.3.2 Originate-To-Distribute During the 1990s and 2000s, loan syndications, loan sales, and securitization skyrocketed, in essence moving banks more and more away from the “originate-to-hold” (OTH) model toward a mix of OTH and the “originate-to distribute” (OTD) model. Sufi (2007) focuses on loan syndications. He examines how information asymmetries between lenders and borrowers affect syndicate structures. He documents that lead banks retain more and form more concentrated syndicates when information asymmetries are more severe. Bord and Santos (2012) assess the impact of the OTD model on corporate lending. They document that while lead banks retained 21 percent of the term loans they originated in 1988, that share had dropped to a mere 3.4 percent by 2010. Banks’ increasing use of the OTD model helped to fuel the syndicated loan market from $339 billion in 1988 to an all-time high of $2.2 trillion in 2007. The secondary loan market transformed from a market in which banks hardly participated to an active market with volumes that rose from $8 billion in 1991 to $176 billion in 2005. While loan sales are easy to grasp, it is helpful to show how securitization works and how it contrasts with traditional banking. As shown in Figure 7.3 Panel B, the bank originates loans as it does in the traditional OTH model, but then transfers the loans to a trust called a Special Purpose Vehicle (SPV), which issues various tranches of debt claims called asset-backed securities (ABS) against this pool of loans. These ABS are sold to institutional investors and the money received by the SPV is transferred in part to the bank.35 Thus, like loan sales, securitization provides banks with extra funding that can be used to originate new loans. 34  Song and Thakor (2007) show theoretically how this influences the bank’s choice of funding mix between core deposits and purchased money. Berlin and Mester (1999) provide empirical evidence that banks with greater reliance on core deposits give their borrowers better insurance against negative shocks to their creditworthiness. Consistent with this, Ivashina and Scharfstein (2010) and Cornett et al. (2011) show that banks that relied more on (stable) deposits, cut their lending less during the subprime lending crisis. 35  The bank may also purchase some of these ABS and use them as collateral to obtain repo funding from institutional investors like money-market mutual funds.

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Creation and Regulation of Bank Liquidity   199 Panel A: Traditional Banking (OTH) Liquid claims against bank

$ Repayments Relationship Bank

Depositors

Borrowers

$ Deposits

$ Relationship loan

Panel B: Securitization in the Shadow Banking System (OTD) Special Purpose Vehicle (SPV)

Sell shares

$

$ SP to V sel ins ls A titu B tio S ns

Retail Investors

Bank transfers loans to SPV

Posts collateral (incl. ABS) Institutions

$

Bank receives Asset-Backed Securities (ABS) $ Repayments Borrowers

Bank $

$ Loan

Figure 7.3  Traditional Banking vs. Securitization in the Shadow Banking System. Note: This figure compares the Originate-To-Hold (OTH) model of traditional banking with the Originate-To-Distribute (OTD) model of the shadow banking system.

Greenbaum and Thakor (1987), presenting the first formal theoretical treatment of securitization, examine which assets banks will securitize, and show that with asymmetric information about borrowers’ payoffs, banks securitize higher-quality assets (see also Gorton and Pennacchi, 1995). Boot and Thakor (1993) show that banks may want to create tranches of claims against pooled assets, so as to diversify away idiosyncratic noise and then create information-sensitive claims that maximize issuer revenue. The push to  split up securities in Gorton and Pennacchi (1990) is demand-driven instead: uninformed investors can reduce their trading losses if they can trade relatively informationinsensitive securities. While these papers focus on the bright side of securitization, recent papers point to a dark side:36 it may negatively affect screening incentives since it allows lenders to pass onto others the loans they have originated (Aghion, Bolton, and  Tirole,  2004; Stiglitz,  2007).37 Evidence from the subprime lending crisis tends 36  Gorton and Haubrich (1990) argue that this is a natural way in which a market develops: initially, easy-to-value assets are sold; later, increasingly complex and risky contracts are made. Loutskina (2011) points at another dark side—securitization makes banks more susceptible to funding shocks when the securitization market is disrupted. 37  These problems may be more severe when the economy is doing well: Thakor (2005) and Dell’Ariccia and Marquez (2006) show that lending standards decline during economic booms. Hellwig (1994) focuses on the incentive effects of securitization and argues that it should be structured such that the

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200   The Theory of Banking to support this view (e.g., Mian and Sufi, 2009; Demyanyk and Van Hemert, 2011; Purnanandam, 2011; Dell’Ariccia, Igan, and Laeven, 2012; Keys, Seru, and Vig, 2012; Dai, Zhang, and Zhao, 2013), although skin in the game seems to improve banks’ screening incentives (Demiroglu and James, 2012). In Gennaioli, Shleifer, and Vishny (2013), securitization leads to greater bank interconnections and raises their exposure to tail risks. Banks may benefit from loan sales. Pennacchi (1988) shows that selling banks have an advantage in originating loans and a disadvantage in providing funding; the reverse holds for buying banks. James (1988) finds that loan sales can reduce the underinvestment problems of banks with risky debt. Firms may also benefit from loan sales. It may enable them to borrow more (Drucker and Puri, 2009; Gande and Saunders, 2012), and it can lower their cost of capital due to increased liquidity in the secondary loan market (Gupta, Singh, and Zebedee,  2008) or risk-sharing benefits between the originating bank and loan buyers (Parlour and Winton, 2013). There is also a dark side. Firms whose loans are sold by banks underperform their peers (Berndt and Gupta, 2009), maybe because banks sell loans of lower-quality borrowers and/or loan sales reduce bank monitoring since the bank–borrower relationship is broken.

7.3.3  Originate-to-Distribute and the Shadow-Banking System The OTD model fuelled the development of the so-called “shadow-banking system.”38 While a consensus definition does not exist, Bernanke (2010) defines shadow banks as “financial entities other than regulated depository institutions (commercial banks, thrifts, and credit unions) that serve as intermediaries to channel savings into investment.” Adrian and Ashcraft (2012) add that such channeling takes place “through a range of securitization and secured funding techniques,” highlighting the importance of securitization in shadow banking.39 The shadow-banking system includes institutions such as investment banks, brokerage houses, and finance companies; securitization structures such as asset-backed securities (ABS) and asset-backed commercial paper (ABCP); and key investors in securitized structures, such as money market mutual funds (MMMFs), which heavily rely on short-term funding like tri-party repurchase agreements (Repos) and commercial paper (CP). See Gorton and Metrick (2010), Adrian and Ashcraft (2012), Claessens et al. (2012), and Martin, Skeie, and Von Thadden (2014a) for more discussions on shadow banking.40 bank retains asset-specific return risks to ensure proper screening and monitoring of clients, that is, the securitizing bank needs the right kind of “skin in the game.” 38  The term “shadow banking” is attributed to money manager Paul McCulley (2007). 39  The Financial Stability Board (FSB, 2012a) describes the shadow-banking system more broadly as “credit intermediation involving entities and activities (fully or partially) outside the regular banking system” or non-bank credit intermediation. 40  Calomiris, Himmelberg, and Wachtel (1995) discuss how growth of the CP market was driven by growth of finance companies, and how it fuelled disintermediation by providing high-quality firms with a low-cost alternative to short-term debt.

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Creation and Regulation of Bank Liquidity   201 As in the case of the OTH model, banks create liquidity in the OTD model as well, since they continue to originate the loans that are subsequently sold or securitized. There are two key differences, however, from a liquidity creation perspective. The first is that with the OTH model, the risk associated with liquidity creation is borne by the bank, whereas with the OTD model this risk is borne largely by the investors who purchase the loans or securities created by securitization.41 The second difference is that funding for loans in the OTH model tends to come from (core) deposits, while funding for securitized structures in the OTD model typically comes eventually from Repos and CP, even though the pre-securitization origination of the loan may have involved deposit funding. Unlike core deposits, there is no deposit insurance backing Repos and CP funding, so runs are possible. Various papers document that such runs indeed occurred during the subprime lending crisis—see Gorton and Metrick (2012) for evidence on a “run on repos”42 and Covitz, Liang, and Suarez (2013) for evidence on “runs on ABCP.”43 These differences aside, loan sales and securitization do not alter the fact that bank-intermediated liquidity creation occurs in the economy—it merely reflects a change in the process by which this liquidity creation is occurring.

7.4  Regulation to Preserve Uninterrupted Liquidity Creation Going Forward Liquidity creation occupies an important seat at the table in both the OTH and OTD models. But for liquidity creation to not be ruptured, it is critical that banks operate with sufficiently high equity capital and liquidity. That became apparent during the subprime lending crisis, which brought issues regarding both to the forefront of the discussions, and has prompted a call for revised capital regulation and new liquidity regulation. We now discuss some of the key regulatory issues and the progress made in the implementation of new regulations in the US and Europe. We first focus on Basel III’s 41  Banks typically continue to bear some risk—they often provide guarantees and keep (part of) the lowest-rated tranche. 42  They focus on the bilateral (i.e., interdealer) repo market and interpret an increase in margin requirements (“haircuts”) as a run. Copeland, Martin, and Walker (2014) find that no such run seemed to have taken place in the tri-party repo market, which may have accounted for 50 to 60 percent of all outstanding repo in the US. Krishnamurthy, Nagel, and Orlov (2014) find similar results and argue that Gorton and Metrick’s (2012) “run on repo” is not the equivalent of a traditional bank run by depositors— to establish that, one should not analyze inter-dealer data but rather examine whether investors run on dealers. Martin, Skeie, and Von Thadden (2014a) show that increasing margin requirements can be stabilizing: while it results in some loss of funding, it is better than losing all funding, as seemed to have happened with Lehman. 43  Martin, Skeie, and Von Thadden (2014b) show under what conditions short-term funding markets such as the repo market are immune to expectation-driven runs and discuss the scope of regulation to stabilize such markets.

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202   The Theory of Banking capital requirements and then on its liquidity requirements. Bank capital requirements after the financial crisis are also discussed in Chapter 22 in this volume.

7.4.1  Capital Requirements for Traditional OTH Banking and for OTD Shadow Banking 7.4.1.1  Basel III The subprime lending crisis revealed important weaknesses in Basel I and II. Both Accords seemed to provide inadequate incentives for banks to hold sufficient capital. Moreover, these accords failed to appropriately incorporate the risks posed by securitization, lacked liquidity standards, and failed to incorporate systemic risks associated with the build-up of leverage in the financial system. Inadequate levels of capital may have led to imprudent asset choices by banks, which then raised solvency concerns that contributed to the drying up of liquidity for banks during the recent crisis. In response to these perceived shortcomings, various academics have written proposals. They argue that there are externalities, due to the safety net provided to banks, and thus social efficiency can be improved by requiring banks to operate with more capital, especially during financial crises (e.g., Kashyap, Rajan, and Stein,  2008; Hart and Zingales, 2011; Calomiris and Herring, 2012; Admati et al., 2014; Thakor, 2014; Acharya, Mehran, and Thakor, 2016).44 Consistent with the academic perspective, Basel III—released in December 2010— imposes higher capital requirements and raises the quality of capital to address the seeming deficiencies of the prior Basel Accords (BIS, 2010, 2013b). Figure 7.4 compares Basel II and Basel III capital requirements. First, Basel III increases the minimum tier 1 risk-based capital ratio from 4 percent to 6 percent, and requires that the common equity component of tier 1 capital (CET1) goes up from 2 percent to 4.5 percent to ensure that a bank holds sufficient truly loss-absorbing capital (both requirements fully phased in by January 1, 2015). It leaves the minimum total risk-based capital ratio unchanged at 8 percent. Second, to reduce procyclicality and better withstand future periods of stress, it introduces a capital conservation buffer (“CCB”—additional common equity tier 1 of 2.5 percent of risk-weighted assets, fully phased in by January 1, 2019). The CCB is the lowest of a bank’s actual minus its minimum capital ratio calculated based on three ratios: the CET1, tier 1, and total capital ratios. Third, to reduce systemic risk that has built up due to excessive credit growth, a country’s regulator may impose a countercyclical capital buffer (“CCyB”—additional common equity tier 1, generally of 0 percent to 2.5 percent of risk-weighted assets).45 This buffer is 44  The externalities include excessive risk-taking and excessive leverage, which increase the risk of crises, which adversely affect other banks and the real economy. 45  A bank-specific CCyB is calculated as the weighted average of the CCyB rates in the jurisdictions where the bank’s relevant credit exposures are located. Countries may implement a rate exceeding 2.5 percent for banks in their jurisdiction, and more than half of the EU and other advanced economies indicate they are willing to exceed this level (BIS, 2017). However, other countries do not have to apply buffers above 2.5 percent when implementing reciprocity.

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Creation and Regulation of Bank Liquidity   203 Leverage Ratio

Risk-based Capital Requirements 13.0% 11.0% 9.5% 7.0%

+ 0% to 2.5%

8.5%

+ 2.5%

6.0%

4.5%

+ 0% to 2.5% + 2.5%

10.5%

+ 0% to 2.5% + 2.5%

8.0%

+ 2.0% 8.0%

+ 2.5% 4.0%

3.0%

2.0% Common Equity Tier 1 (CET1) Risk-Based Capital Ratio

Tier 1 Risk-Based Capital Ratio

Total Risk-Based Capital Ratio

Basel III countercyclical capital buffer (CCyB) Basel III capital conservation buffer (CCB) Basel III minimum increase Basel II minimum In the US: * The CCyB, when used, will only apply to Advanced Approaches Banks. * The CCB applies to all banks. G-SIBs are subject to additional requirements: * Higher capital buffer in the form of a G-SIB surcharge of 1.0% to 3.5% * Total Loss Absorbing Capital (TLAC) standard (from 2019 onward)

Tier 1 Leverage Ratio (Tier 1 capital/ on- and off-balance sheet exposures) Basel III minimum US. implementation: 1) Leverage Ratio (Tier 1 capital/assets) ≥4% for all banks 2) Supplementary Leverage Ratio (SLR) ≥4% for Advanced Approaches Banks. 3) Enhanced Supplementary Leverage Ratio (eSLR): SLR ≥ 5% for G-SIBs and SLR ≥ 6% SLR for G-SIBs insured depository institutions SLR and eSLR is the US implementation of the Basel III Tier 1 Leverage Ratio.

Figure 7.4  Comparison of Basel II and Basel III Capital Requirements. Note: This figure shows the Basel II and Basel III risk-based capital requirements, and the Basel III tier 1 minimum leverage ratio. It also explains the US implementation of Basel III’s leverage ratio.

to be built up during good times and can be used during a financial cycle downturn, thus supporting the flow of credit during periods of financial stress. Table 7.1 presents the CCyB levels in the thirteen countries that have activated or are about to activate this buffer as of March 2019. The US has not activated the CCyB: some (including several Federal Reserve Presidents) argue that it should be activated, while others argue it should be scrapped since bank stress tests already impose increasing capital buffers (see Financial Times, 2018).46 46  Following the financial crisis, regulators realized the limitations of using only capital requirements, which are essentially backward looking in the sense that they depend on the risks of assets already on the bank’s books and not on the risks to which banks could be exposed under future economic stress scenarios. In many countries, large banks now have to be stress tested. Each stress test subjects a bank to hypothetical unfavorable economic scenarios (e.g., deep recession) to determine whether it has enough capital to

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204   The Theory of Banking

Table 7.1  Countercyclical Capital Buffers Country

CCyB

Announced on

Effective since

Bulgaria

0.500%

Sep. 2018

Oct. 2019

Czech Republic

0.500%

Dec. 2015

Jan. 2017

1.000%

Jun. 2017

Jul. 2018

1.250%

Dec. 2017

Jan. 2019

1.500%

Jun. 2018

Jul. 2019

1.750%

Dec. 2018

Jan. 2020

Denmark

0.500%

Mar. 2018

Mar. 2019

France

0.250%

Jul. 2018

Jul. 2019

Hong Kong

0.625%

Jan. 2015

Jan. 2016

1.250%

Jan. 2016

Jan. 2017

1.875%

Jan. 2017

Jan. 2018

2.500%

Jan. 2018

Jan. 2019

1.000%

Mar. 2016

Mar. 2017

1.250%

Nov. 2016

Nov. 2017

1.750%

May 2018

May 2019

Iceland

2.000%

Feb. 2019

Feb. 2020

Ireland

1.000%

Jul. 2018

Jul. 2019

Lithuania

0.500%

Dec. 2017

Dec. 2018

1.000%

Jun. 2018

Jun. 2019

Luxembourg

0.250%

Dec. 2018

Jan. 2020

Norway

1.000%

Dec. 2013

Jun. 2015

1.500%

Jun. 2015

Jun. 2016

2.000%

Dec. 2016

Dec. 2017

2.500%

Dec. 2018

Dec. 2019

0.500%

Jul. 2016

Aug. 2017

1.250%

Jul. 2017

Aug. 2018

1.500%

Jul. 2018

Aug. 2019

1.000%

Sep. 2014

Sep. 2015

1.500%

Jun. 2015

Jun. 2016

2.000%

Mar. 2016

Mar. 2017

2.500%

Sep. 2018

Sep. 2019

0.500% 1.000%

Mar. 2016 Nov. 2017

Mar. 2017 Nov. 2018

Slovakia

Sweden

United Kingdom

Note: This table shows which countries have implemented (or have announced implementation of) countercyclical capital buffers as of March 2019, and how their levels have changed over time. Sources: BIS, National Authorities, and European Systemic Risk Board (https:// www.esrb.europa.eu/national_policy/ccb/all_rates/html/index.en.html).

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Creation and Regulation of Bank Liquidity   205 Fourth, to constrain leverage and to introduce extra safeguards against model risk and measurement error, it supplements the risk-based capital requirements with a minimum leverage ratio (based on tier 1 capital to on- and off-balance-sheet assets) of 3 percent. The US imposes higher leverage ratios: a 4 percent tier 1 leverage ratio (calculated using on-balance-sheet assets only) on all banks; a 4 percent supplementary leverage ratio (“SLR”) on Advanced Approaches Banks, and 5 percent and 6 percent enhanced supplementary leverage ratios (“eSLRs”) on globally systemically important banks (“G-SIBs”) and their insured banking subsidiaries, respectively.47 Fifth, it subjects G-SIBs to additional loss absorbency requirements (extra common equity tier 1 of 1 percent to 3.5 percent of risk-weighted assets depending on assessed systemic importance, fully phased in by January 1, 2019).48 The US subjects each US G-SIB to a surcharge that is the higher of its Basel III surcharge (“method 1”) and a surcharge that takes the G-SIB’s reliance on short-term wholesale funding into account (“method 2”), with the latter typically being binding (Federal Reserve, 2016). Table 7.2 provides an overview of the G-SIB surcharges. The EU applies Basel III to all financial institutions. The US applies it to all US insured depository institutions, bank holding companies (BHCs) with at least $500 million in assets, and savings and loan holding companies. In April 2018, the Board of Governors issued two proposals relating to the capital requirements for large banking organizations: a “Stress Buffer Proposal” (Federal Reserve,  2018a) and a “Scale Back Enhanced Supplementary Leverage Ratio (eSLR) Proposal” (Federal Reserve, 2018b). The “Stress Buffer Proposal” aims to simplify capital rules for the thirty-nine banks subjected to the Federal Reserve’s annual stress test, the Comprehensive Capital Analysis and Review (CCAR), that is, BHCs with consolidated assets over $50 billion and intermediate holding companies of non-US banks. The proposal introduces two firm-specific, risk-sensitive capital buffer requirements: (i) A “stress capital buffer (SCB) requirement” calculated as stress test losses (= institution’s CET1 capital ratio minus its lowest projected CET1 capital ratio under the stress test’s severely adverse scenario) plus four quarters of planned common stock dividends scaled by riskweighted assets. The SCB would have to be at least 2.5 percent and would replace the 2.5 percent capital conservation buffer. The US G-SIBs would be required to add on

withstand their impact. These stress tests are forward looking. The European Central Bank’s stress tests cover approximately 70 percent of the banks across the Eurozone. The US initially only stress-tested the very largest banks. It then imposed on banks with assets between $10 billion and $50 billion one stress test a year; and on banks with assets above $50 billion two stress tests a year (one run by the Federal Reserve and one run by the bank itself as mandated by the Dodd–Frank Act). In 2018, the Dodd–Frank Act Stress Test requirement was eliminated for banks with assets less than $250 billion. 47  As discussed above, US banks had already been subject to a minimum leverage ratio (based on tier 1 capital relative to on-balance-sheet assets) since the early 1980s. 48  G-SIBs are banks whose distress or disorderly failure would significantly disrupt the wider financial system and economic activity (BIS, 2018). G-SIBs have been identified every year in November (from 2011 onward) based on five equally important characteristics: bank size, complexity, interconnectedness, lack of substitutability, and cross-jurisdictional activity.

Basel III G-SIB Surcharge

Actual Surcharge US G-SIBs

1 JP Morgan Chase

2.5%

3.5%

16 Credit Suisse

1.0%

2 Bank of America

2.0%

2.5%

17 Groupe Crédit Agricole

1.0%

3 Citigroup

2.0%

3.0%

18 ING Bank

1.0%

4 Deutsche Bank

2.0%

19 Mizuho FG

1.0%

G-SIB

G-SIB

Basel III G-SIB Surcharge

5 HSBC

2.0%

20 Morgan Stanley

1.0%

6 Bank of China

1.5%

21 Nordea

1.0%

7 Barclays

1.5%

22 Royal Bank of Canada

1.0%

8 BNP Paribas

1.5%

23 Royal Bank of Scotland

1.0%

9 China Construction Bank

1.5%

24 Santander

1.0%

10 Goldman Sachs

1.5%

25 Société Générale

1.0%

2.5%

11 Industrial and Commercial Bank of China Ltd

1.5%

26 Standard Chartered

1.0%

12 Mitsubishi UFJ FG

1.5%

27 State Street

1.0%

13 Wells Fargo

1.5%

14 Agricultural Bank of China

1.0%

15 Bank of New York Mellon

1.0%

2.0% 1.5%

28 Sumitomo Mitsui FG

1.0%

29 UBS

1.0%

30 Unicredit Group

1.0%

Actual Surcharge US G-SIBs

3.0%

1.5%

Note: This table shows the Basel III G-SIB surcharges and the actual (higher) surcharges the Federal Reserve imposes on US G-SIBs as of November/December 2017. Sources: FSB (2017) and US G-SIBs’ websites.

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Table 7.2  G-SIB Surcharges

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Creation and Regulation of Bank Liquidity   207 their G-SIB surcharges; (ii) A “stress leverage buffer requirement,” calculated in a similar way as the SCB, will be imposed in addition to the Basel III minimum 4 percent Tier 1 leverage ratio requirement. The “Scale Back Enhanced Supplementary Leverage Ratio (eSLR) Proposal” is only applicable to US G-SIBs and their insured bank subs: their eSLRs are currently 2 and 3 percentage points higher than the standard 3 percent SLR imposed on other banks. The proposal would replace these supplements with a supplement equal to half of a BHC’s G-SIB surcharge, in an attempt to tie the supplement to the institution’s systemic footprint. If the G-SIB surcharge is 3.5 percent, the eSLR would decline from 5 percent to 4.75 percent at the holding company level and from 6 percent to 4.75 percent at the bank level. The Federal Reserve estimates that this proposal will reduce the amount of required capital at the holding company by $400 million across all eight G-SIBs, and by $121 billion at the bank level.49 Some argue that Basel III is not aggressive enough and that higher capital requirements are needed (e.g., Financial Times, 2012; Haldane and Madouros, 2012; Bloomberg, 2013; Passmore and Von Haften, 2017).50 In deciding on the appropriate level (and form) of future capital requirements, two key issues need to be considered: the effect on bank output, and the need for capital regulation in the shadow-banking system.

Key Issue #1: Effect of Higher Capital Requirements on Bank Output The first issue is how higher capital requirements affect bank output (lending or liquidity creation).51 Bankers are vocal in this respect—they claim that increases in capital would negatively affect their performance and lead to less lending. The academic literature suggests a more complex picture. The theories produce opposite predictions. Some predict that the relation between capital and bank liquidity creation or lending should be negative (e.g., Diamond and Rajan, 2001) because demandable deposits help to resolve a hold-up problem that cannot be resolved by bank capital.52 Others argue that capital facilitates liquidity creation and other forms of bank output, in part because it helps to absorb the risks associated with those activities and improves incentives (e.g., Bhattacharya and Thakor,  1993; Allen and Santomero, 1998; Allen and Gale, 2004; Repullo, 2004; Von Thadden, 2004; Coval and Thakor,  2005; Begenau,  2018). The funding liquidity creation theory of Donaldson, Piacentino, and Thakor (2018) also predicts a positive effect of bank capital on liquidity creation.

49  See footnotes 27 and 29 in Federal Reserve (2018b) for further details on these numbers. 50  The Systemic Risk Council, chaired by former FDIC Chairman Sheila Bair, proposes a minimum leverage ratio of 8 percent (2012). Admati and Hellwig (2013) propose it should be 20 to 30 percent. Passmore and Von Haften (2017) estimate that G-SIB surcharges should be 375–525 basis points higher, and that some very large and systemically important banks that are currently not subject to these charges should be subjected to a 225 basis point surcharge. 51  For an earlier discussion on this, see Berger, Herring, and Szego (1995). 52  Klimenko et al. (2016) focus on aggregate bank capital and show that minimum capital requirements reduce excessive lending.

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208   The Theory of Banking The US evidence is mixed. In the early 1990s, US regulators imposed new leverage requirements, as well as the Basel I risk-based capital standards. Many studies conclude that the leverage requirements may have reduced lending (e.g., Berger and Udell, 1994; Hancock, Laing, and Wilcox, 1995; Peek and Rosengren, 1995), while Thakor (1996) shows that the risk-based capital requirements may have had a similar effect, at least in the short run. However, the unusual combination of several major changes in capital regulation, a recession, and a toughening of supervision makes it challenging to separate the different effects and draw general conclusions. European evidence suggests that the effect of higher capital requirements differs by bank type and the state of the business cycle. Using data from the UK, Aiyar, Calomiris, and Wieladek (2012) find that increases in minimum capital requirements are associated with a decline in lending by some (UK banks and branches of foreign banks) and an increase in lending by others (subsidiaries of foreign banks). Using unique data from changes in capital regulation in Spain, Jiménez et al. (2017) show that countercyclical capital buffers mitigate the effect of business cycles—while such buffers lead to less credit in good times, they result in more lending in bad times. The studies discussed above focus on capital “requirements,” and Thakor’s (2014) conclusion is that an increase in capital requirements often leads to a temporary reduction in lending as banks adjust to the new regime. But this is different from the issue of whether higher capital in banks leads to higher or lower lending. Many papers have focused directly on this issue, and the general conclusion is that there is a significant reduction in lending following a decline in capital. For example, this happened when capital declined due to loan losses in the 1920s to the 1930s (e.g., Calomiris and Wilson, 2004) and the late 1980s to the early 1990s (e.g., Peek and Rosengren, 1995), consistent with a positive causal effect of bank capital on bank lending. Using data on 165 large US BHCs from 1992 to 2009, Berrospide and Edge (2010) also find that higher capital (actual level or measured relative to an estimated target) is associated with higher loan growth, although the effect seems to be small. Francis and Osborne (2012) use data on banks in the UK from 1989 to 2007 to show that banks with greater surplus capital have higher growth in lending and off-balance-sheet activities. They argue that higher capital requirements would reduce the amount of surplus capital and that a positive relationship between surplus capital and lending should be viewed as evidence that higher capital requirements reduce lending. While this argument may be valid in the short run in which capital is hard to adjust, it does not seem appropriate in the long run. Using data from 2001 to 2011, Carlson, Shan, and Warusawitharana (2013) find that banks with higher capital ratios tend to experience stronger loan growth during and shortly after the recent financial crisis, not during other times. Chu, Zhang, and Zhao (2017) document a positive effect of capital on lending. They show that higher-capital banks and Troubled Assets Relief Program (TARP) recipients participating in the same syndicated loan contribute more to that loan. Using data from 1998 to 2015 from forty-seven countries, Klein and Turk-Ariss (2018) show that higher capital ratios improve lending. The effect on the economy is large: a one percentage point higher capital ratio raises real GDP growth by 1.25 percentage points.

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Creation and Regulation of Bank Liquidity   209 Some recent empirical contributions in this area define bank output as liquidity creation instead of lending, thereby permitting a test of the predictions of liquidity creation theories. Berger and Bouwman (2009) examine the relation between bank capital and the amount of liquidity they create using data on banks in the US from 1993 to 2003. For large banks, which create by far most of the liquidity (over 80 percent), they find a positive relationship (driven largely by the effect on off-balance-sheet activities), whereas for small banks, the relationship is negative. Evidence on this topic using data from Russia (Fungáčová, Weill, and Zhou, 2010) and Europe (e.g., Distinguin, Roulet, and Tarazi, 2013; Horvath, Seidler, and Weill, 2014) is starting to emerge. It tends to suggest that capital and on-balance-sheet liquidity creation are negatively related outside the US. While the papers discussed above examine the effect of higher capital requirements and higher capital on bank output, it is important to remember that a key reason to impose higher capital requirements is to obtain a safer and less fragile banking sector.53 Consistent with this objective, Mehran and Thakor (2011) show theoretically and find empirically that bank capital and bank value are positively related in the cross-section. Beltratti and Stulz (2012) provide evidence that banks with higher tier 1 capital ratios before the recent subprime lending crisis showed better stock performance during the crisis. Berger and Bouwman (2013) show that capital helps small banks to survive at all times (during crises and normal times), and helps large banks primarily during banking crises. Baker and Wurgler (2015) document that in the past forty years, banks with higher capital had lower betas but higher stock returns, leading them to conclude that higher capital requirements will increase the cost of capital in banking, although they will also make banks systematically safer. Bouwman, Kim, and Shin (2018) show that highercapital banks earn higher risk-adjusted returns during bad times than low-capital banks, while earning similar returns during other times. In sum, it appears that the effects of higher capital requirements on bank output are mixed, but in the US, this is in part because the introduction of higher capital requirements in the early 1990s coincided with changes in the type of capital requirements and a recession, which makes it harder to interpret the results. In contrast, it seems that higher capital generally benefits banks and their borrowers, reduces bank-specific and systemic risks (e.g., Farhi and Tirole, 2012; Acharya and Thakor, 2016), and reduces the need for taxpayer-funded bailouts (e.g., Farhi and Tirole, 2012).54 See also Thakor (2014) for an extensive review of the theories and empirical evidence on these topics. 53  Several recent papers examine how capital injections by the government affect bank lending in the US (e.g., Black and Hazelwood,  2013; Li,  2013; Duchin and Sosyura,  2014) or liquidity creation in Germany (Berger et al., 2016). 54  Loan rates may also be affected. Specifically, if higher capital requirements cause banks to operate with more capital, then two effects may be generated. First, the replacement of tax-advantaged debt with equity may increase the bank’s weighted average cost of capital, putting upward pressure on loan rates. Second, higher capital will reduce the bank’s debt funding cost (due to the cushioning effect of capital and also its incentive effects), and this reduction may be large enough to increase the bank’s return on equity, so that higher capital in the bank may exert downward pressure on loan rates. The overall effect of bank capital on loan rates may thus turn out to be small. Simulations by Hanson, Kashyap, and Stein (2011) support this notion—depending on the chosen scenario, a 10 percentage point increase in the capital ratio

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Key Issue #2: Capital Requirements and the Shadow-Banking System A second issue is that imposing higher capital requirements might lead to widespread migration of financial intermediation toward the less regulated shadow-banking system (Hanson, Kashyap, and Stein, 2011; FSB, 2012b). This is a concern since the subprime lending crisis showed that the absence of an explicit government safety net in this market can cause runs and that liquidity can dry up for institutions in the shadow-banking system, which can then threaten overall liquidity creation in the economy. Many of these institutions are considered “systemically important,” so the government has an (ex post) incentive to rescue them, as we saw with non-deposit-insured institutions like Bear Stearns and American International Group (AIG) in the subprime lending crisis. One way to address this is to impose capital requirements on shadow banks. Basel III includes steps in this direction (FSB,  2011, 2012b): it increases capital requirements for short-term liquidity facilities provided to securitization vehicles, and for exposures to unregulated financial institutions regardless of size. The Basel Committee decided against increasing capital requirements related to banks’ short-term liquidity facilities to MMFs, fearing this could have unintended consequences and might be unnecessary in light of the introduction of the liquidity coverage ratio. The Dodd–Frank Act imposes capital requirements on shadow banks that are considered SIFIs. The Financial Stability Oversight Council proposed in early June 2013 to designate AIG, Prudential Financial, and GE Capital as such. More steps are likely needed to prevent migration toward the shadow-banking system. Gorton and Metrick (2010) discuss several additional proposals, including the conversion of MMFs that offer bank-like services (transaction accounts and the ability to withdraw funds on demand at par) into “narrow savings banks” with appropriate supervision, government insurance, and access to lender-of-last-resort facilities.

7.4.2  Liquidity Requirements—International and US Developments Although reserve requirements have taken a back seat in US regulation, a desire to have explicit liquidity requirements for financial institutions grew in the US and in other countries after the subprime lending crisis. These developments are reviewed here. The Basel Committee introduced liquidity regulation as part of Basel III. This was a departure from Basel I and II, which focused on strengthening capital regulation. The original December 2010 liquidity framework (BIS, 2010) specifies two minimum liquidity requirements with complementary objectives. The first is the liquidity coverage ratio (LCR) which promotes short-term resilience: to survive a specified stress scenario which lasts one month, banks have to operate with enough high-quality liquid assets. would cause loan rates to increase by a mere 25 to 45 basis points. Cross-country studies on the relationship between capital (not capital requirements) and loan rates tend to find evidence consistent with this (e.g., Demirgüç-Kunt and Huizinga, 1999; Saunders and Schumacher, 2000).

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Creation and Regulation of Bank Liquidity   211 The second is the net stable funding ratio (NSFR) which promotes long-run resilience: to be able to survive an extended closure of wholesale funding markets, banks have to operate with a minimum acceptable amount of “stable funding” over a one-year period. Below, we discuss both: we first cover the BIS minimum standards and then their US implementations. The LCR requires that a bank’s stock of unencumbered high-quality liquid assets (HQLA) generally equals or exceeds its projected net cash outflows (NCOF) over a 30-day HQLA horizon under a stress scenario prescribed by the supervisors: LCR = ≥ 100% .55 NCOF

HQLA, the numerator, includes three groups of assets, with a different expected ability to serve as liquid assets during periods of stress. Level 1 assets (cash, central bank reserves, and certain marketable securities backed by sovereigns and central banks) are considered the most liquid. Level 2A assets (certain government securities, covered bonds, and corporate debt securities) are viewed to be less liquid, and Level 2B assets (lower-rated plain-vanilla senior corporate bonds and certain residential mortgagebacked securities) are viewed to be the least liquid. Therefore, Level 2A (2B) assets are discounted by 15 percent (50 percent) and may not account for more than 40 percent (15 percent) of the bank’s total stock of HQLA. NCOF, the denominator, is defined as total expected cash outflows minus total expected cash inflows in the specified stress scenario for the next thirty days. Total expected cash outflows are calculated by multiplying the outstanding balances of different types of liabilities and off-balance-sheet commitments by the rates at which they are expected to run off or be drawn down in the prescribed stress scenario. For example, unsecured interbank loans are assumed to run off fully if they come due during the stress scenario, while deposits are assumed to run off by 5 percent or 10 percent, depending on the type of deposit. To ensure a minimum level of HQLA holdings at all times, total cash inflows are subject to a cap of 75 percent of total expected cash outflows. The LCR is supposed to stay above 100 percent, but can briefly drop below this floor during times of stress (BIS, 2013b). The NSFR requires that a bank has a sufficient level of available stable funding (ASF) to ASF meet their required stable funding (RSF) over a one-year horizon: NSFR = > 100% .56 RSF

ASF, the numerator, is the portion of capital and liabilities expected to be reliable over a one-year period. ASF is determined by first assigning capital and liabilities to five buckets, then weighting the amount in each bucket by an ASF factor (100 percent, 95 percent, 90 percent, 50 percent, or 0 percent), and finally summing the weighted amounts. The ASF factors aim to measure the stickiness of each funding source—the less likely it is to run, the higher the ASF factor.57 RSF, the denominator, is calculated 55  The BIS first published the LCR in December 2010 (BIS, 2010) and issued the full text of a revised LCR in January of 2013 (BIS, 2013b). The LCR was phased in gradually from January 1, 2015, with a minimum requirement starting at 60 percent, increasing in 10 percent annual increments to 100 percent on January 1, 2019. 56  The BIS issued its final standard for the NSFR on October 31, 2014 (BIS, 2014). 57  A 100 percent ASF factor is assigned to capital instruments with residual maturities exceeding one year, and to borrowings and liabilities (including term deposits) with residual maturities exceeding one

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212   The Theory of Banking using a similar process as that used for the numerator. Assigned RSF factors include 0 percent, 5 percent, 10 percent, 15 percent, 50 percent, 65 percent, 85 percent, and 100 percent. Activities that are more liquid receive the lowest RSF factors (and require less stable funding) because they can act as a source of extended liquidity in case of stress.58 The US versions of the LCR and NSFR differs somewhat from their Basel III counterparts, as explained in the LCR final rule (Federal Reserve, 2014) and the NSFR notice of proposed rulemaking (Federal Reserve, 2016). First, the US LCR rule and NSFR proposal use a more conservative definition of HQLA. For example, securities issued by financial institutions and some privately-issued mortgage-backed securities do not count as HQLA under the US rule, but do count as such under Basel III.59 In addition, the US LCR rule uses the largest liquidity mismatch over a 30-day stress period, while the Basel standard focuses on cumulative cash flows over this window. Second, the US LRC rule and NSFR proposal differ by bank size. The full LCR and full NSFR apply to BHCs with at least $250 billion in consolidated assets, BHCs with at least $10 billion in on-balancesheet foreign exposure (e.g., loans to foreign firms), and depository institutions with at least $10 billion in consolidated assets that are subsidiaries of covered BHCs. A modified LCR and a modified NSFR apply to BHCs with consolidated assets between $50 billion and $250 billion that are not subject to the full versions. These institutions have to meet less stringent requirements: their net cash outflows and required stable funding (the denominators in the LCR and NSFR, respectively) are multiplied by 70 percent. No LCR

year. ASF factors of 95 percent and 90 percent are given to stable, non-maturity (demand) deposits and/ or term retail and small business deposits with residual maturities less than one year. A 50 percent ASF factor is assigned to, for example, operational deposits and funding with a residual maturity of less than one year provided by non-financial corporate customers, sovereigns, public sector entities, and multilateral and national development banks. A 0 percent ASF factor is assigned to, for example, other liabilities without a stated maturity. 58  Cash and central bank reserves receive a weight of 0 percent. Unencumbered Level 1 assets (except those receiving a 0 percent RSF) are weighted at 5 percent. Unencumbered loans to financial institutions with remaining maturities up to six months are weighted at 10 percent or 15 percent; the latter weight is also assigned to unencumbered Level 2A assets. A 50 percent RSF factor is assigned to unencumbered Level 2B assets, HQLA that are unencumbered for six to twelve months, loans to financial institutions and central banks with residual maturity of six to twelve months, operational deposits, and non-HQLA with a remaining maturity up to one year. A 65 percent RSF factor is for unencumbered residential mortgages and other unencumbered loans not included above with a remaining maturity of at least one year that would receive a 35 percent or lower risk weight under the Basel II standardized approach. An 85 percent RSF factor is for cash/securities posted as initial margin for derivatives; unencumbered not-indefault securities that do not qualify as HQLA with a remaining maturity of at least one year; exchangetraded equities; and physical traded commodities. A 100 percent RSF factor is for all assets that are encumbered for at least one year, and all other assets not included above (e.g., non-performing loans, loans to financial institutions with a remaining maturity of at least one year, non-exchange traded equities, fixed assets, subsidiary interests, and defaulted securities). 59  The 2014 rule did not treat securities issued by public sector entities below the national level as HQLA. The Federal Reserve changed its rule in 2016, permitting a limited amount of municipal obligations to be included in Level 2B HQLA. An interim final rule issued by the Board, the OCC, and FDIC in August 2018 allows municipal obligations that are investment grade, liquid, and readily marketable to be treated as Level 2B HQLA (Federal Reserve, 2018c).

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Creation and Regulation of Bank Liquidity   213 or NSFR requirements are imposed on banking organizations with consolidated assets of less than $50 billion and on-balance-sheet foreign exposure of less than $10 billion. The three US agencies are expected to issue a final rule on the NSRF in 2019. The Treasury Department recommended in 2017 that US regulators delay the implementation of the NSFR until they have been able to appropriately assess and calibrate it (Mnuchin and Phillips, 2017). Various opponents urge regulators not to implement the NSFR. The president of the American Bankers Association argues that it would impose significant needless costs, given that other regulations (including the LCR and G-SIB surcharge) already limit reliance on short-term funding and encourage stable funding (ABA Banking Journal, 2017).

Key Issue #1: Better Understanding Liquidity Requirements Very few papers try to examine the purpose and effect of liquidity regulation. Allen and Gale (2017) provide a useful overview of this short literature. We highlight some recent contributions that explicitly aim to examine the optimality and design of liquidity requirements in light of Basel III. Diamond and Kashyap (2016) consider monopolist banks that provide liquidity insurance to customers with uncertain withdrawal needs. They make two modifications to Diamond and Dybvig (1983). First, the bank can invest in a liquid asset with a return greater than the return from liquidating illiquid assets, so selling liquid assets is an efficient way to meet withdrawal needs. Second, only some customers receive a signal about the bank’s health so in case of a run, not all customers will run. They show that regulations similar to the LCR and NSFR can make runs less likely. Dewatripont and Tirole (2018) focus on the LCR, since their model only has a single liquidity shock, which does not allow them to distinguish between two horizons. They show that banks’ liquidity buffers should not cover extreme risks—in such cases, it is socially optimal for the state to step in and provide liquidity assistance. Since banks underinvest in liquidity under laissez-faire, it is important to regulate liquidity coverage. The privately and socially optimal liquidity solution is for banks to meet a liquidity requirement similar to the LCR (hold sufficient low-yield, highly liquid assets to meet ordinary liquidity shocks, and sufficient higher-yield, less liquid assets to address larger shocks) and for the state to provide liquidity support in case of exceptional liquidity shocks. In contrast, Thakor (2018) argues against liquidity requirements, suggesting that their genesis in Basel III may be based on a misreading of the subprime lending crisis as a liquidity crisis, when the empirical evidence suggests it was an insolvency risk crisis. His argument is partly based on Donaldson, Piacentino, and Thakor (2018), in which liquidity requirements reduce liquidity creation. Berger and Bouwman (2016) show correlations between the two Basel liquidity requirements and bank liquidity creation. They do this separately for small, medium, and large banks. Their results suggest that the three capture different things, suggesting that it is important to measure all three and to conduct new research to see which are better at predicting performance of individual banks and the banking sector.

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Key Issue #2: Understanding How Liquidity Requirements Interact with Capital Requirements Liquidity requirements and capital requirements are designed to address two different problems and affect different sides of the balance sheet. Specifically, liquidity requirements deal with withdrawal risk on the liability side by stipulating that a fraction of the bank’s assets be held as cash or deposits with the central bank, while capital requirements deal with asset-substitution risk by stipulating that a fraction of the bank’s liabilities be in the form of equity. Nonetheless, liquidity requirements and capital requirements may interact. Little research has been done in this important area. A few recent papers address this issue theoretically. Calomiris, Heider, and Hoerova (2015) incorporate two unique aspects of cash relative to capital: the value of cash is observable at all times, and cash is riskless, making it impervious to risk shifting. These features mean that cash mitigates both liquidity risk associated with exogenous withdrawal shocks and endogenous asset risk. Specifically, the market recognizes that banks with higher cash holdings make more prudent risk-management decisions and thus will be more willing to provide funds, which implies that in bad states of the world, banks will avoid higher asset risk and increase their cash holdings to preserve market confidence. A key insight of the paper is that liquidity requirements should not be viewed as a mere insurance policy to deal with liquidity risk that may occur in a financial crisis, but also as a prudential regulatory tool that—like capital requirements—can limit default risk and encourage good risk management. That is, liquidity requirements and capital requirements act as (imperfect) substitutes. Acharya, Mehran, and Thakor (2016) examine optimal capital regulation for banks that face two moral hazard problems: shirking by managers and risk-shifting by shareholders. A simple minimum capital requirement can rule out the second problem, but not the first problem, since it makes debt so safe that it takes away managers’ monitoring incentives. To deal with both moral hazards, they propose two kinds of capital requirements: a regular minimum capital requirement and a “special capital account.” The regular capital can be used to invest in any type of assets. The special capital has to be invested in relatively safe and liquid assets such as Treasuries, and can be viewed as a “capital-cum-liquidity” requirement. The key innovation in the paper is that the special capital belongs to the bank’s shareholders as long as the bank is solvent, but when the bank is insolvent, it goes to the regulator, not the bank’s creditors. This means that this special capital is “invisible” to the bank’s creditors and does not dilute their incentive to discipline the bank. Carletti, Goldstein, and Leonello (2018) examine how capital and liquidity affect bank stability. They show that higher capital reduces the likelihood of a solvency crisis, while higher liquidity increases it. In their model, the probability of a liquidity crisis crucially depends on the bank’s capital and liquidity position. When capital or portfolio liquidity are low, an increase in either makes a liquidity crisis more likely, since both raise debtholders’ repayment. When capital or liquidity are intermediate, injections of capital or liquidity are beneficial. When capital or liquidity are high, the main risk facing a bank is

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Creation and Regulation of Bank Liquidity   215 a solvency crisis, for which higher capital is beneficial, but more liquidity is not since it makes a solvency crisis more likely. They show that capital and liquidity requirements only restore full efficiency when market funding conditions are good and the cost of capital and liquidity for banks is small. Thakor (2018) concludes that liquidity requirements, at least as presently designed, are counterproductive: they seem to lead to lower bank lending and may not even reduce liquidity risk.60 The paper points out that lowering/eliminating liquidity requirements and increasing capital requirements will reduce the likelihood of banks facing short-term funding dry-ups during times of stress, which will reduce their reliance on central banks to flood the market with liquidity. Moreover, this will free up loanable funds for banks to invest in stimulating economic growth, and will lead to a more transparent, simpler, and efficient regulatory structure. The observations by Calomiris, Heider, and Hoerova (2015) and Thakor (2018) are in line with the idea that capital and liquidity requirements are substitutes.61 Robust enough capital requirements minimize the risk of banks not having access to sufficient market liquidity when they need it. This, in turn, reduces the need to impose onerous liquidity requirements that freeze assets in the sense that they cannot be invested productively. Moreover, the “L” in CAMELS, the supervisory rating system applied to every bank in the US and many banks outside the US to evaluate banks’ performance and determine their weaknesses and strengths,62 refers to bank liquidity, so liquidity is attended to as part of the normal bank examination process. Finally, at the end of the day, it is the job of the central bank as an LOLR to provide banks with liquidity.63 It seems far more efficient for the LOLR to provide liquidity to banks when needed than to require each bank to hold sufficient liquid assets on its balance sheet. The optimal design of both capital and liquidity requirements can only be addressed with a good understanding of the nature of government intervention in financial crises. It would be preferable to acknowledge up front that such intervention is unavoidable and ask how capital and liquidity requirements should be designed ex ante, conditional on knowing that bailouts will occur ex post in circumstances that can be identified ex ante.

60  Barroso, Gonzalez, and Nazar Van Doornik (2017) show that higher reserve requirements in Brazil reduced the credit supply by its banks. The ClearingHouse expects that the NSFR will be a binding constraint for banks and can hence impose substantial costs on the economy because it may reduce lending (Covas and Nelson, 2016). 61  In contrast, Van den Heuvel (2018) argues that they are not substitutes. His model shows that it is socially optimal for liquidity requirements to deal with liquidity risk and for capital requirements to reduce credit risk. 62  CAMELS stands for capital adequacy, asset quality, management, earnings, liquidity, and sensitivity to market risk. 63  See Calomiris, Flandreau, and Laeven (2016) for a global historical perspective on the evolution of the LOLR; and Garcia-de-Andoain et al. (2016) for an examination of the impact of liquidity provision by the European Central Bank in its role as LOLR from 2008–2014.

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7.5 Conclusion This chapter has covered the theory and empirical evidence related to bank liquidity creation to shed light on the underlying economics of this central aspect of the financial system. It has discussed two distinct notions of bank liquidity creation developed in the theoretical literature—funding liquidity creation and improved risk sharing for riskaverse depositors. It has also covered regulatory issues and how these are affected by the evolution of banking from an Originate-To-Hold (OTH) model to one that has a mix of OTH and Originate-To-Distribute (OTD). These developments have profound implications for regulatory policy that is designed to ensure that liquidity creation continues without the costly breaches associated with financial crises. An important conclusion is that while higher bank capital seems to increase liquidity creation, liquidity requirements seem to reduce it. As discussed, much work remains to be done. Foremost among these is the question of how capital requirements ought to be designed for both traditional OTH banking activities as well as for the newly emerged shadow-banking system. A second question is whether bank liquidity requirements serve any useful purpose, and if so, what the best way is to design them to minimize their adverse impact on liquidity creation. These two issues should not be addressed in isolation. Finally, Farhi and Tirole (2012) highlight the fact that inefficient bailouts of banks by regulators may occur because regulators cannot distinguish between insolvency and illiquidity even ex post, so research that informs regulators about how to distinguish between insolvency and illiquidity, as a precursor to intervening in what looks like a crisis, would be very useful.

References ABA Banking Journal (2017). “ABA to Fed: Unnecessary to Finalize Basel NSFR,” November 17. Acharya, V.  V. and Thakor, A.  V. (2016). “The Dark Side of Liquidity Creation: Leverageinduced Systemic Risk and Implications for the Lender of Last Resort,” Journal of Financial Intermediation, 28, 4–21. Acharya, V. V., Mehran, H., and Thakor, A. V. (2016). “Caught Between Scylla and Charybdis? Regulating Bank Leverage when there is Rent Seeking and Risk Shifting,” Review of Corporate Finance Studies, 5, 36–75. Admati, A. R. and Hellwig, M. F. (2013). The Bankers’ New Clothes: What’s Wrong with Banking and What to Do About It (Princeton, NJ: Princeton University Press). Admati, A. R., DeMarzo, P. M., Hellwig, M. F., and Pfleiderer, P. (2014). “Fallacies and Irrelevant Facts in the Discussion of Capital Regulation: Why Bank Equity is not Expensive,” in C. Goodhart, D. Gabor, J. Vestergaard, and I. Erturk (eds.), Central Banks at a Crossroads: Europe and Beyond (London: Anthem Press), 33–50. Admati, A. R., DeMarzo, P. M., Hellwig, M. F., and Pfleiderer, P. (2018). “The Leverage Ratchet Effect,” Journal of Finance, 73, 145–98. Adrian, T. and Ashcraft, A.  B. (2012). “Shadow Banking: A Review of the Literature,” in S. N. Durlauf and L. E. Blume (eds.), The New Palgrave Dictionary of Economics (New York: Palgrave Macmillan).

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Creation and Regulation of Bank Liquidity   217 Aghion, P., Bolton, P., and Tirole, J. (2004). “Exit Options in Corporate Finance: Liquidity versus Incentives,” Review of Finance, 8, 327–53. Aiyar, S., Calomiris, C. W., and Wieladek, T. (2012). “Does Macropru Leak? Evidence from a UK Policy Experiment,” Journal of Money, Credit and Banking, 46, 181–214. Allen, F. (1990). “The Market for Information and the Origin of Financial Intermediation,” Journal of Financial Intermediation, 1, 3–30. Allen, F. and Gale, D. (2004). “Financial Intermediaries and Markets,” Econometrica, 72, 1023–61. Allen, F. and Gale, D. (2017). “How Should Bank Liquidity be Regulated?” Working Paper. Allen, F. and Santomero, A. M. (1998). “The Theory of Financial Intermediation,” Journal of Banking and Finance, 21, 1461–85. Allen, L., Peristiani, S., and Saunders, A. (1989). “Bank Size, Collateral, and Net Purchase Behavior in the Federal Funds Market: Empirical Evidence,” Journal of Business, 62, 501–15. Armantier, O., Ghysels, E., Sarkar, A., and Shrader, J. (2015). “Discount Window Stigma During the 2007–2008 Financial Crisis,” Journal of Financial Economics, 118, 317–35. Bai, J., Krishnamurthy, A., and Weymuller, C.-H. (2018). “Measuring Liquidity Mismatch in the Banking Sector,” Journal of Finance, 73, 51–93. Baker, M. and Wurgler, J. (2015). “Do Strict Capital Requirements Raise the Cost of Capital? Bank Regulation, Capital Structure, and the Low-risk Anomaly,” American Economic Review, Papers and Proceedings, 105, 315–20. Barrons (2009). “Where’s the stimulus,” February 2, Column by J. McTague. Barroso, J., Gonzalez, R., and Nazar Van Doornik, B. F. (2017). “Credit Supply Responses to Reserve Requirement: Loan-level Evidence from Macroprudential Policy,” Working Paper. Beck, T., Degryse, H., De Haas, R., and van Horen, N. (2018). “When Arm’s Length is Too Far: Relationship Banking over the Credit Cycle,” Journal of Financial Economics, 127, 174–96. Begenau, J. (2018). “Capital Requirements, Risk Choice, and Liquidity Provision in a Business Cycle Model,” Working Paper. Beltratti, A. and Stulz, R.  M. (2012). “The Credit Crisis Around the Globe: Why did some Banks Perform Better?” Journal of Financial Economics, 105, 1–17. Benink, H. and Benston, G. (2005). “The Future of Banking Regulation in Developed Countries: Lessons from and for Europe,” Financial Markets, Institutions & Instruments, 14, 289–328. Berger, A. N. and Bouwman, C. H. S. (2009). “Bank Liquidity Creation,” Review of Financial Studies, 22, 3779–837. Berger, A. N. and Bouwman, C. H. S. (2013). “How Does Capital Affect Bank Performance During Financial Crises?” Journal of Financial Economics, 109, 146–76. Berger, A. N. and Bouwman, C. H. S. (2016). Bank Liquidity Creation and Financial Crises (Amsterdam: Elsevier). Berger, A. N. and Bouwman, C. H. S. (2017). “Bank Liquidity Creation, Monetary Policy, and Financial Crises,” Journal of Financial Stability, 30, 139–55. Berger, A. N. and Sedunov, J. (2017). “Bank Liquidity Creation and Real Economic Output,” Journal of Banking and Finance, 81, 1–19. Berger, A.  N. and Udell, G.  F. (1992). “Some Evidence on the Empirical Significance of Rationing,” Journal of Political Economy, 100, 1047–77. Berger, A. N. and Udell, G. F. (1994). “Did Risk-Based Capital Allocate Bank Credit and Cause a ‘Credit Crunch’ in the United States?” Journal of Money, Credit, and Banking, 26, 585–628. Berger, A. N. and Udell, G. F. (1995). “Relationship Lending and Lines of Credit in Small Firm Finance,” Journal of Business, 68, 351–81.

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218   The Theory of Banking Berger, A. N., Black, L. K., Bouwman, C. H. S., and Dlugosz, J. (2017). “The Federal Reserve’s Discount Window and TAF Programs: Pushing on a String?” Journal of Financial Intermediation, 32, 1–15. Berger, A. N., Bouwman, C. H. S., Kick, T., and Schaeck, K. (2016). “Bank Liquidity Creation Following Regulatory Interventions and Capital Support,” Journal of Financial Intermediation, 26, 115–41. Berger, A. N., Guedhami, O., Kim, H. H., and Li, X. (2018). “Economic Policy Uncertainty and Bank Liquidity Hoarding,” Working Paper. Berger, A.  N., Herring, R.  J., and Szego, G.  P. (1995). “The Role of Capital in Financial Institutions,” Journal of Banking and Finance, 19, 393–430. Berger, A.  N., Miller, N.  H., Petersen, M.  A., Rajan, R.  G., and Stein, J.  C. (2005). “Does Function Follow Organizational Form? Evidence from the Lending Practices of Large and Small Banks,” Journal of Financial Economics, 76, 237–69. Berkovitch, E. and Greenbaum, S. I. (1991). “The Loan Commitment as an Optimal Financing Contract,” Journal of Financial and Quantitative Analysis, 26, 83–95. Berlin, M. and Mester, L. J. (1999). “Deposits and Relationship Lending,” Review of Financial Studies, 12, 579–607. Bernanke, B. S. (1983). “Nonmonetary Effects of the Financial Crisis in Propagation of the Great Depression,” American Economic Review, 73, 257–76. Bernanke, B. S. (2008). “Liquidity Provision by the Federal Reserve,” Remarks at the Federal Reserve Bank of Atlanta Financial Markets Conference, Sea Island, Georgia, May 18. Bernanke, B. S. (2010). “Causes of the Recent Financial and Economic Crisis,” Statement before the Financial Crisis Inquiry Commission, Washington, DC, delivered on September 2. Berndt, A. and Gupta, A. (2009). “Moral Hazard and Adverse Selection in the Originate-toDistribute Model of Bank Credit,” Journal of Monetary Economics, 56, 725–43. Berrospide, J. M. and Edge, R. M. (2010). “The Effects of Bank Capital on Lending: What Do We Know, and What Does It Mean?” International Journal of Central Banking, 6, 5–54. Besanko, D. and Kanatas, G. (1996). “The Regulation of Bank Capital: Do Capital Standards Promote Bank Safety?” Journal of Financial Intermediation, 5, 160–83. Bharath, S., Dahiya, S., Saunders, A., and Srinivasan, A. (2007). “So What Do I Get? The Bank’s View of Lending Relationships,” Journal of Financial Economics, 85, 368–419. Bhattacharya, S. and Thakor, A.  V. (1993). “Contemporary Banking Theory,” Journal of Financial Intermediation, 3, 2–50. Billett, M. T., Flannery, M. J., and Garfinkel, J. A. (1995). “The Effect of Lender Identity on a Borrowing Firm’s Equity Return,” Journal of Finance, 50, 699–718. Billett, M. T., Flannery, M. J., and Garfinkel, J. A. (2006). “Are Bank Loans Special? Evidence on the Post-Announcement Performance of Bank Borrowers,” Journal of Financial and Quantitative Analysis, 41, 733–51. BIS (Bank for International Settlements) (2010). “Basel III: International Framework for Liquidity Risk Measurement, Standards and Monitoring,” December. BIS (2013). “Basel III: The Liquidity Coverage Ratio and Liquidity Risk Monitoring Tools,” January. BIS (2014). “Basel III: The Net Stable Funding Ratio,” October. BIS (2017). “Implementation: Range of Practices in Implementing the Countercyclical Capital Buffer Policy,” June. BIS (2018). “Global Systemically Important Banks: Revised Assessment Methodology and the Higher Loss Absorbency Requirement,” July.

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Creation and Regulation of Bank Liquidity   219 Black, L. K. and Hazelwood, L. N. (2013). “The Effect of TARP on Bank Risk-taking,” Journal of Financial Stability, 9, 790–803. Blackwell, N. R. and Santomero, A. M. (1982). “Bank Credit Rationing and Customer Relation,” Journal of Monetary Economics, 9, 121–9. Bloomberg (2013). “Must Financial Reform Await Another Crisis?” by A.  Admati and M. Hellwig, February 6. Bolton, P., Freixas, X., Gambacorta, L., and Mistrulli, P.  E. (2016). “Relationship and Transaction Lending in a Crisis,” Review of Financial Studies, 29, 2643–76. Boot, A.  W.  A. (2000). “Relationship Banking: What Do We Know?” Journal of Financial Intermediation, 9, 7–25. Boot, A. W. A. and Thakor, A. V. (1993). “Security Design,” Journal of Finance, 48, 1349–78. Boot, A. W. A. and Thakor, A. V. (1994). “Moral Hazard and Secured Lending in an Infinitely Repeated Credit Market Game,” International Economic Review, 35, 899–920. Boot, A. W. A. and Thakor, A. V. (2000). “Can Relationship Banking Survive Competition?” Journal of Finance, 55, 679–714. Boot, A.  W.  A., Greenbaum, S.  I., and Thakor, A.  V. (1993). “Reputation and Discretion in Financial Contracting,” American Economic Review, 83, 1165–83. Boot, A.  W.  A., Thakor, A.  V., and Udell, G.  F. (1991). “Credible Commitments, Contract Enforcement Problems and Banks: Intermediation as Credibility Assurance,” Journal of Banking and Finance, 15, 605–32. Bord, V. M. and Santos, J. A. C. (2012). “The Rise of the Originate-to-Distribute Model and the Role of Banks in Financial Intermediation,” FRBNY Economic Policy Review, July, 21–34. Bouwman, C.  H.  S., Kim, H., and Shin, S.-O. (2018). “Bank Capital and Bank Stock Performance,” Working Paper. Boyson, N., Helwege, J., and Jindra  J. (2014). “Crises, Liquidity Shocks, and Fire Sales at Commercial Banks,” Financial Management, 43, 857–84. Brunnermeier, M. K. and Oehmke, M. (2013). “The Maturity Rat Race,” Journal of Finance, 68, 483–521. Bryant, J. (1980). “A Model of Reserves, Bank Runs, and Deposit Insurance,” Journal of Banking and Finance, 4, 335–44. Calomiris, C. W. and Gorton, G. B. (1991). “The Origins of Banking Panics: Models, Facts, and Bank Regulation,” in R. G. Hubbard (ed.), Financial Markets and Financial Crises (Chicago, IL: University of Chicago Press), 109–74. Calomiris, C. W. and Herring, R. J. (2012). “Why and How to Design a Contingent Convertible Debt Requirement,” in R. J. Herring and R. E. Litan (eds.), Rocky Times: New Perspectives on Financial Stability (Washington, DC: Brookings/NICMR Press). Calomiris, C.  W. and Kahn, C.  M. (1991). “The Role of Demandable Debt in Structuring Optimal Banking Arrangements,” American Economic Review, 81, 497–513. Calomiris, C.  W. and Mason, J.  R. (2008). “Resolving the Puzzle of the Underissuance of National Bank Notes,” Explorations in Economic History, 45, 327–55. Calomiris, C. W. and Pornrojnangkool, T. (2009). “Relationship Banking and the Pricing of Financial Services,” Journal of Financial Services Research, 35, 189–224. Calomiris, C. W. and Wilson, B. (2004). “Bank Capital and Portfolio Management: The 1930s ‘Capital Crunch’ and the Scramble to Shed Risk,” Journal of Business, 77, 421–55. Calomiris, C.  W., Flandreau, M., and Laeven, L. (2016). “Political Foundations of the Lender of Last Resort: A Global Historical Narrative,” Journal of Financial Intermediation, 28, 48–65.

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220   The Theory of Banking Calomiris, C.  W., Heider, F., and Hoerova, M. (2015). “A Theory of Bank Liquidity Requirements,” Working Paper. Calomiris, C. W., Himmelberg, C. P., and Wachtel, P. (1995). “Commercial Paper and Corporate Finance: A Microeconomic Perspective,” Carnegie-Rochester Conference Series on Public Policy, 45, 203–50. Campbell, T. S. (1978). “A Model of the Market for Lines of Credit,” Journal of Finance, 33, 231–44. Campbell, T. S., Chan, Y.-S., and Marino, A. M. (1992). “An Incentive-Based Theory of Bank Regulation,” Journal of Financial Intermediation, 2, 255–76. Campello, M., Giambona, E., Graham, J. R., and Harvey, C. R. (2011). “Liquidity Management and Corporate Investment During a Financial Crisis,” Review of Financial Studies, 24, 1944–79. Carletti, E., Goldstein, I., and Leonello, A. (2018). “The Interdependence of Bank Capital and Liquidity,” Working Paper. Carlson, M. A., Shan, H., and Warusawitharana, M. (2013). “Capital Ratios and Bank Lending: A Matched Bank Approach,” Journal of Financial Intermediation, 22, 663–87. Champ, B. (2010). “The National Banking System: A Brief History,” Federal Reserve Bank of Cleveland, Working Paper No. WP-23R. Chan, Y.-S., Greenbaum, S. I., and Thakor, A. V. (1992). “Is Fairly Priced Deposit Insurance Possible?” Journal of Finance, 47, 227–45. Chari, V.  V. and Jagannathan, R. (1988). “Banking Panics, Information, and Rational Expectations Equilibrium,” Journal of Finance, 43, 749–61. Chu, Y., Zhang, D., and Zhao, Y. (2017). “Bank Capital and Lending: Evidence from Syndicated Loans,” Working Paper. Claessens, S., Pozsar, Z., Ratnovski, L., and Singh, M. (2012). “Shadow Banking: Economics and Policy,” IMF Staff Discussion Note SDN/12/12. Copeland, A., Martin, A., and Walker, M. (2014). “Repo Runs: Evidence from the Tri-party Repo Market,” Journal of Finance, 69, 2343–80. Cornett, M.  M., McNutt, J.  J., Strahan, P.  E., and Tehranian, H. (2011). “Liquidity Risk Management and Credit Supply in the Financial Crisis,” Journal of Financial Economics, 101, 297–312. Covas, F. and Nelson, B. (2016). “The Net Stable Funding Ratio: Neither Necessary nor Harmless,” The ClearingHouse, July. Covitz, D.  M., Liang, N., and Suarez, G.  A. (2013). “The Evolution of a Financial Crisis: Collapse of the Asset-backed Commercial Paper Market,” Journal of Finance, 68, 815–48. Dai, Z., Zhang, H., and Zhao, F. (2013). “Tug-of-War: Incentive Alignment in Securitization and Loan Performance,” Working Paper. Dasgupta, S. (2009). “Comment on L.  Zingales: ‘Why Not Consider Maximum Reserve Ratios?” The Economist’s Voice, 6(4), art. 6. Degryse, H., Kim, M., and Ongena, S. (2009). Microeconometrics of Banking: Methods, Applications, and Results (Oxford: Oxford University Press). Dell’Ariccia, G. and R. Marquez, R. (2006). “Lending Booms and Lending Standards,” Journal of Finance, 61, 2511–46. Dell’Ariccia, G., Detragiache, E., and Rajan, R. G. (2008). “The Real Effects of Banking Crises,” Journal of Financial Intermediation, 17, 89–112. Dell’Ariccia, G., Igan, D., and Laeven, L. (2012). “Credit Booms and Lending Standards: Evidence from the Subprime Mortgage Market,” Journal of Money, Credit, and Banking, 44, 367–84.

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Creation and Regulation of Bank Liquidity   221 Demirgüç-Kunt, A. and Huizinga, H. (1999). “Determinants of Commercial Bank Interest Margins and Profitability: Some International Evidence,” World Bank Economic Review, 13, 379–408. Demiroglu, C. and James, C.  M. (2012). “How Important is having Skin in the Game? Originator–Sponsor Affiliation and Losses on Mortgage-backed Securities,” Review of Financial Studies, 25, 3217–58. Demyanyk, Y. and Van Hemert, O. (2011). “Understanding the Subprime Mortgage Crisis,” Review of Financial Studies, 24, 1848–80. Dewatripont, M. and Tirole, J. (1994). “A Theory of Debt and Equity: Diversity of Securities and Manager–Shareholder Congruence,” Quarterly Journal of Economics, 109, 1027–54. Dewatripont, M. and Tirole, J. (2018). “Liquidity Regulation, Bail-ins and Bailouts,” Working Paper. Diamond, D.  W. (1984). “Financial Intermediation and Delegated Monitoring,” Review of Economic Studies, 51, 393–414. Diamond, D.  W. and Dybvig, P.  H. (1983). “Bank Runs, Deposit Insurance and Liquidity,” Journal of Political Economy, 91, 401–19. Diamond, D. W. and Kashyap, A. K. (2016). “Liquidity Requirements, Liquidity Choice and Financial Stability,” in J. B. Taylor and H. Uhlig (eds.), Handbook of Macroeconomics, Vol. 2B (Amsterdam: Elsevier). Diamond, D. W. and Rajan, R. G. (2001). “Liquidity Risk, Liquidity Creation, and Financial Fragility: A Theory of Banking,” Journal of Political Economy, 109, 287–327. Distinguin, I., Roulet, C., and Tarazi, A. (2013). “Bank Regulatory Capital and Liquidity: Evidence from US and European Publicly Traded Banks,” Journal of Banking and Finance, 37, 3295–317. Donaldson, J., Piacentino, G., and Thakor, A.  V. (2018). “Warehouse Banking,” Journal of Financial Economics, 129, 250–67. Drechsler, I., Drechsel, T., Marques-Ibanez, D., and Schnabl, P. (2016). “Who Borrows from the Lender of Last Resort? Evidence from the European Financial Crisis,” Journal of Finance, 71, 1933–74. Drucker, S. and Puri, M. (2005). “On the Benefits of Concurrent Lending and Underwriting,” Journal of Finance, 60, 2763–99. Drucker, S. and Puri, M. (2009). “On Loan Sales, Loan Contracting, and Lending Relationships,” Review of Financial Studies, 22, 2835–72. Duchin, R. and Sosyura, D. (2014). “Safer Ratios, Riskier Portfolios: Banks’ Response to Government Aid,” Journal of Financial Economics, 113, 1–28. Edlin, A.  S. and Jaffee, D.  M. (2009). “Show me the Money,” The Economists’ Voice, 6(4), art. 9. Ennis, H. M. and Weinberg, J. A. (2013). “Over-the-Counter Loans, Adverse Selection, and Stigma in the Interbank Market,” Review of Economic Dynamics, 16, 601–16. European Parliament (2011). “US Implementation of Basel II: Final Rules Issued, but no Supervisory Approvals to Date,” Briefing Note requested by the European Parliament’s Committee on Economic and Monetary Affairs. Farhi, E. and Tirole, J. (2012). “Collective Moral Hazard, Maturity Mismatch, and Systemic Bailouts,” American Economic Review, 102, 60–93. FDIC (Federal Deposit Insurance Corporation) (2003). “Basel and the Evolution of Capital Regulation: Moving Forward, Looking Back,” A Study by S. Burhouse, J. Feid, G. French, and K. Ligon.

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

222   The Theory of Banking Federal Reserve (1933). “Member Bank Reserves—Report of the Committee on Bank Reserves of the Federal Reserve System,” 19th Annual Report of the Board of Governors of the Federal Reserve System, Washington, DC, 260–85. Federal Reserve (2007). “Risk-based Capital Standards: Advanced Capital Adequacy Framework – Basel II,” 72 Federal Register 235, December 7. Federal Reserve (2014). “Liquidity Coverage Ratio: Liquidity Risk Measurement Standards,” Final Rule, 79 Federal Register 61440, October 10. Federal Reserve (2016). “Regulatory Capital Rules: Implementation of Capital Requirements for Global Systemically Important Bank Holding Companies,” Final Rule, 12 CFR Part 217 Regulation Q, Docket No. R01535, December 9. Federal Reserve (2018a). “Amendments to the Regulatory Capital, Capital Plan, and Stress Test Rules,” Notice of Proposed Rulemaking, 83 Federal Register 18160, April 25. Federal Reserve (2018b). “Regulatory Capital Rules: Regulatory Capital, Enhanced Supplementary Leverage Ratio Standards for US Global Systemically Important Bank Holding Companies and Certain of their Subsidiary Insured Depository Institutions; Total Loss-Absorbing Capacity Requirements for US Global Systemically Important Bank Holding Companies,” Proposed Rule, 83 Federal Register 171317, April 19. Federal Reserve (2018c). “Liquidity Coverage Ratio Rule: Treatment of Certain Municipal Obligations as High-quality Liquid Assets,” Interim Final Rule, 83 Federal Register 44451, August 31. Feinman, J.  N. (1993). “Reserve Requirements: History, Current Practice, and Potential Reform,” Federal Reserve Bulletin, (June), 569–89. Financial Times (2012). “Get Basel III Right and Avoid Basel IV,” by T. Hoenig, December 12. Financial Times (2018). “Federal Reserve Debates Banks’ Capital Buffers as Markets Surge,” by Sam Fleming, August 29. Francis, W. A. and Osborne, M. (2012). “Capital Requirements and Bank Behavior in the UK: Are there Lessons for International Capital Standards?” Journal of Banking and Finance, 36, 803–16. Freixas, X. and Rochet, J.-C. (2008). Microeconomics of Banking, 2nd edn (Boston, MA: MIT Press). FSB (Financial Stability Board) (2011). “Shadow Banking: Strengthening Oversight and Regulation,” Recommendations of the Financial Stability Board. FSB (2012a). “Securities Lending and Repos: Market Overview and Financial Stability Issues,” Interim Report of the FSB Workstream on Securities Lending and Repos, April 27. FSB (2012b). “Strengthening Oversight and Regulation of Shadow Banking: An Integrated Overview of Policy Recommendations,” November 18. FSB (2017). “2017 List of Global Systemically Important Banks (G-SIBs),” November 21. Fungáčová, Z., Weill, L., and Zhou, M. (2017). “Bank Capital, Liquidity Creation and Deposit Insurance,” Journal of Financial Services Research, 51, 97–123. Furfine, C. (2001). “The Reluctance to Borrow from the Fed,” Economics Letters, 72, 209–213. Gande, A. and Saunders, A. (2012). “Are Banks still Special when there is a Secondary Market for Loans?” Journal of Finance, 67, 1649–84. Garcia-de-Andoain, C., Heider, F., Hoerova, M., and Manganelli, S. (2016). “Lending-of-LastResort Is as Lending-of-Last-Resort Does: Central Bank Liquidity Provision and Interbank Market Functioning in the Euro Area,” Journal of Financial Intermediation, 28, 32–47. Gatev, E., Schuermann, T., and Strahan, P. E. (2006). “How do Banks Manage Liquidity Risk? Evidence from the Equity and Deposit Markets in the Fall of 1998,” in M. Carey and R. Stulz (eds.), Risks of Financial Institutions (Chicago, IL: University of Chicago Press), 105–27.

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Creation and Regulation of Bank Liquidity   223 Gatev, E., Schuermann, T., and Strahan, P. E. (2009). “Managing Bank Liquidity Risk: How Deposit–Loan Synergies Vary with Market Conditions,” Review of Financial Studies, 22, 995–1020. Gennaioli, N., Shleifer, A., and Vishny, R. W. (2013). “A Model of Shadow Banking,” Journal of Finance, 68, 1331–63. Genotte, G. and Pyle, D. H. (1991). “Capital Controls and Bank Risk,” Journal of Banking and Finance, 15, 805–24. Goel, A. and Thakor, A. V. (2015). “Information Reliability and Welfare: A Theory of Coarse Credit Ratings,” Journal of Financial Economics, 115, 541–57. Gorton, G. (1988). “Banking Panics and the Business Cycle,” Oxford Economic Papers, 40, 751–81. Gorton, G. B. and Haubrich, J. G. (1990). “The Loan Sales Market,” in G. Kaufman (ed.), Research in Financial Services: Private and Public Policy, Vol. II (Greenwich, CT: Jai Press), 85–135. Gorton, G. B. and Metrick, A. (2010). “Regulating the Shadow Banking System,” Brookings Papers on Economic Activity, 41, 261–312. Gorton, G. B. and Metrick, A. (2012). “Securitized Banking and the Run on Repo,” Journal of Financial Economics, 104, 425–51. Gorton, G. B. and Pennacchi, G. G. (1990). “Financial Intermediaries and Liquidity Creation,” Journal of Finance, 45, 49–71. Gorton, G. B. and Pennacchi, G. G. (1995). “Banks and Loan Sales: Marketing Non-marketable Assets,” Journal of Monetary Economics, 3, 389–411. Greenbaum, S.  I. and Thakor, A.  V. (1987). “Bank Funding Modes: Securitization versus Deposits,” Journal of Banking and Finance, 11, 379–401. Greenbaum, S. I., Kanatas, G., and Venezia, I. (1989). “Equilibrium Loan Pricing under the Bank–Client Relationship,” Journal of Banking and Finance, 13, 221–35. Greenbaum, S.  I., Thakor, A.  V., and Boot, A.  W.  A. (2015). Contemporary Financial Intermediation, 3rd edn (Amsterdam: North-Holland/Elsevier/Academic Press). Gupta, A., Singh, A. K., and Zebedee, A. A. (2008). “Liquidity in the Pricing of Syndicated Loans,” Journal of Financial Markets, 11, 339–76. Haldane, A. G. and Madouros, V. (2012). “The Dog and the Frisbee,” Speech at the Jackson Hole Economic Policy Symposium, August 31. Hancock, D., Laing, A. J., and Wilcox, J. A. (1995). “Bank Balance Sheet Shocks and Aggregate Shocks: Their Dynamic Effects on Bank Capital and Lending,” Journal of Banking and Finance, 19, 661–77. Hanson, S.  G., Kashyap, A.  K., and Stein, J.  C. (2011). “A Macroprudential Approach to Financial Regulation,” Journal of Economic Perspectives, 25, 3–28. Hart, O. and Zingales, L. (2011). “A New Capital Regulation for Large Financial Institutions,” American Law and Economics Review, 13, 453–90. Hellmann, T. F., Murdock, K. C., and Stiglitz, J. E. (2000). “Liberalization, Moral Hazard in Banking, and Prudential Regulation: Are Capital Requirements Enough?” American Economic Review, 90, 147–65. Hellwig, M. (1994). “Liquidity Provision, Banking, and the Allocation of Interest Rate Risk,” European Economic Review, 39, 1363–89. Ho, T. S. Y. and Saunders, A. (1983). “Fixed Rate Loan Commitments, Take-Down Risk, and the Dynamics of Hedging with Futures,” Journal of Financial and Quantitative Analysis, 18, 499–516. Holmstrom, B. and Tirole, J. (1998). “Public and Private Supply of Liquidity,” Journal of Political Economy, 106, 1–40.

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224   The Theory of Banking Horvath, R., Seidler, J., and Weill, L. (2014). “Bank Capital and Liquidity Creation: ­Granger-Causality Evidence,” Journal of Financial Services Research, 45, 341–61. Huffington Post (2010). “Malpractice at the Bernanke Federal Reserve,” September 13, Column by R. Auerbach. Ivashina, V. and Scharfstein, D. (2010). “Bank Lending During the Financial Crisis of 2008,” Journal of Financial Economics, 97, 319–38. Jacklin, C. J. (1987). “Demand Deposits, Trading Restrictions, and Risk Sharing,” in E. C. Prescott and N. Wallace (eds.), Contractual Arrangements for Intertemporal Trade, Minnesota Studies in Macroeconomics Vol. I (Minneapolis, MN: University of Minnesota Press). Jacklin, C. J. (1993). “Market Rate versus Fixed Rate Demand Deposits,” Journal of Monetary Economics, 32, 237–58. James, C.  M. (1981). “Self-Selection and the Pricing of Bank Services: An Analysis of the Market for Bank Loan Commitments and the Role of the Compensating Balance Requirements,” Journal of Financial and Quantitative Analysis, 16, 725–46. James, C. M. (1987). “Some Evidence on the Uniqueness of Bank Loans,” Journal of Financial Economics, 19, 217–36. James, C. M. (1988). “The Use of Loan Sales and Standby Letters of Credit by Commercial Banks,” Journal of Monetary Economics, 22, 395–422. Jiang, L., Levine, R., and Lin, C. (2019). “Competition and Bank Liquidity Creation,” Journal of Financial and Quantitative Analysis, 54, 513–38. Jiménez, G., Ongena, S., Peydró, J.-L., and Saurina, J. (2017). “Macroprudential Policy, Countercyclical Bank Capital Buffers and Credit Supply: Evidence from the Spanish Dynamic Provisioning Experiments,” Journal of Political Economy, 125, 2126–77. Kane, E., Laeven, L., and Demirgüç-Kunt, A. (2008). “Determinants of Deposit Insurance Adoption and Design,” Journal of Financial Intermediation, 17, 407–38. Kashyap, A. K., Rajan, R. G., and Stein, J. C. (2002). “Banks as Liquidity Providers: An Explanation for the Coexistence of Lending and Deposit-taking,” Journal of Finance, 57, 33–73. Kashyap, A. K., Rajan, R. G., and Stein, J. C. (2008). “Rethinking Capital Regulation,” Federal Reserve Bank of Kansas City Symposium on Maintaining Stability in a Changing Financial System, Federal Reserve Bank of Kansas City, Kansas City, 431–71. Keister, T. and McAndrews, J. J. (2009). “Why are Banks Holding so many Excess Reserves?” Current Issues in Economics and Finance—Federal Reserve Bank of New York, 15, 1–10. Keys, B., Seru, A., and Vig, V. (2012). “Lender Screening and Role of Securitization: Evidence from Prime and Subprime Mortgage Markets,” Review of Financial Studies, 25, 2071–108. Kim, D. and Santomero, A.  M. (1988). “Risk in Bank and Capital Regulation,” Journal of Finance, 43, 1219–33. Klein, P.-O. and Turk-Ariss, R. (2018). “Is the Cost of a Safer Banking System Lower Economic Activity?” Working Paper. Klimenko, N., Pfeil, S., Rochet, J.-C., and De Nicolo, G. (2016). “Aggregate Bank Capital and Credit Dynamics,” Working Paper. Koehn, M. and Santomero, A.  M. (1980). “Regulation of Bank Capital and Portfolio Risk,” Journal of Finance, 35, 1235–44. Krishnamurthy, A., Nagel, S., and Orlov, D. (2014). “Sizing Up Repo,” Journal of Finance, 69, 2381–417. Leland, H. E. and Pyle, D. H. (1977). “Informational Asymmetries, Financial Structure and Financial Intermediation,” Journal of Finance, 32, 371–87. Li, L. (2013). “TARP Funds Distribution and Bank Loan Supply,” Journal of Banking and Finance, 37, 4777–92.

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Creation and Regulation of Bank Liquidity   225 Loutskina, E. (2011). “The Role of Securitization in Bank Liquidity and Funding Management,” Review of Financial Studies, 100, 663–84. Mailath, G.  J. and Mester, L.  J. (1994). “A Positive Analysis of Bank Closure,” Journal of Financial Intermediation, 3, 282–99. Martin, A., Skeie, D., and von Thadden, E.-L. (2014a). “Repo Runs,” Review of Financial Studies, 27, 957–89. Martin, A., Skeie, D., and von Thadden, E.-L. (2014b). “The Fragility of Short-Term Secured Funding Markets,” Journal of Economic Theory, 149, 15–42. McCulley, P. (2007). “Teton Reflections,” PIMCO Global Central Bank Focus. Mehran, H. and Thakor, A. V. (2011). “Bank Capital and Value in the Cross-Section,” Review of Financial Studies, 24, 1019–67. Melnik, A. and Plaut, S. (1986). “Loan Commitment Contracts, Terms of Lending, and Credit Allocation,” Journal of Finance, 41, 425–35. Merton, R.  C. (1977). “On the Pricing of Contingent Claims and the Modigliani–Miller Theorem,” Journal of Financial Economics, 5, 241–9. Merton, R. C. and Bodie, Z. (1992). “On the Management of Financial Guarantees,” Financial Management, 21, 87–109. Merton, R. C. and Thakor, R. T. (forthcoming). “Customers and Investors: A Framework for Understanding the Evolution of Financial Institutions,” Journal of Financial Intermediation. Mester, L.  J., Nakamura, L.  I., and Renault, M. (2007). “Transactions Accounts and Loan Monitoring,” Review of Financial Studies, 20, 529–56. Mian, A. and Sufi, A. (2009). “The Consequences of Mortgage Credit Expansion: Evidence from the US Mortgage Default Crisis,” Quarterly Journal of Economics, 124, 1449–96. Millon, M. H. and Thakor, A. V. (1985). “Moral Hazard and Information Sharing: A Model of Financial Information Gathering Agencies,” Journal of Finance, 40, 1403–22. Mnuchin, S.  T. and Phillips, C.  S. (2017). “A Financial System that Creates Economic Opportunities: Banks and Credit Unions,” US Department of Treasury Report to President Donald  J.  Trump, Executive Order 13772 on Core Principles for Regulating the United States Financial System, June. Morgan, D. P. (1994). “Bank Credit Commitments, Credit Rationing, and Monetary Policy,” Journal of Money, Credit and Banking, 26, 87–101. O’Hara, M. and Shaw, W. (1990). “Deposit Insurance and Wealth Effects: The Benefit of Being Too Big To Fail,” Journal of Finance, 45, 1587–600. Parlour, C. A. and Winton, A. (2013). “Laying Off Credit Risk: Loan Sales versus Credit Default Swaps,” Journal of Financial Economics, 107, 25–45. Passmore, W. and Von Haften, A.  H. (2017). “Are Basel’s Capital Surcharges for Global Systemically Important Banks Too Small?” Finance and Economics Discussion Series 2017–12. Washington, DC: Board of Governors of the Federal Reserve System. Peek, J. and Rosengren, E. S. (1995). “The Capital Crunch: Neither a Borrower Nor a Lender Be,” Journal of Money, Credit and Banking, 27, 625–38. Pennacchi, G. G. (1988). “Loan Sales and the Cost of Bank Capital,” Journal of Finance, 43, 375–96. Perignon, C., Thesmar, D., and Vuillemey, G. (2018). “Wholesale Funding Dry-ups,” Journal of Finance, 73, 575–617. Petersen, M.  A. and Rajan, R.  G. (1994). “The Benefits of Lending Relationships: Evidence from Small Business Data,” Journal of Finance, 49, 3–37. Prilmeier, R. (2017). “Why do Loans Contain Covenants? Evidence from Lending Relationships,” Journal of Financial Economics, 123, 558–79.

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226   The Theory of Banking Purnanandam, A. (2011). “Originate-to-Distribute Model and the Subprime Mortgage Crisis,” Review of Financial Studies, 24, 1881–915. Rajan, R. G. (1992). “Insiders and Outsiders: The Choice Between Informed and Arm’s-length Debt,” Journal of Finance, 47, 1367–400. Ramakrishnan, R.  T.  S. and Thakor, A.  V. (1984). “Information Reliability and a Theory of Financial Intermediation,” Review of Economic Studies, 51, 415–32. Repullo, R. (2004). “Capital Requirements, Market Power, and Risk-Taking in Banking,” Journal of Financial Intermediation, 13, 156–82. Saunders, A. and Schumacher, L. (2000). “The Determinants of Bank Interest Rate Margins: An International Study,” Journal of International Money and Finance, 19, 813–32. Sharpe, S.  A. (1990). “Asymmetric Information, Bank Lending and Implicit Contracts: A Stylized Model of Customer Relationships,” Journal of Finance, 45, 1069–87. Shockley, R. and Thakor, A. V. (1997). “Bank Loan Commitments: Data, Theory, and Tests,” Journal of Money, Credit and Banking, 29, 517–34. Song, F. and Thakor, A. V. (2007). “Relationship Banking, Fragility and the Asset–Liability Matching Problem,” Review of Financial Studies, 20, 2129–77. Stiglitz, J. E. (2007). “Houses of Cards,” The Guardian, October 9. Sufi, A. (2007). “Information Asymmetry and Financing Arrangements: Evidence from Syndicated Loans,” Journal of Finance, 62, 629–68. Sufi, A. (2009). “Bank Lines of Credit in Corporate Finance: An Empirical Analysis,” Review of Financial Studies, 22, 1057–88. Sumner, S. (2009). “Comment on Brad Delong: Can We Generate Controlled Reflation in a Liquidity Trap?” The Economists’ Voice, 6(4), art. 7. Systemic Risk Council (2012). “Comment Letter Regarding: Regulatory Capital Rules,” October 4. Thakor, A. V. (1982). “Toward a Theory of Bank Loan Commitments,” Journal of Banking and Finance, 6, 55–83. Thakor, A. V. (1996). “Capital Requirements, Monetary Policy and Aggregate Bank Lending: Theory and Empirical Evidence,” Journal of Finance, 51, 279–324. Thakor, A. V. (2005). “Do Loan Commitments Cause Overlending?” Journal of Money, Credit and Banking, 37, 1067–100. Thakor, A.  V. (2014). “Bank Capital and Financial Stability: An Economic Trade-off or a Faustian Bargain?” Annual Review of Financial Economics, 6, 185–223. Thakor, A. V. (2015). “The Financial Crisis of 2007–09: Why Did It Happen and What Did We Learn?” Review of Corporate Finance Studies, 4, 115–205. Thakor, A. V. (2018). “Post-crisis Regulatory Reform in Banking: Address Insolvency Risk, not Illiquidity!” Journal of Financial Stability, 37, 107–11. Thakor, A. V., Hong, H., and Greenbaum, S. I. (1981). “Bank Loan Commitments and Interest Rate Volatility,” Journal of Banking and Finance, 5, 497–510. Van den Heuvel, S. J. (2018). “The Welfare Effects of Bank Liquidity and Capital Requirements,” Working Paper. Von Thadden, E.-L. (2004). “Bank Capital Adequacy Regulation Under the New Basel Accord,” Journal of Financial Intermediation, 13, 90–95. Wall Street Journal (2018). “A Vote to Upend Banking As We Know It,” by Brian Blackstone, June 1.

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PA RT I I

AC T I V I T I E S A N D PE R FOR M A NC E

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chapter 8

Th e Per for m a nce of Fi na nci a l I nstit u tions Modeling, Evidence, and some Policy Implications Joseph P. Hughes and Loretta J. Mester

8.1 Introduction The commercial banking industry is undergoing disruption from other types of financial intermediaries. To understand the future evolution of the industry in the wake of such disruption, it is important to take a step back and ask: What do commercial banks do? What are the key components of commercial banking technology that allow them to do it? And what determines whether banks do it efficiently? Banks’ ability to ameliorate informational asymmetries between borrowers and lenders and to manage risks is the essence of bank production. The literature on financial intermediation suggests that commercial banks, by screening and monitoring borrowers, can help solve potential moral hazard and adverse selection problems caused by the imperfect information between borrowers and lenders. Commercial banks are unique in issuing demandable debt that participates in the economy’s payments system. This debt confers an informational advantage to banks over other lenders in making loans to informationally opaque borrowers. In particular, the information obtained from checking account transactions and other sources allows banks to assess and manage risk, write contracts, monitor contractual performance, and, when required, resolve non-performance problems. Bhattacharya and Thakor (1993) review the modern theory of financial intermediation, which takes an informational approach to banking.

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230   Activities and Performance That commercial banks’ liabilities are demandable debt also gives banks an incentive advantage over other intermediaries. The relatively high level of debt in a bank’s capital structure disciplines managers’ risk-taking and their diligence in producing financial services by exposing the bank to an increased risk of insolvency. The demandable feature of the debt, to the extent that it is not fully insured, further heightens performance pressure and safety concerns by increasing liquidity risk. These incentives tend to make banks good monitors of their borrowers. Thus, banks’ unique funding by demandable debt that participates in the economy’s payments system gives banks both an incentive advantage and an informational advantage in lending to firms too informationally opaque to borrow in public debt and equity markets. The uniqueness of commercial bank production, in contrast to the production of other types of lenders, is derived from the special characteristics of banks’ capital structure: the funding of informationally opaque assets with demand deposits.1 Calomiris and Kahn (1991) and Flannery (1994) discuss the optimal capital structure of commercial banks. But banks’ ability to perform efficiently—to adopt appropriate investment strategies, to obtain accurate information concerning their customers’ financial prospects, and to write and enforce effective contracts—depends in part on the property rights and legal, regulatory, and contracting environments in which they operate. Such an environment includes accounting practices, chartering rules, government regulations, and the market conditions (e.g., market power) under which banks operate. Differences in these features across political jurisdictions can lead to differences in the efficiency of banks across jurisdictions.2 Banks’ unique funding by demand deposits motivates key components of the legal and regulatory environments that influence managerial incentives for risk-taking and efficiency. Banks’ participation in the payments system leads to their regulation and, in particular, to restrictions on entry into the industry. The need to obtain a charter to open a bank confers a degree of market power on banks operating in smaller markets and, in general, permits banks to exploit valuable investment opportunities related to financial intermediation and payments. Government regulation and supervision of banks promotes their safety and soundness in order to protect the payments system from bank runs that reduce bank lending and threaten macroeconomic stability. Protecting the payments system frequently involves deposit insurance. To the extent that the insurance 1  Berlin and Mester (1999) find empirical evidence of an explicit link between banks’ liability structure and their distinctive lending behavior. As discussed in Mester (2007), relationship lending is associated with lower loan rates, less stringent collateral requirements, a lower likelihood of credit rationing, contractual flexibility, and reduced costs of financial distress for borrowing firms. Banks’ access to core deposits, which are rate inelastic, enables banks to insulate borrowers with whom they have durable relationships from exogenous credit shocks. Mester, Nakamura, and Renault (2007) also find empirical evidence of a synergy between the liability and asset sides of a commercial bank’s balance sheet, showing that information on the cash flows into and out of a borrower’s transactions account can help an intermediary monitor the changing value of collateral that a small-business borrower has posted. 2  Demirgüç-Kunt, Kane, and Laeven (2007) use a sample of 180 countries to study the external and internal political features that influence the adoption and design of deposit insurance, which, in turn, affects the efficiency of the domestic banking system.

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The Performance of Financial Institutions   231 is credible, it reduces depositors’ incentive to run banks when they have fears about banks’ solvency. Consequently, it reduces banks’ liquidity risk and, to the extent it is underpriced, gives banks the incentive to take additional risk for higher expected return. Moreover, if uninsured creditors also believe they will be protected from losses because government regulators will treat the bank as too big to fail, the risk-taking incentive is heightened further.

8.2  Banking Technology and Performance 8.2.1  Banks’ Risk Menu and Conflicting Incentives for Risk-Taking Mispriced deposit insurance and too-big-to-fail policies can create a cost-of-funds subsidy that gives banks an incentive to take additional risk.3 But banks also have an incentive to avoid risk to protect their valuable charters from episodes of financial distress. Distress involves liquidity crises resulting from runs by uninsured depositors, regulatory intervention in banks’ investment decisions, and even the loss of the charter when distress results in insolvency. As discussed in Hughes and Mester (2013b), Marcus (1984) finds that banks with high-valued investment opportunities maximize their expected market value by pursuing lower-risk investment strategies that protect their charters and thereby preserve their ability to exploit these opportunities. On the other hand, banks with lowvalued investment opportunities maximize their expected value by adopting higher-risk investment strategies that exploit the cost-of-funds subsidy of mispriced deposit insurance (Keeley, 1990). Mid-range risk strategies do not maximize value. These dichotomous investment strategies, as well as other sources of risk-taking and risk-avoidance, fundamentally shape production decisions and must be taken into account when modeling bank production. Herring and Vankudre (1987) offer a similar analysis of these dichotomous investment strategies. Hughes, Mester, and Moon (2016) provide evidence of these dichotomous value-maximizing strategies in banks’ capitalization, and Hughes and Moon (2018) find similar evidence in credit risk strategies. The risk environment banks face can be characterized by a frontier of expected return and return risk, which shows a bank’s menu of efficient investment choices.4 3  FDIC (2014) summarizes some of the estimates of the subsidy found in the literature. 4  For expository purposes, in this discussion we are assuming that only the first two moments of the distribution of returns matter for bank production. More generally, however, higher moments, such as skewness and kurtosis, can be expected to influence, for example, calculations of value-at-risk and the choice of investment strategies that minimize the probability of financial distress or that exploit the federal safety net. Thus, risk resulting from higher moments likely plays an important role in bank production.

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232   Activities and Performance Expected Return Larger Output

ERD ERC

D C

ERB

ERA=ERA′

0

B

A′

RiskA′

Smaller Output

A

RiskA=RiskB

RiskC

RiskD

Risk

Figure 8.1  Scale-Related Diversification and Risk-Return Frontiers. Source: Hughes and Mester (2013b).

In Figure 8.1, from Hughes and Mester (2013b), a smaller bank’s menu of investment choices is given by the lower frontier. Consider a smaller bank that operates at point A.5 To illustrate scale-related diversification, suppose a larger bank is created by scaling up the assets of this smaller bank. In principle, the larger bank can obtain better diversification of its assets, which reduces credit risk, and better diversification of its deposits, which reduces liquidity risk. Thus, the larger bank can efficiently produce the expected return of the smaller bank (point A) with less return risk (point A´). In fact, the larger bank will likely take advantage of its better diversification and produce a different (and perhaps more complicated) mix of financial services. Nonetheless, the risk-expected-return frontier of the larger bank lies above that of the smaller bank because the larger bank has a better menu of investment choices resulting from improved diversification. Textbooks point to better diversification, which reduces the costs of risk management, as a key source of scale economies. The link between better diversification and scale economies is apparent when comparing a larger bank operating at point A´ with one operating at point B. A larger bank operating at point A´ has the same expected return but lower risk than the smaller bank operating at point A, while a larger bank at point B operates with the same return risk as the smaller bank but obtains a higher expected return. At point B, the better diversification of deposits allows the larger bank to economize on liquid assets without increasing liquidity risk, while the better diversification of loans 5  To simplify the discussion, we assume that the smaller bank operates efficiently; therefore, point A  lies on the frontier rather than beneath it. See Hughes and Mester (2013b) for an analysis of how ­inefficiency is related to scale economies in banking.

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The Performance of Financial Institutions   233 allows it to economize on equity capital without increasing insolvency risk. Thus, its expected return for the same risk as the smaller bank is higher. Better diversification, though, does not necessarily mean that the larger bank operates with less risk; rather, it means the larger bank experiences a better risk-expected-return frontier. Heightened competition and lower-valued growth opportunities in the larger bank’s markets, or lower marginal costs of risk management, might induce the larger bank to choose to produce its output with more risk in order to obtain a higher expected return—say, the strategy at point C or point D. A bank’s risk-taking is also influenced by external and internal mechanisms that discipline bank managers. Internal discipline might be induced or reduced by organizational form, ownership and capital structure, governing boards, and managerial compensation. External discipline might be induced or reduced by government regulation and the safety net, capital market discipline (takeovers, cost of funds, stakeholders’ ability to sell stock), managerial labor market competition, outside blockholders of equity and debt, and product market competition.6 This operating environment can also create agency conflicts that influence managers’ incentives to pursue valuemaximizing risk strategies. Managers whose wealth consists largely of their undiversified human capital tend to avoid riskier investment strategies that maximize the value of banks with poorer investment opportunities. However, the presence of a diversified outside owner of a large block of stock might encourage the board of directors to put in place a compensation plan that overcomes managers’ risk aversion and encourages value-maximizing risk-taking (Laeven and Levine,  2009; Cheng, Hong, and Scheinkman, 2015). Thus, in order to measure the efficiency of bank production, it is important to account for bank risk-taking and the optimality of this risk-taking.

8.2.2  The Empirical Measurement of Banking Technology and Performance There are two broad approaches to measuring technology and explaining performance: non-structural and structural. Using a variety of financial measures that capture various aspects of performance, the non-structural approach compares performance among banks and considers the relationship of performance to investment strategies and other factors such as characteristics of regulation and governance. For example, the nonstructural approach might investigate technology by asking how performance measures 6  La Porta, Lopez-de-Silanes, and Shleifer (2002) examine banking systems in ninety-two countries and find that government ownership is correlated with poorer countries and countries with less-developed financial systems, poorer protection of investors’ rights, more government intervention, and poorer performance of institutions. They also find that government ownership is associated with higher cost ratios and wider interest rate margins. Aghion, Alesina, and Trebbi (2007) provide evidence that democracy has a positive impact on productivity growth in more advanced sectors of the economy, possibly by fostering entry and competition.

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234   Activities and Performance are correlated with such investment strategies as growing by asset acquisitions and diversifying or focusing the bank’s product mix. It looks for evidence of agency problems in correlations of performance measures and variables characterizing the quality of banks’ governance. While informal and formal theories may motivate some of these investigations, no general theory of performance provides a unifying framework for these studies. The structural approach is choice-theoretic and, as such, relies on a theoretical model of the banking firm and a concept of optimization. The older literature applies the traditional microeconomic theory of production to banking firms in much the same way as it is applied to non-financial firms and industries. The newer literature views the bank as a financial intermediary that produces informationally intensive financial services and takes on and diversifies risks—unique, essential aspects of financial intermediation that are not generally taken into account in traditional applications of production theory.7 For example, the traditional theory defines a cost function by a unique cost-minimizing combination of inputs for any given level of outputs. Thus, the cost function gives the minimum cost of any given output vector without regard to the return risk implied by the cost-minimizing input vector. Ignoring the implied return risk may be appropriate for non-financial firms, but for financial institutions, return risk plays an essential role in maximizing the discounted flow of expected profits. First, return risk influences the rate at which future expected profits are discounted. Second, return risk affects the expected cost of financial distress. The bank with high-valued investment opportunities may find the level of risk associated with the cost-minimizing vector too high. If so, it may choose to reduce the credit risk of the given output vector by adding more labor and physical capital to improve its credit evaluation and loan monitoring capabilities. In doing so, it trades higher cost (lower profit) for lower profit risk to reduce the expected costs of financial distress and the discount rate on its expected cash flow, thus maximizing its market value. This trade-off suggests that measuring bank performance by a cost metric or a profit metric that fails to account for endogenous risk-taking is likely to be seriously biased. Notice in this example that risk influences the decision of how to produce a given output vector and, thus, must influence the cost of producing it. In Figure 8.1, when the risk-expected-return frontier for the larger bank is narrowly interpreted as showing different investment strategies for producing the same output vector—the scaled-up outputs of the smaller bank—it is clear that larger banks with higher-valued investment opportunities are likely to choose a lower risk-expected-return strategy, say, point B or 7  This framework often guides the choice of outputs and inputs in the bank’s production structure. For example, as discussed in Mester (2008), the traditional application of efficiency analysis to banking does not allow bank production decisions to affect bank risk, which rules out the possibility that scaleand scope-related improvements in diversification could lower the cost of borrowed funds and induce banks to alter their risk exposure. Also, much of the traditional literature does not account for the bank’s role in producing information about its borrowers in its underwriting decisions when specifying the bank’s outputs and inputs. An exception is Mester (1992), who directly accounted for banks’ monitoring and screening role by measuring bank output, treating loans purchased and loans originated as separate outputs entailing different types of screening, and treating loans held on balance sheet and loans sold as separate outputs entailing different types of monitoring.

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The Performance of Financial Institutions   235 A´, than banks with lower-valued opportunities, say, point C or D. Since the cost of producing the scaled-up output vector is likely to differ along the frontier, the valuemaximizing input vector and, hence, the cost of the output, will be driven in part by risk considerations. And these risk considerations imply that revenue influences cost when risk matters. How, then, can managers’ preferences for these production plans and their implied risk be represented? Letting the output vector be represented by q, the input vector by x, and equity capital by k, the technology for producing a given output vector is represented by the transformation function T(x, k; q) ≤ 0. Points C and D in Figure 8.1 arise from different input vectors (x, k) that produce the given output q. Let z represent the production plan and price environment. Managers’ beliefs about how production plans interact with a given state of the world, s, to yield profit, π, imply a realization of profit, π = g(z, s), that is conditioned on the state of the world. And managers’ beliefs about the probability distribution of states of the world imply a subjective distribution of profit that is conditional on the production plan: f(π; z). Under well-known restrictive conditions, this distribution can be represented by its first two moments, E(π; z) and S(π; z).8 The traditional literature on bank production and efficiency assumes that banks choose their production plan to minimize expected cost and maximize expected profit: Managers rank production plans by their expected profit and cost, the first moment of their subjective probability distribution of profit, f(π; z), attached to each production plan. The newer research assumes that bank managers maximize the utility of their production plans. Rather than define the utility function over the first two moments, the newer literature defines it over profit and the production plan, U(π; z), which is equivalent to defining it over the conditional probability distributions f(π; z). Utility maximization is a more general objective that subsumes profit maximization and cost minimization (e.g., Hughes, 1999; Hughes et al., 1999; Hughes et al., 2000; Hughes, Mester, and Moon, 2001; Hughes and Mester, 2013b). However, when higher moments of the profit distribution influence managers’ preferences, managers may trade profit to achieve other objectives involving risk, say, value maximization. The model treats the choice of risk as endogenous. Note, though, that the other objectives might reflect agency problems: Managers might take on too little risk in order to protect their jobs, or they might consume private benefits that reduce shareholder wealth. Thus, the utility-maximizing framework can explain inefficient as well as efficient production. When the output vector is held constant, the utility-maximizing cost of output can be derived from the utility-maximizing input demands. This cost function accounts for the choice of whether to produce the particular output vector using a method that has lower risk and lower expected return or a method with higher risk and higher expected return (e.g., point B versus point C in Figure 8.1). This choice depends on differences in the value of investment opportunities. In this case, managers’ ranking of production plans captures the profit and profit-risk environment they face. 8  See Hughes et al. (2000) for further discussion of this model.

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236   Activities and Performance How one gauges performance in structural models, then, depends on whether one views bank managers as ranking production plans by their first moments (i.e., minimum expected cost or maximum expected profit), or, more generally, by higher moments as well as the first moment, that is, considerations involving risk. In the latter case, one would want to gauge the tradeoffs between risk and expected return being made by banks where there is less of an agency problem between owners and managers—that is, banks with strong corporate controls (see Hughes, Mester, and Moon, 2001). In both the structural and non-structural approaches, the performance metric and the specification of the performance equation reflect implicitly or explicitly an underlying theory of managerial behavior. As a general specification of the structural and non-structural approaches, let yi represent the measure of the ith bank’s performance. Let zi be a vector of variables that capture key components of the ith bank’s technology (e.g., output levels and input prices) and let τi be a vector of variables affecting the technology (e.g., the ratio of non-performing to total loans). Jensen and Meckling (1979) add a vector, θi, of characteristics of the property-rights system, contracting, and regulatory environment in which the ith firm operates (e.g., whether the country has a deposit insurance scheme and the degree of investor protection that exists) and a vector, ϕi, of characteristics of the organizational form and the governance and control environment of the ith firm (e.g., whether the bank is organized as a mutual or stock-owned firm, the degree of product market concentration, and the number of outside directors on its board). When the sample of banks used in the estimation includes financial institutions located in environments with different property rights and contracting environments or with different governance and control structures, estimating this model permits one to investigate how these differences are correlated with differences in bank performance. Allowing for random error, the performance equation to be estimated takes the form,

= yi f ( z i , τ i , φi , θ i | β ) + ε i . (1)

The specification of the vectors zi and τi differs between the structural and non-structural approaches.

8.2.3  The Structural Approach to Bank Efficiency Measurement: Cost Minimization, Profit Maximization, X-Inefficiency, and Managerial Utility Maximization The traditional structural approach usually relies on the economics of cost minimization or profit maximization, where the performance equation (1) denotes a cost function or a profit function. Occasionally, the structural performance equation denotes a production function. While estimating a production function might tell us if the firm is technically efficient, that is, if managers organize production such that the firm maximizes the amount

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The Performance of Financial Institutions   237 of output produced with a given amount of inputs (so that the firm is operating on its production frontier), we are more interested in economic efficiency, that is, whether the firm is responding to relative prices in choosing its inputs and outputs to minimize cost and/or to maximize profit, which subsumes technical efficiency. Risk plays no explicit role in these performance functions, although some papers include one or more dimensions of risk in the estimation as control variables. See Berger and Mester (1997, 2003) and Mester (2008) for further discussion. Including risk components as controls does not fully capture the tradeoff between risk and the expected return that banks face. While including risk, for example, the variance of profit, in the cost function might control for the second moment of return, higher moments would not be taken into account, and these higher moments may be an important element in the bank’s production decision. So the standard cost function conditioned on risk is unlikely to capture important considerations in banking production and value maximization. In addition, as discussed below, the assumptions of cost minimization and profit maximization underlying the standard structural approach have been tested and rejected by some papers in the literature. See, for example, Evanoff (1998), Evanoff, Israilevich, and Merris (1990), Hughes et al. (1996, 2000), Hughes, Mester, and Moon (2001), and Hughes and Mester (2013b). In the newer literature, the optimization problem is managerial utility maximization, where the manager ranks production plans not just by their first moment—expected profit—but also by higher moments, such as skewness and kurtosis risk, as well as variance risk, that characterize profit risk. The utility-maximizing cost function is derived from the profit function, conditioned on the output vector. Thus, the cost function includes arguments that characterize revenue. In Figure 8.1 the larger bank can produce its scaled-up output vector with a menu of production plans that differ by their expected profit and profit risk. The utility-maximizing cost function captures the plan that maximizes managerial utility and, thus, reflects a risk-expected-return trade-off. To specify the utility-maximizing performance equation (1), Hughes et al. (1996, 1999, 2000) adapt the Almost Ideal Demand System to derive a utility-maximizing profit equation and its associated input demand equations. This profit function does not necessarily maximize profit, since it follows from managers’ assessment of risk and risk’s effect on asset value; it might also reflect managers’ concerns about their job security. Profit maximization (cost minimization) can be tested by noting that the standard translog profit (cost) function and share equations are nested within the model and can be recovered by imposing the parameter restrictions implied by profit maximization (cost minimization) on the coefficients of this adapted system. Hughes et al. (1996, 1999, 2000) and Hughes and Mester (2013b) test these restrictions in their applications and reject the hypothesis of profit maximization (and cost minimization). Both newer and traditional performance functions can differ by the definition of cost they use: Accounting (cash-flow) cost excludes the cost of equity capital, while economic cost includes it. The challenge of specifying economic cost is in estimating the cost of equity capital. McAllister and McManus (1993) arbitrarily pick the required return and assume it is uniform across banks. Clark (1996) and Fiordelisi (2007) use the Capital Asset Pricing Model to estimate it. Fiordelisi (2007) describes the resulting profit function as

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238   Activities and Performance “economic value added.” Alternatively, the quantity of equity capital can be substituted for its price. In these cases of restricted cost and profit functions, the expense of equity capital is excluded from the empirical measure of cost and profit. The traditional structural performance equation can be fitted to the data as an average relationship, which assumes that all banks are equally efficient at minimizing cost or maximizing profit, subject to random error, εi, which is assumed to be normally distributed. Alternatively, it can be estimated as a frontier to capture best observed practice and to gauge X-inefficiency, the difference between the best-observed-practice performance and achieved performance. The literature has used four basic methods for estimating the frontier: the stochastic frontier, the distribution-free approach, the thick frontier, and data envelopment analysis (DEA). Berger and Mester (1997) review the estimation methods and present evidence on scale economies, cost X-inefficiency, and profit X-inefficiency using the stochastic frontier and distribution-free methods.9 Mester (2008) reviews the concept, measurement, and empirical literature on X-efficiency and Dijkstra (2017) catalogs many of the studies. In the stochastic frontier method, the error term, εi, consists of two components: One is a two-sided random error that represents noise (νi), and the other is a one-sided error representing inefficiency (μi). The stochastic frontier approach disentangles the inefficiency and random error components by making explicit assumptions about their distributions. The inefficiency component measures each bank’s extra cost or shortfall of profit relative to the frontier—the best-practice performance observed in the sample. Leibenstein (1966) called the type of inefficiency that can result from poor managerial incentives or the failure of the labor market to allocate managers efficiently and weed out incompetent managers, X-inefficiency. Jensen and Meckling (1976) called such inefficiency agency costs and provided a theoretical model of managerial utility maximization to explain how, when incentives between managers and outside stakeholders are misaligned, managers may trade off the market value of their firm to enjoy more of their own private benefits, such as consuming perquisites, shirking, discriminating prejudicially, and taking too much or too little risk to enhance their control. Let yi denote either the cost or profit of firm i. The stochastic frontier gives the highest or lowest potential value of yi given zi, τi, ϕi, and θi,

= y i F( z i , τi , φi , θi | β )+ εi , (2)

where εi ≡ μi + νi is a composite error term comprising νi, which is normally distributed with zero mean, and μi, which is usually assumed to be half-normally distributed and negative when the frontier is fitted as an upper envelope in the case of a profit function and positive when the frontier is fitted as a lower envelope as in the case of a cost function. β are parameters of the deterministic kernel, F(zi, τi, ϕi, θi | β), of the stochastic 9  Note that the literature often uses the term “best-practice performance” and sometimes calls it “potential performance.” However, this is somewhat of an abuse of terms, since measured best-practice performance does not necessarily represent the best possible practice, but merely the best practice observed among banks in the sample (see Berger and Mester, 1997; Mester, 2008).

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The Performance of Financial Institutions   239 frontier. The ith bank’s inefficiency is usually estimated by the mean of the conditional distribution of μi given εi,, i.e., E(μi| εi,). The difference between best-observed-practice and achieved performance gauges managerial inefficiency in terms of either excessive cost—cost inefficiency—or lost profit—profit inefficiency. Expressing the shortfall and excess as ratios of their frontier (best observed practice) values yields profit and cost inefficiency ratios. While the fitted stochastic frontier identifies best-observed-practice performance of the banks in the sample, it cannot explain the behavior of inefficient banks. A number of papers have surveyed investigations of bank performance using these concepts: for example, Berger and Humphrey (1997), Berger and Mester (1997), and Berger (2007). A recent comprehensive survey and classification of these models is found in Dijkstra (2017).10 As discussed in Hughes et al. (2000) and Mester (2008), since inefficiency is derived from the regression residual, selection of the characteristics of the banks and the environmental variables to include in the frontier estimation is particularly important. These variables define the peer group that determines best-practice performance against which a particular bank’s performance is judged. If something extraneous to the production process is included in the specification, this might lead to too narrow a peer group and an overstatement of a bank’s level of efficiency. Moreover, the variables included determine which type of inefficiency gets penalized. If bank location, for example, urban versus rural, is included in the frontier, then an urban bank’s performance would be judged against other urban banks but not against rural banks, and a rural bank’s performance would be judged against other rural banks. If it turned out that rural banks are more efficient than urban banks, all else equal, the inefficient choice of location would not be penalized. An alternative to including the variable in the frontier regression is to measure efficiency based on a frontier in which it is omitted and then see how it correlates with efficiency. Several papers have looked at the correlations of efficiency measures and exogenous factors, including Mester (1993, 1996, 1997), and Berger and Mester (1997). Mester (1997) shows that estimates of bank cost efficiency can be biased if bank heterogeneity is ignored. See also Bos et al. (2005) on the issue of whether certain differences in the economic environment belong in the definition of the frontier. Since the utility-maximizing profit function explains inefficient as well as efficient production, it cannot be fitted as a frontier. To gauge inefficiency, Hughes et al. (1996) and Hughes, Mester, and Moon (2001) estimate a best-observed-practice risk-return frontier and measure inefficiency relative to it. The estimated utility-maximizing profit function yields a measure of expected profit for each bank in the sample, and, when divided by equity capital, the expected profit is transformed into expected return on equity, E(πi/k i). Each bank’s expected (or predicted) return is a function of its production plan and other explanatory variables. When the estimation of the profit function allows for heteroscedasticity, the standard error of the predicted return (profit), σi, which is a measure of econometric prediction risk, is also a function of the production plan and 10  See Dijkstra (2017, table 1, p. 29).

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240   Activities and Performance other explanatory variables and varies across banks in the sample.11 The estimation of a stochastic frontier similar to (2) gives the highest expected return at any particular risk exposure:

E(π i / ki ) = α 0 + α1σ i + α 2σ i 2 − µi +ν i , (3)

where νi is a two-sided error term representing noise, and μi is a one-sided error term representing inefficiency. A bank’s return inefficiency is the difference between its potential return and its noise-adjusted expected return, gauged among its peers with the same level of return risk. (Note, however, that if a bank’s managers are taking too much or too little risk relative to the value-maximizing amount, this inappropriate level of risk is not taken into account by this measure of inefficiency.) Koetter (2006) uses the model of managerial utility maximization and the associated measure of risk-return efficiency developed in Hughes et al. (1996, 1999, 2000) to investigate the efficiency of universal banks in Germany between 1993 and 2004. Comparing the measure of return efficiency with cost and profit efficiency estimated by standard formulations, he finds evidence that efficient banks using a low-risk investment strategy score poorly in terms of standard profit efficiency measures, since they also expect lower profit. Hughes, Mester, and Moon (2001) take this a step further by recognizing that the utilitymaximizing choices of bank managers need not be value maximizing to the extent that there are agency problems within the firm and managers are able to pursue their own non-value-maximizing objectives. To identify the value-maximizing banks among the set of all banks, they select the quarter of banks in the sample that have the highest predicted return efficiency. These banks are the most likely group to be maximizing value or, at least, producing with the smallest agency costs. One can use this set of efficient banks to gauge characteristics of the value-maximizing production technology. For example, mean scale economies across this set of banks would indicate whether there were scale economies as banks expand output along a path that maximizes value. In contrast, mean scale economies across all banks would indicate whether there were scale economies as banks expand output along a path that maximizes managers’ utility, but this can differ from the value-maximizing expansion path to the extent that managers are able to pursue their own objectives and these objectives differ from those of outside owners. 11  Note that the estimated profit (or return) function resembles a multi-factor model where the factors are the explanatory variables in the profit function. The regression coefficients can be interpreted as marginal returns to the explanatory variables, and the standard error of the predicted return, a function of the variance–covariance matrix of the estimated marginal returns, resembles the variance of a portfolio return. Hughes (1999) and Hughes, Mester, and Moon (2001) report that the regression of ln(market value of equity) on ln(E(πi/ki)) and ln(σi) for 190 publicly traded bank holding companies has an R-squared of 0.96, which implies that the production-based measures of expected return and risk explain a large part of a bank’s market value. For a regression of the market value of equity on E(πi/ki) and σi, Hughes and Mester (2013b) report R-squared values of 0.99, 0.94, and 0.97 for samples of data from 2003, 2007, and 2010, respectively. These values of R-squared are significantly higher than those obtained by regressing the market value on the accounting net income before and after taxes.

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The Performance of Financial Institutions   241 While the model of managerial utility maximization yields a structural utility-­ maximizing profit function that includes as special cases the standard maximum profit function and a value-maximizing profit function, it is, nevertheless, based on accounting measures of performance. An alternative model developed by Hughes and Moon (2003) gauges performance using the market value of assets. They develop a utility-maximizing q-ratio function derived from a model where managers allocate the potential (frontier) market value of their firm’s assets between their consumption of agency goods (marketvalue inefficiency) and the production of market value, which, given their ownership stake, determines their wealth. The utility function is defined over wealth and the value of agency goods and is conditioned on capital structure, outside blockholder ownership, stock options held by insiders, and other managerial incentive variables. The authors derive a utility-maximizing demand function for market value and for agency goods (inefficiency). Hence, their q-ratio equation is structural and, consequently, enjoys the properties of a well-behaved consumer demand function. The authors use these properties to analyze the relationship between value (or inefficiency) and the proportion of the firm owned by insiders, which is their opportunity cost of consuming agency goods.

8.2.4  The Non-structural Approach to Bank Efficiency Measurement The non-structural approach to bank performance measurement usually focuses on achieved performance and measures yi, in equation (1), by a variety of financial ratios, such as the return-on-assets, the return-on-equity, or the ratio of fixed costs to total costs. However, some applications have used measures of performance that are based on the market value of the firm (which inherently incorporates market-priced risk), such as Tobin’s q-ratio (which is the ratio of the market value of assets to the book value of assets); the Sharpe ratio (which measures the ratio of the firm’s expected return in excess of the risk-free return to the volatility of this excess return (where volatility is measured by the standard deviation of the excess return)); or an event study’s cumulative abnormal return (CAR), which is the cumulative error terms of a model predicting banks’ market return around a particular event. Other applications have measured performance by an inefficiency ratio obtained by estimating either a non-structural or a structural performance equation as a frontier. The non-structural approach focuses on the relationship of these performance measures to various bank and environmental characteristics, including the bank’s investment strategy, location, governance structure, and corporate control environment. For example, the non-structural approach might investigate technology by asking how performance ratios are correlated with characteristics of the bank, such as asset acquisitions, the bank’s product mix, whether the bank is organized as a mutual or stock-owned firm, and the ratio of outside to inside directors on its board. While informal and formal theories may motivate some of these investigations, no general theory of performance provides a unifying framework for these studies.

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242   Activities and Performance For example, Hughes et al. (2018) use stochastic frontier techniques to estimate banks’ best-practice return on assets (ROA) achieved for a given level of ROA risk. The bestpractice ROA gauges the potential return of a bank’s investment opportunities, while the difference between a bank’s best-practice ROA and its achieved ROA, adjusted for noise, eliminates the influence of luck (statistical noise) and gauges its systematic failure to achieve its potential return. ROA inefficiency measures a bank’s effectiveness in exploiting its investment opportunities and adds an important performance measure to the standard measures of achieved ROA and risk-normalized ROA. Assaf et al. (2018) estimate cost and profit functions and use the distribution-free approach to gauge cost and profit efficiency in the years preceding the financial crises in the US economy. They then ask how these measures of efficiency are related to ­performance during a financial crisis. They find that cost efficiency in periods of ­normal economic activity is related to improved ROA and return on equity (ROE) and reduced return risk and risk of failure during crises. However, profit efficiency yields limited benefits, perhaps because it could reflect higher returns from riskier investments. Fiordelisi, Marques-Ibanez, and Molyneux (2011) investigate the intertemporal relationship of cost and revenue efficiency, capital, and risk in European banks during the period 1995–2007. Their evidence suggests that lower efficiency is associated with higher future bank risk and that increases in capital are related to future cost efficiency improvements. Moreover, higher efficiency is associated with higher future capitalization. In an innovative study of bank performance, Egan, Lewellen, and Sunderam (2017) develop two measures of bank productivity: one focused on deposit-taking and the other on the returns generated by a bank’s asset allocation. They study how the market-tobook ratio is related to the two measures and find that deposit productivity is associated with the majority of variation in bank value. Moreover, they find synergies between deposit-taking and lending. High deposit productivity is associated with high asset productivity. These results are consistent with those of Mester, Nakamura, and Renault (2007), who find synergies between the liability and asset sides of a commercial bank’s balance sheet. Using the frontier methods in a non-structural approach, Hughes et al. (1997) proposed a proxy for Jensen and Meckling’s agency cost: a frontier of the market value of assets fitted as a potentially non-linear function of the book-value investment in assets and the book value of assets squared. This frontier gives the highest potential value observed in the sample for any given investment in assets. For any bank, the difference between its highest potential value and its noise-adjusted achieved value represents its lost market value—a proxy for agency cost (X-inefficiency). Several studies have used either this systematic lost market value or the resulting noise-adjusted q-ratio to measure performance: Baele, De Jonghe, and Vander Vennet (2006), Hughes et al. (2003), De Jonghe and Vander Vennet (2005), Hughes and Moon (2003), Hughes et al. (1999), Hughes, Mester, and Moon (2001), Hughes and Mester (2013a and 2013b), and Hughes, Mester, and Moon (2016). Habib and Ljungqvist (2005) specified an alternative market-value frontier as a function of a variety of managerial decision variables, including size, financial leverage, capital

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The Performance of Financial Institutions   243 expenditures, and advertising expenditures. Thus, the peer grouping on which the frontier is estimated is considerably narrower than the wide grouping based on investment in assets, and inefficient choices of these conditioning values are not accounted for in the measurement of agency costs.

8.2.5  Specifying Outputs and Inputs in Structural Models of Production In estimating the standard cost or profit function or the managerial utility maximization model, one must specify the outputs and inputs of bank production. The intermediation approach (Sealey and Lindley, 1977) focuses on the bank’s production of intermediation services and the total cost of production, including both interest and operating expenses. Outputs are typically measured by the dollar volume of the bank’s assets in various categories. As mentioned above, an exception is Mester (1992), who, to account for the bank’s screening and monitoring activities, measured outputs as loans previously purchased (which require only monitoring), loans currently originated for the bank’s own portfolio, loans currently purchased, and loans currently sold. Inputs are typically specified as labor, physical capital, deposits and other borrowed funds, and, in some studies, equity capital. While the intermediation approach treats deposits as inputs, there has been some discussion in the literature about whether deposits should be treated as an output, since banks provide transactions services for depositors. Hughes and Mester (1993) formulated an empirical test for determining whether deposits act as an input or an output. Consider variable cost, VC, which is the cost of non-deposit inputs and is a function of the prices of non-deposit inputs, w, output levels, y, other variables affecting the technology, τ, and the level of deposits, x. If deposits are an input, then ∂VC/∂x < 0: Increasing the use of some input should decrease the expenditures on other inputs. If deposits are an output, then ∂VC/∂x > 0: Output can be increased only if expenditures on inputs are increased. Hughes and Mester’s empirical results indicate that insured and uninsured deposits are inputs at banks in all size categories.

8.2.6  Specifying Capital Structure in Performance Equations Typically, cost and profit functions are measured without considering the bank’s capital structure, which results in a seriously mis-specified model that omits an important funding input: equity capital. However, the newer literature recognizes the importance of bank managers’ choice of risk and capital structure to bank performance. Some of the first structural models to include equity capital as an input are Hancock (1985, 1986), McAllister and McManus (1993), Hughes and Mester (1993), Clark (1996), and Berger and Mester (1997).

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244   Activities and Performance As discussed in Hughes and Mester (1993), Berger and Mester (1997), Hughes (1999), and Mester (2008), a bank’s insolvency risk depends not only on the riskiness of its portfolio but also on the amount of financial capital it has to absorb losses. Insolvency risk affects bank costs and profits through (1) the risk premium the bank has to pay for uninsured debt, (2) the intensity of risk management activities the bank undertakes, and (3) the discount rate applied to future profits. A bank’s capital level also directly affects costs by providing an alternative to deposits as a funding source for assets. Most studies use the cash-flow (accounting) concept of cost, which includes the interest paid on debt (deposits) but not the required return on equity, as opposed to economic cost, which includes the cost of equity. Failure to include equity capital among the inputs can bias efficiency measurement. If a bank were to substitute debt for some of its financial equity capital, its accounting (cash-flow) costs could rise, making the less capitalized bank appear to be more costly than the more well-capitalized bank. To solve this problem, one can include the level of equity capital as a quasi-fixed input in the cost function. The resulting cost function captures the relationship of cash-flow cost to the level of equity capital, and the (negative) derivative of cost with respect to equity capital—the amount by which cash-flow cost is reduced if equity capital is increased—gives the shadow price of equity. The shadow price of equity will equal the market price when the amount of equity minimizes cost or maximizes profit. Even when the level of equity does not conform to these objectives, the shadow price nevertheless provides a measure of its opportunity cost. Hughes, Mester, and Moon (2001) find that the mean shadow price of equity for small banks is significantly smaller than that of larger banks. This suggests that smaller banks over-utilize equity relative to its cost-minimizing value, perhaps to protect charter value. On the other hand, larger banks appear to under-utilize equity relative to its cost-minimizing value, perhaps to exploit a cost-of-funds subsidy due to deposit insurance and the too-big-to-fail doctrine. In both cases, these capital strategies, while not minimizing cost, may be maximizing value.

8.2.7  Specifying Output Quality in the Performance Equation In measuring efficiency, one should control for differences in output quality to avoid labeling unmeasured differences in product quality as differences in efficiency. Controls for loan quality, for example, non-performing loans to total loans by loan category or loan losses, are sometimes included in the cost or profit frontier as controls (see Mester, 2008, for further discussion).12 12  As discussed in Berger and Mester (1997), whether it is econometrically appropriate to include non-performing loans or loan losses in the cost or profit function depends on the extent to which these variables can be treated as exogenous. If the main driver of losses is economic shocks (bad luck), the variables could be considered exogenous. If losses largely reflect management decisions (e.g., management is inefficient or has made a conscious decision to cut short-run expenses by cutting back on loan origination and monitoring resources), then it may not be appropriate to treat the variables as exogenous.

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The Performance of Financial Institutions   245 The variable, non-performing loans, can also play a role as a quasi-fixed “input” whose quantity rather than price is included in the performance equation. As such, its “cost”—loan losses—is excluded from the performance metric, either cost or profit. Its price is the expected loan-loss rate. Hence, when the cost of non-performing loans, that is, loan losses, is excluded from the performance measure, a case can be made for including the level of non-performing loans, and when the performance measure is net of loan losses, the logic suggests that the loss rate be included in the specification of the performance equation. Hughes and Moon (2018) suggest that the relationship between bank performance and the non-performing loan ratio can be decomposed into two parts: (1) non-performance due to the inherent credit risk the bank assumes and (2) non-performance due to the proficiency of the bank in assessing credit risk and monitoring loan performance. They use stochastic frontier techniques to estimate the minimum non-performance ratio observed in the sample, conditional on the volume and composition of a bank’s loans, the average contractual interest rate charged on these loans, and market conditions such as the average GDP growth rate and market concentration. This minimum ratio reflects the best-practice ratio—the ratio that a bank would experience if it were fully efficient at credit-risk evaluation and loan monitoring—and gauges the inherent credit risk of the loan portfolio. The difference between a bank’s noise-adjusted observed non-performing loan ratio and the best-practice minimum ratio reflects the elimination of the influence of luck (statistical noise) and gauges the bank’s inefficiency at lending. Restricting the sample to publicly traded US bank holding companies and gauging financial performance by market value at year-end 2013, they find that the ratio of non-performing loans to total loans is, on average, negatively related to financial performance except at the largest banks. This positive association of financial performance with non-performing loans at the largest banks can be refined by decomposing non-performance into inherent credit risk and lending inefficiency: The results suggest that taking more inherent credit risk enhances market value at a larger group of large banks, not just the largest ones, while lending inefficiency is negatively related to market value at all banks. Thus, market discipline appears to reward riskier lending at large banks and discourage lending inefficiency at all banks. Hughes et al. (2018) use this technique to compare the business lending and commercial real estate lending performance of banks in three size groups: banks with assets of less than $1 billion (small community banks), banks with assets between $1 billion and $10 billion (large community banks), and banks with assets between $10 billion and $50 billion (mid-size banks). They find that for business lending and commercial real estate lending, large community banks and mid-size banks assume higher inherent credit risk and exhibit more efficient lending. They also find that, unlike small community banks, large community banks have financial incentives to increase lending to small businesses. To solve this problem, Berger and Mester (1997) use the ratio of nonperforming loans to total loans in the bank’s state as the control variable. The state average would be nearly entirely exogenous to any one bank, but can control for negative shocks that affect bank output quality.

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8.3  Applications of the Structural Approach 8.3.1  Performance in Relation to Organizational Form, Governance, Regulation, and Market Discipline An increasing number of papers using structural models are exploring the importance of governance and ownership structure to the performance of banks. The structural model is first used to obtain a frontier-based measure of inefficiency. Then inefficiency is regressed on a set of explanatory variables. Using confidential regulatory data on small, closely held commercial banks, DeYoung, Spong, and Sullivan (2001) use a stochastic frontier to measure banks’ profit efficiency. They find banks that hire a manager from outside the group of controlling shareholders perform better than those with owner-managers; however, this result depends on motivating the hired managers with sufficient holdings of stock. They calculate an optimal level of managerial ownership that minimizes profit inefficiency. Higher levels of insider holdings lead to entrenchment and lower profitability. Berger and Hannan (1998) consider the relationship of bank cost efficiency, estimated by a stochastic frontier, to product market discipline, gauged by a Herfindahl index of market power. They find that the reduced discipline of concentrated markets is associated with a loss of cost efficiency far more significant than any welfare loss due to monopoly pricing. DeYoung, Hughes, and Moon (2001) use the model of managerial utility maximization developed by Hughes et al. (1996, 2000) to estimate expected return and return risk. Using these values, they estimate a stochastic risk-return frontier as in equation (3) to obtain each bank’s return inefficiency. They consider how banks’ supervisory CAMEL ratings are related to their size, their risk-return choice, and their return inefficiency. They find that the risk-return choices of efficient banks are not related to their supervisory rating, while the higher-risk choices of inefficient banks are penalized with poorer ratings. Moreover, the risk-return choices of large inefficient banks are held to a stricter standard than smaller banks and large efficient banks. Two studies by Mester (1991, 1993) investigate differences in scale and scope measures for stock-owned and mutual savings and loans by estimating average cost functions. She finds evidence of agency problems at mutual S&Ls, as evidenced by diseconomies of scope, prior to the industry’s deregulation, and evidence that these agency costs were lessened after the deregulation in the mid-1980s. Using data for the period 1989–96, Altunbas, Evans, and Molyneux (2001) estimate separate and common frontiers for three organizational forms in German banking: private commercial, public (government-owned) savings, and mutual cooperative banks. They argue that the same technology of intermediation is available to all so that the

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The Performance of Financial Institutions   247 choice of technology is a management decision whose efficiency should be compared among all types of firms. The private sector appears to be less profitable and less cost efficient than the other two sectors. These results are especially clear in the case of the common frontier, but they are also obtained from the estimation of separate frontiers.

8.3.2  Uncovering Evidence of Scale Economies by Accounting for Risk and Capital Structure Former Federal Reserve Chairman Alan Greenspan (2010) summarized the literature on scale economies in banking: “For years the Federal Reserve had been concerned about the ever larger size of our financial institutions. Federal Reserve research had been unable to find scale economies in banking beyond a modest-sized institution.” But, in fact, many investigators, including some at the Fed, have found evidence of scale economies even at the largest financial institutions. This research includes, for example, Hughes et al. (1996), Berger and Mester (1997), Hughes and Mester (1998), Hughes, Mester, and Moon (2001), Berger and Mester (2003), Bossone and Lee (2004), Feng and Serletis (2010), Wheelock and Wilson (2012), Hughes and Mester (2013b), and Dijkstra (2017). Dijkstra (2017) provides an extensive classification of papers investigating scale and scope economies by their techniques and findings.13 The Greenspan observation raises the fundamental question: Are scale economies in banking illusive or elusive? The investment strategies of many of the largest financial institutions constituted ground zero in the recent banking crisis, and their rescue under the too-big-to-fail doctrine has prompted some prominent policymakers to call for breaking up the largest banks. For example, Fisher and Rosenblum (2012) assert, “Hordes of Dodd-Frank regulators are not the solution; smaller, less complex banks are. We can select the road to enhanced financial efficiency by breaking up TBTF banks— now.” Hoenig and Morris (2012) call for limiting the government safety net to the core activities of commercial banks, including lending, taking deposits, providing liquidity and credit intermediation services, and disallowing banks from doing certain non-core banking activities, including engaging in broker–dealer activities, making markets in derivatives or securities, trading derivatives and securities for their own account or their customers’, or sponsoring hedge funds or private equity funds. Tarullo (2011), however, questions whether breaking up banks would lead to efficiency and suggests there is a tradeoff between concerns for systemic risk and efficiency: “An additional concern would arise if some countries made the trade-off by limiting the size or configuration of their financial firms for systemic risk reasons at the cost of realizing genuine economies of scope or scale, while other countries did not. In this case, firms from the first group of countries might well be at a competitive disadvantage in the provision of certain crossborder activities.” And Powell (2013) indicates that if the current regulatory reform 13  See Dijkstra (2017, table 3, p. 38).

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248   Activities and Performance agenda succeeds in substantially reducing the likelihood of bank failure and minimizing the externalities caused by a large bank failure, then in his view, this would be preferable to breaking up the banks, since such a break-up would “likely involve arbitrary judgments, efficiency losses, and a difficult transition.” While textbooks assert that scale economies characterize banking (e.g., Kohn, 2004; Saunders and Cornett, 2010), these economies elude many empirical studies because the studies generally fail to account for the effects of endogenous risk-taking on banks’ cost as bank size increases. Textbooks cite diversification as one component of the technology that generates scale economies. As discussed above, in Figure 8.1, the larger bank enjoys a better risk-expected-return trade-off and chooses its risk exposure on that improved frontier to maximize managerial utility, which is likely associated with expected shareholder value in the absence of severe agency problems. The increase in cost due to the larger output will depend on the investment strategy the larger bank chooses. For example, as a bank scales up its output and moves from point A to point A´, diversification has resulted in lower risk, and cost is likely to have increased less than proportionately than the increase in output. If risk-taking is costly, then the investment strategy at point C may result in, say, a proportional increase in cost compared to operating at point A, while the investment strategy at point D may imply a more than proportional increase in cost. Hughes (1999) contends that studies of how cost varies with output that ignore the effects of endogenous risk-taking on cost, are likely to identify the technology as constant returns to scale when larger banks tend to produce at point C and as scale diseconomies when larger banks tend to produce at point D. To the extent that larger banks are generally more risky than smaller banks (Demsetz and Strahan, 1997), the naïve econometric investigation of banking cost that ignores endogenous risk-taking is likely to find that larger banks experience constant returns to scale or even scale diseconomies. Hughes, Mester, and Moon (2001) call the effect on cost from moving from point A to point A´, the diversification effect—diversification leads to a decline in risk for the same level of expected profit. They call the effect on cost of moving from point A´, which resulted from better scale-related diversification, to point C or D, the risk-taking effect. Accounting for endogenous risk-taking—isolating the diversification effect—in estimating scale economies requires controlling for revenue as well as cost. While the traditional cost function does not incorporate any revenue terms, the utility-maximizing cost function incorporates revenue because it is derived from the utility-maximizing profit function, conditioned on the output vector, and as noted earlier, it reflects bank managers’ choice of risk as well as expected return. In Figure 8.1, suppose that the smaller bank chooses to produce its output vector with the investment strategy at point A and the large bank chooses to produce its output vector with the strategy at point D. Scale economies estimated in the neighborhood of point A refer to the increase in cost for a  small proportional increase in outputs given the investment strategy at point A. If  expanded output allows for better diversification that lowers costs for a given expected return, then the estimated scale economies would compare cost at point A to

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The Performance of Financial Institutions   249 cost at point A´. In this way, it would isolate the diversification effect and avoid the bias of measuring scale economies at point D relative to point A.14 Hughes and Mester (2013b) estimate several traditional cost functions and the riskreturn-driven cost function for US bank holding companies in 2003, 2007, and 2010. In all three years, estimates derived from the traditional minimum cost functions, which do not take into account the banks’ risk-expected-return choice, indicate modest scale economies or, in some cases, constant returns to scale. In contrast, the utility-maximizing cost function, which takes into account the banks’ risk-expected-return choice, yields evidence of large-scale economies that increase with the scale of the bank. For example, in 2007, for the smallest banks (with less than $0.8 billion in assets), estimated scale economies is 1.12, which means that a 10 percent increase in output levels is associated with an 8.8 percent increase in cost. For the largest banks (with greater than $100 billion in assets), estimated scale economies is 1.34, which means that a 10 percent increase in output levels is associated with a 7.5 percent increase in cost. Hughes and Mester (2013b) also find that the estimated expected profit and profit risk obtained from this model explain between 94 and 99 percent of the variation in US bank market value between the years 2003 and 2010. Thus, these measures of performance and best-practice capture the capital market’s assessment of banks’ market-priced risk and performance. Dijkstra (2017) also estimates the risk-return-driven cost function and standard formulations of the cost function for banks in countries in the Eurozone for each year from 2002 through 2011 and compares estimates of scale economies based on these estimated functions. The results based on the standard formulations of the cost function show scale economies in the early part of the time period that turn into diseconomies around the start of the financial crisis in 2008. But estimates based on the risk-returndriven cost function indicate scale economies at banks of all sizes that rise throughout the sample period, with magnitudes similar to those in Hughes and Mester (2013b). In addition, Dijkstra’s (2017) estimates based on the risk-return-driven cost function indicate economically significant scope economies. Dijkstra finds that scale economies measured by the risk-return-driven cost function increase over the span of his data, 2002 through 2011. This finding is consistent with the substantial improvements in banking technology that have occurred over this period. Advances in information technology and communications have improved the efficiency of payments networks, credit evaluation, loan monitoring, risk management, and organizational control. In addition, deregulation of interstate banking in the US has allowed 14  Demsetz and Strahan (1997) demonstrate that a larger scale of operations leads to better diversification of banking risk—in particular, bank-specific risk estimated from a multi-factor asset pricing model. To isolate this diversification effect, they regress bank-specific risk on asset size and find a small negative association. When they control for the many ways banks take risk, the relationship between risk and asset size becomes much more negative and statistically significant. They note that isolating the scale-related diversification effect requires controlling for differences in business strategies that influence risk exposure. Finding the effect of scale-related diversification on scale economies requires a similar approach to controlling for endogenous risk-taking.

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250   Activities and Performance banks to expand their scale to exploit cost economies related to scale and has improved takeover discipline in banking.15 Dijkstra’s estimates of scale economies for European banking increase from 1.160 in 2002 to 1.271 in 2011. Hughes et al. (2000) estimate the risk-return-driven cost function and find scale economies of 1.146 for US banks in 1990. Hughes, Mester, and Moon (2001) estimate scale economies of 1.145 for US banks in 1994. Hughes and Mester (2013b) estimate scale economies of 1.183 for US banks in 2003 compared to 1.254 for US banks in 2010. For the largest US financial institutions with assets exceeding $100 billion, Hughes and Mester (2013b) estimate scale economies of 1.357 in 2003 and 1.432 in 2010. Using the methods of Wheelock and Wilson (2012), Wheelock and Wilson (2017) compare estimates of scale economies for US banks in 2006 to those in 2015. They find that 27 percent more banks experienced increasing returns in 2015 than in 2006 and that (p. 20) “. . . the largest four banks have seen significant increases in returns to scale since 2006, suggesting that scale economies still provide an impetus to become even larger.” These estimates of scale economies, which increase over time, are consistent with the hypothesis that technological improvements substantially reduce the average cost of financial products and services and, as Wheelock and Wilson (2017) observe, provide strong incentives to institutions to increase their scale to exploit these improving economies.16 Spreading overhead costs, such as those related to technology and regulatory compliance, over a larger scale is often cited as an important source of scale economies in banking. Kovner, Vickery, and Zhou (2014) investigate this issue and find evidence of  operating cost economies when they control for a bank’s investment strategy. Controlling for the bank’s investment strategy when measuring the effect of an increase in scale on cost can be illustrated in our Figure 8.1. This would be equivalent to assessing the increase in cost when a bank moves from A to A´ rather than when it moves from point A to C or D—points that represent riskier investment strategies. When Kovner, Vickery, and Zhou estimate the cost elasticity without controlling for the investment strategy, they find that a 10 percent increase in assets implies a 9.93 percent increase in operating cost—essentially constant returns to scale. When they control for asset allocation, the cost elasticity falls to 9.79 percent. When they control for asset allocation, revenue sources, funding structure, and organizational complexity, the operating cost elasticity falls to 8.99 percent—evidence of scale-related operating cost economies. Moreover, operating scale economies increase with bank size, so that the largest financial institutions obtain the largest operating cost economies. This evidence of large-scale economies at the largest financial institutions suggests that breaking them up into smaller institutions with the goal of reducing the systemic risk they pose would reduce their competitiveness in global financial markets. Using 15  See Brook, Hendershott, and Lee (1998), who investigate how the relaxation of interstate banking restrictions in the US improved bank performance. 16  As described previously, cost studies based on the mis-specified cost function that fails to account for potentially costly endogenous risk-taking are likely to underestimate scale economies. Using data from the 1980s, such studies typically failed to find evidence of scale economies except at the smallest banks. On the other hand, data obtained from the 1990s were more likely to yield estimates of scale economies at larger banks. Thus, even these estimates suggest technological advances. For a detailed catalogue of these studies, see Dijkstra (2017).

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The Performance of Financial Institutions   251 their 2007 estimates, Hughes and Mester (2013b) consider breaking in half each of the seventeen institutions that exceed $100 billion in consolidated assets to create thirtyfour banks with total assets equal to those of the seventeen larger institutions. Holding product mix constant, that is, assuming the smaller institutions produce the same product mix as the larger ones, their costs are 23 percent higher. In a similar exercise, Wheelock and Wilson (2012), who also find large-scale economies at banks of all sizes, scale back the four largest US institutions in 2009 to a size of $1 trillion and increase their numbers so that the total assets of the smaller institutions equal those of the larger institutions. They find that the cost of the smaller institutions is approximately 19 percent higher. These two exercises suggest that breaking up the largest institutions into smaller institutions will limit their global competitiveness and provide incentives to produce their financial services offshore, where such limits are not operative. A related issue in this literature questions whether the estimated scale economies at the largest financial institutions result from cost-of-funds subsidies due to banks being considered too big to fail. Hughes and Mester (2013b) present several pieces of evidence indicating that the large-scale economies they find are not driven by a cost-of-funds subsidy derived from banks being considered too big to fail. First, they find large-scale economies at small banks in their sample as well as at large banks. Second, when they re-estimate their model excluding banks with assets greater than $100 billion, and then calculate scale economies out of sample for the largest banks, their results are unchanged. Finally, they calculate scale economies for the largest banks if they faced the cost-of-funds of smaller banks. Again, their results are unchanged. Hughes and Mester (2013b) conclude that the underlying technology, not too-big-to-fail subsidies, accounts for the scale economies of the largest financial institutions. Davies and Tracey (2014) adopt the strategy used by Hughes and Mester (2013b) of replacing the observed price of borrowed funds with a price that seeks to eliminate the too-big-to-fail subsidy—one derived from a Moody’s rating for each bank that assumes government assistance in financial distress. The authors find that using the actual observed price of borrowed funds yields evidence of scale economies that disappear when the pseudo price is used. The authors assume that this difference in measured scale economies is due to a too-bigto-fail subsidy. However, there is a critical difference between their methodology and that of Hughes and Mester (2013b). Hughes and Mester measure scale economies by substituting the pseudo prices into the fitted measure of scale economies, which is derived from the cost function estimated using the actual input prices, outputs, and control variables that the banks faced. Davies and Tracey do not use the original estimated cost function. Instead, they re-estimate the cost function and share equations using the pseudo prices along with the actual observed data on the other variables, including total cost, cost shares, other input prices, outputs, and control variables. Thus, the total costs and cost shares used in the re-estimation do not match the prices used. The model assumes that banks minimize cost with respect to the pseudo prices, but since these pseudo prices do not give rise to the observed cost and cost shares, the resulting ­re-estimated technology is difficult to interpret. Kroszner (2016) considers differences in funding costs not only between large and small financial institutions but also between large and small firms in non-financial

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252   Activities and Performance industries—industries where there is no possibility of government support during financial distress. He finds that funding costs are lower for large firms across many industries: from 84 basis points for energy to 5 basis points for utilities, with banks in the middle at 35 basis points. Using data from the period 2004 to 2013, Ahmed, Anderson, and Zarutskie (2015) find that the borrowing costs of non-financial firms as well as those of financial firms tend to decline with borrower size; moreover, financial firms exhibit lower borrowing costs that are less sensitive to size than those in several other industries. They suggest that size-related differences in borrowing costs may be partially influenced by higher liquidity and recovery rates of larger borrowers, rather than government subsidies related to size. Minton, Stulz, and Taboada (2017), whose investigations we discuss in the next section, study banks over the period 1987–2015 and find no evidence that larger banks benefit from too-big-to-fail subsidies.

8.4  Applications of the Non-Structural Approach 8.4.1  Measuring the Value of Investment Opportunities (“Charter Value”) The value of a bank’s investment opportunities is often measured by Tobin’s q-ratio; however, in the presence of agency costs, Tobin’s q-ratio captures only the ability of the incumbent managers to exploit these opportunities. Ideally, the value of investment opportunities should be gauged independently of the ability and actions of the current management. Hughes et al. (1997) and Hughes et al. (2003) propose a measure based on fitting a stochastic frontier to the market value of assets as a function of the book value of assets and variables characterizing the market conditions faced by banks in their local markets. These conditions include a Herfindahl index of market power and the macroeconomic growth rate. The fitted frontier gives the highest potential value of a bank’s assets in the markets in which it operates. Thus, this potential value is conditional on the location of the bank and represents the value the bank would fetch in a competitive auction. Hughes et al. (1997) define this value as the bank’s “charter value”—its value in a competitive auction.

8.4.2  Measuring the Performance of Capital Strategies Several papers have used the non-structural performance equation to examine the relationship between bank value and bank capital structure. Hughes et al. (1997) regress performance measured by Tobin’s q-ratio and market-value inefficiency on a number of variables characterizing bank production. Calomiris and Nissim (2007) regress the ratio

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The Performance of Financial Institutions   253 of the market value of equity to its book value on a similar list of variables. De Jonghe and Vander Vennet (2005) apply the market-value frontier of Hughes et al. (1997) to derive a noise-adjusted measure of Tobin’s q, which they use to evaluate how leverage and market power are related to value. Hughes, Mester, and Moon (2016) regress performance based on the market value of assets and on the shortfall of the market value of assets, obtained from a market-value frontier, on banks’ capital structure and variables that characterize banks’ business strategy. All four studies find evidence that banks follow dichotomous strategies for enhancing value, as predicted by Marcus (1984): a strategy that entails lower risk and lower leverage and a strategy that entails higher risk and higher leverage.

8.4.3  Measuring the Performance of Business Strategies A common result in the corporate finance literature is that non-financial conglomerates, which combine firms in different industries, trade at a discount. Klein and Saidenberg (2010) consider the extent to which such a diversification discount exists in commercial banking. Because banks’ scope is generally limited to financial products and services, a diversification discount in banking would likely result from organizational complexity rather than industry diversification. They use data from 1990–4, a period before geographical restrictions were lifted by the Riegle–Neal Act when banks crossed state lines by forming a holding company to operate separate bank subsidiaries in other states. They find that bank holding companies with many subsidiaries have, on average, a lower Tobin’s q-ratio than banks with fewer subsidiaries. They conclude that organizational complexity, in addition to scope-related diversification, may also contribute to the diversification discount reported in the corporate finance literature. Brook, Hendershott, and Lee (1998) investigate how bank performance was affected by the Riegle-Neal Act’s lifting of interstate branching restrictions, a liberalization that allowed bank holding companies to consolidate subsidiaries operating across state lines. They find evidence in support of their hypothesis that relaxation of the restrictions on interstate banking improved bank performance through better exploitation of scale economies and through enhanced market discipline due to more extensive takeover threats. Using event–study methodology, they investigate the reaction of bank stock prices to the passage of the legislation and find a statistically significant positive CAR. Underperforming banks whose management was least entrenched received the highest CAR. Minton, Stulz, and Taboada (2017) investigate the relationship between bank valuation and asset size. Using Tobin’s q-ratio and the market-to-book value of equity to measure valuation, they find a statistically insignificant relationship between bank asset size and valuation for banks with assets in the $10 billion to $50 billion range, but a significantly negative association between size and valuation for banks with assets greater than $50 billion. Their analysis suggests that this negative association is due to the volume of trading assets that a bank holds. Namely, they find that banks with more trading assets

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254   Activities and Performance are valued less, and that larger banks tend to have larger volumes of trading assets relative to assets. Cetorelli, Jacobides, and Stern (2017) use a new data set that details the organizational structure of US bank holding companies. They map a bank’s entry and exit across scoperelated sectors and find that scope expansion is, on average, associated with worse financial performance measured by the Tobin q ratio and by ROE. Schmid and Walter (2014) adopt a strategy developed by Berger and Ofek (1995) to look for evidence of a scope-related diversification discount in banking. They construct a measure of excess value that compares a bank’s value to its value were its segments operating as standalones. They define these segments by categorizing a bank’s assets into distinct industry segments. The value of each of these segments is given by the median ratio of the market value of assets per dollar of assets for banks that operate solely in a segment. The imputed value of a bank that operates in multiple segments were its assets divided into stand-alone segments is computed as the asset-weighted sum of values across the segments in which the bank holds assets. The authors find that, on average, the imputed stand-alone value of the portfolio is greater than that of the diversified firm. The diversification discount is approximately 11 percent in 2005 but statistically insignificant throughout the ensuing financial crisis. The textbook definition of scope economies compares the cost of producing an output vector in a single multi-product firm with the cost of producing it in separate singleproduct firms. Mester (1991) proposes a technique of estimating scope economies from the multi-product cost estimation that does not require finding banks in the sample that produce only one type of output, or setting the value of a particular type of output to zero in the estimated cost function when no firms in the sample produce at this level. Essentially, this technique indicates whether the marginal cost of a particular output increases or decreases with another output. If it decreases, there are scope economies between the two outputs. Hughes and Mester (1993) apply this technique to US data and do not find evidence of overall scope economies. Dijkstra (2017) applies it to Eurozone banks and finds evidence of scope economies.

8.4.4  Relationship of Ownership Structure to Bank Value In an influential study, Morck, Shleifer, and Vishny (1988) hypothesized that managerial ownership creates two contrasting incentives: A higher ownership stake, first, better aligns the interests of managers and outside owners and, second, enhances managers’ control over the firm and makes it harder for managers to be ousted when they are not efficient. Measuring performance by Tobin’s q, these authors provide evidence that the so-called alignment-of-interests effect dominates the entrenchment effect at lower levels of managerial ownership, while the entrenchment effect dominates over a range of higher levels. Studies that attempt to measure the net effect of the alignment and entrenchment effects on firm valuation cannot identify these effects individually—only their sum in

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The Performance of Financial Institutions   255 the form of the sign of a regression coefficient or a derivative of a regression equation. Adams and Santos (2006) cleverly isolate the entrenchment effect by considering how the proportion of a bank’s common stock that is controlled but not owned by the bank’s own trust department, is statistically related to the bank’s economic performance. The voting rights exercised by management through the trust department enhance management’s control over the bank but do not align their interests with outside shareholders’ because the beneficiaries of the trusts, not the managers, receive the dividends and the capital gains and losses. Caprio, Laeven, and Levine (2003) study the effect of ownership, shareholder protection laws, and supervisory and regulatory policies on the valuations of banks around the world. The authors construct a database of 244 banks across forty-four countries. They measure performance by Tobin’s q-ratio and by the ratio of the market value of equity to the book value of equity. They find evidence that (1) banks in countries with better protection of minority shareholders are more highly valued; (2) bank regulations and supervision have no significant effect on bank value; (3) the degree of cash-flow rights of the largest owner has a significant positive effect on bank value; and (4) an increase in ownership concentration has a larger positive effect on valuation when the legal protection of minority shareholders is weak. Laeven and Levine (2009) consider a sample of large banks in forty-eight countries in 2001 and investigate how the cash-flow rights of the largest shareholder and various regulatory provisions affect the probability of insolvency. They find that the cash-flow rights of the largest shareholder are positively related to the risk of insolvency. They also find that when there is a shareholder with large cash-flow rights, deposit insurance and activity restrictions are associated with increased insolvency risk, but they are uncorrelated with insolvency risk when the bank is widely held. Hughes et al. (2003) examine US bank holding companies and find evidence of managerial entrenchment among banks with higher levels of insider ownership, more valuable growth opportunities, poorer financial performance, and smaller asset size. When managers are not entrenched, asset acquisitions and sales are associated with reduced market value inefficiency. When managers are entrenched, sales are associated with smaller reductions in inefficiency, while acquisitions are associated with greater inefficiency.

8.5  Conclusions and Policy Implications Great strides have been made in the theory of bank technology in terms of explaining banks’ comparative advantage in producing informationally intensive assets and financial services and in taking, diversifying, and offsetting a variety of risks. Great strides have also been made in explaining sub-par managerial performance in terms of agency theory and in applying these theories to analyze the particular environment of banking. In recent years, the empirical modeling of bank technology and

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256   Activities and Performance the measurement of bank performance have begun to incorporate these theoretical developments and yield interesting insights that reflect the unique nature and role of banking in modern economies. This new literature recognizes that the choice of risk influences banks’ production decisions (including their mix of assets, asset quality, off-balance-sheet hedging activities, capital structure, debt maturity, and resources allocated to risk management), and so, in turn, affects banks’ costs and profitability. Measures of bank performance should take account of this endogeneity. The estimation of structural models that incorporate managerial preferences for expected return and risk has uncovered significant scale economies in banking that increase with bank scale, a finding that differs from the earlier literature but accords with the consolidation of the banking industry that has been occurring worldwide. This finding of significant scale economies at the largest financial institutions also suggests that proposals to break up these institutions into smaller institutions in an attempt to ameliorate too-big-to-fail problems could limit their global competitiveness and provide them with incentives to produce their financial services offshore where such limits are not operative. Moreover, banks’ strategies to avoid restrictions on scale, such as moving such activities into the lessregulated non-bank sector, may create new sources of systemic risk that are harder to supervise and regulate. Performance studies based on structural models of managerial utility maximization, as well as those based on non-structural models of bank production, have incorporated variables designed to capture incentive conflicts between managers and outside stakeholders. These studies have shown that factors associated with enhanced market discipline are also associated with improved bank performance and that improved bank performance is not necessarily associated with improved financial stability when the improved performance results from investment strategies that increase financial leverage and heighten credit risk. In short, the incentive of larger banks to take extra risk to exploit the federal safety net and increase their expected market value may undermine financial stability. These results suggest an important role for capital regulation and enhanced supervision of large financial institutions.

Acknowledgments The authors thank the editors Allen Berger, Phillip Molyneux, and John Wilson for helpful comments. The views expressed in this chapter are those of the authors and do not necessarily reflect those of the Federal Reserve Bank of Cleveland or of the Federal Reserve System.

References Adams, R. B. and Santos, J. A. C. (2006). “Identifying the Effect of Managerial Control on Firm Performance,” Journal of Accounting and Economics, 41, 55–85. Aghion, P., Alesina, A., and Trebbi, F. (2007). “Democracy, Technology, and Growth,” Working Paper, Department of Economics, Harvard University, May.

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The Performance of Financial Institutions   257 Ahmed, J. I., Anderson, C., and Zarutskie, R. E. (2015). “Are the Borrowing Costs of Large Financial Firms Unusual?” Finance and Economics Discussion Series 2015–024. Washington: Board of Governors of the Federal Reserve System, available at: http://dx.doi.org/10.17016/ FEDS.2015.024. Altunbas, Y., Evans, L., and Molyneux, P. (2001). “Bank Ownership and Efficiency,” Journal of Money, Credit, and Banking, 33, 926–54. Assaf, A., Berger, A. N., Roman, R. A., and Tsionas, M. (2018). “Does Efficiency Help Banks Survive and Thrive During Financial Crises?” Working Paper. Baele, L., De Jonghe, O., and Vander Vennet, R. (2006). “Does the Stock Market Value Bank Diversification?” Working Paper No. 2006/402, August, Department of Financial Economics, Ghent University. Berger, A. N. (2007). “International Comparisons of Banking Efficiency,” Financial Markets, Institutions and Instruments, 16, 119–44. Berger, A. N. and Hannan, T. H. (1998). “The Efficiency Cost of Market Power in the Banking Industry: A Test of the ‘Quiet Life’ and Related Hypotheses,” Review of Economics and Statistics, 80, 454–65. Berger, A. N. and Humphrey, D. B. (1997). “Efficiency of Financial Institutions: International Survey and Directions for Future Research,” European Journal of Operational Research, 98, 175–212. Berger, A. N. and Mester, L. J. (1997). “Inside the Black Box: What Explains Differences in the Efficiencies of Financial Institutions,” Journal of Banking and Finance, 21, 895–947. Berger, A. N. and Mester, L. J. (2003). “Explaining the Dramatic Changes in Performance of US Banks: Technical Change, Deregulation, and Dynamic Changes in Competition,” Journal of Financial Intermediation, 12, 57–95. Berger, P. G. and Ofek, E. (1995). “Diversification’s Effect on Firm Value,” Journal of Financial Economics, 37, 39–65. Berlin, M. and Mester, L. J. (1999). “Deposits and Relationship Lending,” Review of Financial Studies, 12, 579–607. Bhattacharya, S. and Thakor, A. (1993). “Contemporary Banking Theory,” Journal of Financial Intermediation, 3, 2–50. Bos, J. W. B., Heid, F., Koetter, M., Kolari, J. W., and Kool, C. J. M. (2005). “Inefficient or Just Different? Effects of Heterogeneity on Bank Efficiency Scores,” Deutsche Bundesbank Discussion Paper No. 2. Bossone, B. and Lee, J.-K. (2004). “In Finance, Size Matters: The ‘Systemic Scale Economies’ Hypothesis,” IMF Staff Papers, 51:1. Brook, Y., Hendershott, R., and Lee, D. (1998). “The Gains from Takeover Deregulation: Evidence from the End of Interstate Banking Restrictions,” Journal of Finance, 53, 2185–204. Calomiris, C.  W. and Kahn, C.  M. (1991). “The Role of Demandable Debt in Structuring Optimal Banking Arrangements,” American Economic Review, 70, 312–26. Calomiris, C.  W. and Nissim, D. (2007). “Activity-Based Valuation of Bank Holding Companies,” Working Paper No. 12918, National Bureau of Economic Research. Caprio, G., Laeven, L., and Levine, R. (2003). “Governance and Bank Valuation,” Working Paper No. 10158, National Bureau of Economic Research. Cetorelli, N., Jacobides, M. G., and Stern, S. (2017). “Transformation of Corporate Scope in US Banks: Patterns and Performance Implications,” Staff Report No. 813, Federal Reserve Bank of New York, May.

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258   Activities and Performance Cheng, I.-H., Hong, H., and Scheinkman, J. A. (2015). “Yesterday’s Heroes: Compensation and Risk at Financial Firms,” Journal of Finance, 70, 839–79. Clark, J. (1996). “Economic Cost, Scale Efficiency and Competitive Viability in Banking,” Journal of Money, Credit, and Banking, 28, 342–64. Davies, R. and Tracey, B. (2014). “Too Big to be Efficient? The Impact of Too-Big-to-Fail Factors on Scale Economies for Banks,” Journal of Money, Credit, and Banking, 46, 219–53. De Jonghe, O. and Vander Vennet, R. (2005). “Competition versus Agency Costs: An Analysis of Charter Values in European Banking,” Working Paper, Ghent University. Demirgüç-Kunt, A., Kane, E. J., and Laeven, L. (2007). “Determinants of Deposit-Insurance Adoption and Design,” NBER Working Paper No. 12862, January. Demsetz, R.  S. and Strahan, P.  E. (1997). “Diversification, Size, and Risk at Bank Holding Companies,” Journal of Money, Credit, and Banking, 29, 300–13. DeYoung, R. E., Hughes, J. P., and Moon, C.-G. (2001). “Efficient Risk-taking and Regulatory Covenant Enforcement in a Deregulated Banking Industry,” Journal of Economics and Business, 53, 255–82. DeYoung, R., Spong, K., and Sullivan, R. J. (2001). “Who’s Minding the Store? Motivating and Monitoring Hired Managers at Small, Closely Held Commercial Banks,” Journal of Banking and Finance, 25, 1209–43. Dijkstra, M.  A. (2017). Economies of Scale and Scope in Banking: Effects of Government Intervention, Corporate Strategy and Market Power (Amsterdam: Amsterdam University Press). Egan, M., Lewellen, S., and Sunderam, A. (2017). “The Cross Section of Bank Value,” NBER Working Paper No. 23291. Evanoff, D. D. (1998). “Assessing the Impact of Regulation on Bank Cost Efficiency,” Economic Perspectives, Federal Reserve Bank of Chicago, 22, 21–32. Evanoff, D. D., Israilevich, P. R., and Merris, R. C. (1990). “Relative Price Efficiency, Technical Change, and Scale Economies for Large Commercial Banks,” Journal of Regulatory Economics, 2, 281–98. Federal Deposit Insurance Corporation (2014). “TBTF Subsidy for Large Banks—Literature Review (updated),” prepared for Thomas Hoenig, Vice Chair, Federal Deposit Insurance Corporation. Feng, G. and Serletis, A. (2010). “Efficiency, Technical Change, and Returns to Scale in Large US Banks: Panel Data Evidence from an Output Distance Function Satisfying Theoretical Regularity,” Journal of Banking and Finance, 34, 127–38. Fiordelisi, F. (2007). “Shareholder Value Efficiency in European Banking,” Journal of Banking and Finance, 31, 2151–71. Fiordelisi, F., Marques-Ibanez, D., and Molyneux, P. (2011). “Efficiency and Risk in European Banking,” Journal of Banking and Finance, 35, 1315–26. Fisher, R. and Rosenblum, H. (2012). “How Huge Banks Threaten the Economy,” Wall Street Journal, April 4. Flannery, M.  J. (1994). “Debt Maturity and the Deadweight Cost of Leverage: Optimally Financing Banking Firms,” American Economic Review, 84, 320–31. Greenspan, A. (2010). “The Crisis,” Brookings Papers on Economic Activity, Spring, 201–46. Habib, M. A. and Ljungqvist, A. (2005). “Firm Value and Managerial Incentives: A Stochastic Frontier Approach,” Journal of Business, 78, 2053–93. Hancock, D. (1985). “The Financial Firm: Production with Monetary and Nonmonetary Goods,” Journal of Political Economy, 93, 859–80.

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The Performance of Financial Institutions   259 Hancock, D. (1986). “A Model of the Financial Firm with Imperfect Asset and Deposit Liabilities,” Journal of Banking and Finance, 10, 37–54. Herring, R. J. and Vankudre, P. (1987). “Growth Opportunities and Risk-taking by Financial Intermediaries,” Journal of Finance, 42, 583–99. Hoenig, T. M. and Morris, C. S. (2012). “Restructuring the Banking System to Improve Safety and Soundness,” manuscript, Federal Deposit Insurance Corporation. Hughes, J. P. (1999). “Incorporating Risk into the Analysis of Production, Presidential Address to the Atlantic Economic Society,” Atlantic Economic Journal, 27, 1–23. Hughes, J. P. and Mester, L. J. (1993). “A Quality and Risk-Adjusted Cost Function for Banks: Evidence on the ‘Too-Big-to-Fail’ Doctrine,” Journal of Productivity Analysis, 4, 293–315. Hughes, J. P. and Mester, L. J. (1998). “Bank Capitalization and Cost: Evidence of Scale Economies in Risk Management and Signaling,” Review of Economics and Statistics, 80, 314–25. Hughes, J. P. and Mester, L. J. (2013a). “A Primer on Market Discipline and Governance of Financial Institutions for those in a State of Shocked Disbelief,” in F.  Pasiouras (ed.), Efficiency and Productivity Growth: Modelling in the Financial Services Industry (Chichester: John Wiley and Sons), 19–47. Hughes, J.  P. and Mester, L.  J. (2013b). “Who Said Large Banks don’t Experience Scale Economies? Evidence from a Risk–Return-driven Cost Function,” Journal of Financial Intermediation, 22, 559–85. Hughes, J. P. and Moon, C.-G. (2003). “Estimating Managers’ Utility-Maximizing Demand for Agency Goods,” Working Paper No. 2003–24, Department of Economics, Rutgers University. Hughes, J.  P. and Moon, C.-G. (2018). “How Bad is a Bad Loan? Distinguishing Inherent Credit Risk from Inefficient Lending (Does the Capital Market Price this Difference?),” Department of Economics, Rutgers University, Working Paper No. 201802. Hughes, J. P., Jagtiani, J., Mester, L. J., and Moon, C.-G. (2018). “Does Scale Matter in Community Bank Performance? Evidence Obtained by Applying Several New Measures of Performance,” Working Paper No. 18–11, Federal Reserve Bank of Philadelphia, March. Hughes, J.  P., Lang, W., Mester, L.  J., and Moon, C.-G. (1996). “Efficient Banking Under Interstate Branching,” Journal of Money, Credit, and Banking, 28, 1045–71. Hughes, J. P., Lang, W., Mester, L. J., and Moon, C.-G. (1999). “The Dollars and Sense of Bank Consolidation,” Journal of Banking and Finance, 23, 291–324. Hughes, J. P., Lang, W., Mester, L. J., and Moon, C.-G. (2000). “Recovering Risky Technologies Using the Almost Ideal Demand System: An Application to US Banking,” Journal of Financial Services Research, 18, 5–27. Hughes, J. P., Lang, W., Mester, L. J., Moon, C.-G., and Pagano, M. (2003). “Do Bankers Sacrifice Value to Build Empires? Managerial Incentives, Industry Consolidation, and Financial Performance,” Journal of Banking and Finance, 27, 417–47. Hughes, J.  P., Lang, W., Moon, C.-G., and Pagano, M. (1997). “Measuring the Efficiency of Capital Allocation in Commercial Banking,” Working Paper No. 98–2, Federal Reserve Bank of Philadelphia (revised as Working Paper No. 2004–1, Rutgers University Economics Department). Hughes, J. P., Mester, L. J., and Moon, C.-G. (2001). “Are Scale Economies in Banking Elusive or Illusive? Evidence Obtained by Incorporating Capital Structure and Risk-Taking into Models of Bank Production,” Journal of Banking and Finance, 25, 2169–208. Hughes, J. P., Mester, L. J., and Moon, C.-G. (2016). “The Two Faces of Equity Capital in US Commercial Banking: Market Discipline Working For and Against Financial Stability,” Department of Economics, Rutgers University, Working Paper No. 201611.

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260   Activities and Performance Jensen, M. C. and Meckling, W. H. (1976). “Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure,” Journal of Financial Economics, 5, 305–60. Jensen, M. C. and Meckling, W. H. (1979). “Rights and Production Functions: An Application to Labor-Managed Firms and Codetermination,” Journal of Business, 52, 469–506. Keeley, M.  C. (1990). “Deposit Insurance, Risk, and Market Power in Banking,” American Economic Review, 80, 1183–200. Klein, P. G. and Saidenberg, M. R. (2010). “Organizational Structure and the Diversification Discount: Evidence from Commercial Banking,” Journal of Industrial Economics, 58, 127–55. Koetter, M. (2006). “The Stability of Efficiency Rankings when Risk-Preferences and Objectives are Different,” Discussion Paper 08/2006, Series 2: Banking and Financial Studies, Deutsche Bundesbank. Kohn, M. (2004). Financial Institutions and Markets (Oxford: Oxford University Press). Kovner, A., Vickery, J., and Zhou, L. (2014). “Do Big Banks have Lower Operating Costs?” Economic Policy Review, Federal Reserve Bank of New York, December, 1–27. Kroszner, R. (2016). “A Review of Bank Funding Cost Differentials,” Journal of Financial Services Research, 49, 151–74. Laeven, L. and Levine, R. (2009). “Bank Governance, Regulation, and Risk-Taking,” Journal of Financial Economics, 93, 259–75. La Porta, R., Lopez-de-Silanes, F., and Shleifer, A. (2002). “Government Ownership of Banks,” Journal of Finance, 57, 265–301. Leibenstein, H. (1966). “Allocative Efficiency vs. ‘X-efficiency,’” American Economic Review, 56, 392–415. Marcus, A. J. (1984). “Deregulation and Bank Financial Policy,” Journal of Banking and Finance, 8, 557–65. McAllister, P. H. and McManus, D. (1993). “Resolving the Scale Efficiency Puzzle in Banking,” Journal of Banking and Finance, 17, 389–406. Mester, L.  J. (1991). “Agency Costs Among Savings and Loans,” Journal of Financial Intermediation, 1, 257–78. Mester, L.  J. (1992). “Traditional and Nontraditional Banking: An Information-Theoretic Approach,” Journal of Banking and Finance, 16, 545–66. Mester, L.  J. (1993). “Efficiency in the Savings and Loan Industry,” Journal of Banking and Finance, 17, 267–86. Mester, L. J. (1996). “A Study of Bank Efficiency Taking into Account Risk-Preferences,” Journal of Banking and Finance, 20, 1025–45. Mester, L.  J. (1997). “Measuring Efficiency at US Banks: Accounting for Heterogeneity is Important,” European Journal of Operational Research, 98, 230–42. Mester, L. J. (2007). “Some Thoughts on the Evolution of the Banking System and the Process of Financial Intermediation,” Federal Reserve Bank of Atlanta, First and Second Quarters, Economic Review, 67–75. Mester, L.  J. (2008). “Optimal Industrial Structure in Banking,” in A.  Boot and A.  Thakor (eds.), Handbook of Financial Intermediation and Banking (Amsterdam: North-Holland/ Elsevier), 133–62. Mester, L.  J., Nakamura, L.  I., and Renault, M. (2007). “Transactions Accounts and Loan Monitoring,” Review of Financial Studies, 20, 529–56. Minton, B. A., Stulz, R. M., and Taboada, A. G. (2017). “Are Larger Banks Valued More Highly?” Fisher College of Business Working Paper Series, The Ohio State University, WP 2017–08.

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The Performance of Financial Institutions   261 Morck, R., Shleifer, A., and Vishny, R.  W. (1988). “Management Ownership and Market Valuation: An Empirical Analysis,” Journal of Financial Economics, 20, 293–315. Powell, J.  H. (2013). “Ending ‘Too Big to Fail,’ ” Remarks at the Institute of International Bankers, Washington Conference, Washington, DC. Saunders, A. and Cornett, M. (2010). Financial Institutions Management: A Risk Management Approach (New York: McGraw-Hill Higher Education). Schmid, M. and Walter, I. (2014). “Firm Structure in Banking and Finance: Is Broader Better?” Journal of Financial Perspectives, 2, 65–75. Sealey, C. W. and Lindley, J. T. (1977). “Inputs, Outputs, and a Theory of Production and Cost at Depository Financial Institutions,” Journal of Finance, 32, 1251–66. Tarullo, D.  K. (2011). “Industrial Organization and Systemic Risk: An Agenda for Further Research,” Remarks at the Conference on the Regulation of Systemic Risk, Federal Reserve Board, Washington, DC. Wheelock, D. and Wilson, P. (2012). “Do Large Banks Have Lower Costs? New Estimates of Returns to Scale for US Banks,” Journal of Money, Credit, and Banking, 44, 171–99. Wheelock, D. and Wilson, P. (2017). “The Evolution of Scale Economies in US Banking,” Working Paper No. 2015-021C, Federal Reserve Bank of St. Louis.

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chapter 9

Tech nol ogica l Ch a nge a n d Fi na nci a l I n novation i n Ba n k i ng Some Implications for FinTech W. Scott Frame, Larry Wall, and Lawrence J. White

9.1 Introduction Financial intermediation has changed dramatically over the past thirty years, due in  large part to technological change arising from advances in telecommunications, information technology, and financial practice. This technological progress has spurred financial innovations that have altered many financial products, services, production processes, and organizational structures. To the extent that such financial innovations reduce costs or risks, social welfare may be improved. Of course, many financial innovations fail owing to fundamental design flaws or simply being replaced by better alternatives. A good example of technological change that has been dramatically reshaping the financial services industry is the ongoing shift from relying on human judgment to automated analysis of consumer data. This has taken what had been largely local markets for banking services and opened them up to nationwide competition from other banks and non-bank financial institutions. For example, retail loan applications are now routinely evaluated using credit-scoring tools built using comprehensive historical credit registry databases. This automated approach eliminates the need to have a local presence to make a loan and substantially reduces underwriting and compliance costs for lenders, and the resulting data can be leveraged to improve further their risk measurement and management. Such a reliance on hard information also makes underwriting transparent to third parties and hence facilitates secondary markets for retail loans

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Technological Change and Financial Innovation in Banking   263 through securitization, which allows non-bank firms that lack deposit funding to compete via capital market financing. Given the growing importance of technology to financial services, it is perhaps not too surprising that the latest trend has been for technology-based firms to offer financial services, a development that is often called “FinTech.” Many FinTech firms combine automated analysis of retail customers with more user-friendly interfaces to provide services that are more convenient, and sometimes a at lower cost, to consumers. For example, “marketplace lending” platforms have emerged as a new organizational form that attracts borrowers with a simplified loan application process, leverages credit scoring tools to analyze these applications, and then matches creditworthy borrowers directly to investors. Furthermore, in some jurisdictions, machine learning (artificial intelligence) is now being leveraged to further improve retail loan risk measurement. Another set of recent technological developments is being touted as having the potential to have an even more fundamental impact on the financial system, potentially eliminating the need for trusted third parties such as banks. Whether, and to what extent, blockchains and cryptocurrencies will disrupt the existing financial system remains to be seen, as the technology is too new and immature to draw firm conclusions. However, the potential benefits of cryptocurrencies and blockchain technology are sufficient to attract considerable interest from tech-knowledgeable individuals, large financial organizations, and even major governments. This chapter surveys the research literature pertaining to several specific financial innovations that have appeared in recent decades that were specifically driven by technological change. Particular attention is paid to innovations that may provide insights into the prospects for certain widely discussed FinTech applications. To set the stage, we begin by providing some additional clarity about what is meant by financial innovation.

9.2  Financial Innovation: Definition and Determinants As described by Merton (1992, p. 12), the primary function of a financial system is to facilitate the allocation and deployment of economic resources—both spatially and across time—in an uncertain environment. This function encompasses a payments system with a medium of exchange; the transfer of resources from savers to borrowers; the gathering of savings for pure time transformation; and the reduction of risk through insurance and diversification. The operation of a financial system involves real resources employed by financial intermediaries, and a large share of these resources is expended in the data collection and analyses to deal with problems of asymmetric information. There are also uncertainties about future states of the world that generate risks that represent costs to risk-averse individuals.

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264   Activities and Performance Hence, new or improved financial (i) production processes, (ii) products and services, and (iii) organizational structures that can better satisfy financial system participants’ demand and reduce costs and risk processes, should generally be welcomed. Viewed in this context, Frame and White (2004) define a financial innovation as “something new that reduces costs, reduces risks, or provides an improved product/service/instrument that better satisfies financial system participants’ demands.” Importantly, Tufano (2003) emphasizes that financial innovation includes the process of both invention (the ongoing research and development function) and diffusion (or adoption) of new products, services, or ideas. The centrality of finance in an economy, and its importance for economic growth, naturally raises the significance of financial innovations (and their diffusion).1 Finance facilitates virtually all production activity and much consumption activity; and so improvements in the financial sector can have direct positive implications for an economy. Moreover, an improved financial sector can encourage more and better saving and investment decisions, making financial innovation even more valuable for an economy. This positive view of financial innovation has been discussed in a number of articles, including: Van Horne (1985), Miller (1986, 1992), Merton (1992, 1995), Berger (2003), Tufano (2003), and Frame and White (2004). However, the recent global financial crisis has led some observers to cast doubt on the usefulness of most financial innovation— seeing such activity as being largely associated with financial malpractice and instability (e.g., Krugman, 2007; Volcker, 2009).2 This negative view focuses on the “dark side” of financial innovation, which some view as the root cause of the Global Financial Crisis of the late 2000s. While such a re-evaluation is natural in light of the crisis, it is important to recognize that not every financial innovation will be welfare-enhancing or successful. Innovation involves trial and error, and failures can be costly—especially for widely diffused innovations (e.g., Lerner and Tufano, 2011). So, financial innovation should more accurately be viewed as likely being beneficial “on net.” Consistent with these conjectures, Beck et al. (2016) conduct a cross-country analysis and find that financial innovation is associated with higher (but more volatile) economic growth and with greater bank fragility. Campbell (1988) offers four environmental conditions that are conducive to financial innovation: The first relates to underlying technologies and the ability of their improvement to increase efficiency. For example, the information technology revolution has facilitated the creation and use of “big data” and applied statistics for financial risk 1  See Levine (1997) for an extensive discussion of the relationship between financial development and economic growth in the context of the theoretical and empirical literature at that time. For subsequent empirical evidence, see Levine (1998, 1999); Levine and Zervos (1998); Beck, Levine, and Loayza (2000); Levine, Loayza, and Beck (2000); Arestis, Demetriades, and Luintel (2001); Beck and Levine (2004). 2  Thakor (2012) and Gennaioli, Shleifer, and Vishny (2012) are recent examples of theoretical research that attempts to tie financial innovation and financial instability. Both provide models where banks innovate by making new loans or creating new securities; but then altered information or beliefs results in runs or panics. Henderson and Pearson (2011) provide a recent empirical analysis of a welfare-reducing financial innovation.

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Technological Change and Financial Innovation in Banking   265 measurement and management; and machine learning is now used to leverage the data further. A second condition is an unstable macroeconomic environment, as the concomitant fluctuating asset prices are likely to spur risk-transfer innovations. A third condition is regulation, which can inhibit some innovations and encourage others (often as a mechanism to avoid regulation). Finally, taxes can spur financial innovations to the extent that they create incentives to repackage (or re-label) specific income streams so as to reduce tax liability. Over the past thirty years, each of these environmental conditions was markedly altered and resulted in substantial changes to the practice of financial intermediation. The remainder of this chapter focuses mostly on Campbell’s first environmental condition: The role of technological change in driving financial innovation.

9.3  Process Innovation The past thirty years have witnessed important changes in financial institution production processes. The use of electronic transmission of bank-to-bank retail payments, which had modest beginnings in the 1970s, has exploded owing to greater retail acceptance, online banking, and check conversion. In terms of intermediation, credit bureau data have been used to create credit scores that increasingly substitute for manual underwriting—and this has been extended even into historically relationship-oriented products, such as small business loans. This trend toward hardening information has facilitated deep secondary consumer loan markets in the United States and has provided key inputs for risk management systems. Recently, the advent of blockchain/distributed ledger technology and significant advances in artificial intelligence/machine learning has raised important questions about the future of financial intermediation. We discuss each of these topics below.

9.3.1  Research Evidence from Past Process Innovations Automated Clearinghouse. An automated clearinghouse (ACH) is an electronic funds transfer network that connects banks and is primarily used for recurring, small-dollar payments. While several ACH networks emerged in the 1970s, volumes grew only modestly through the 1980s, with the networks’ being used almost exclusively for direct payroll deposits. Over the past twenty years, however, consolidation has occurred, and volumes have soared. According to the National Automated Clearing House Association, in 2015 there were some 24 billion ACH payments totaling $41 trillion. The modest literature on ACH networks has focused on the Federal Reserve’s ACH pricing policies. On the supply-side, Bauer and Hancock (1995) estimate a cost function and find that over the 1979–94 period the cost of processing an ACH item fell

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266   Activities and Performance dramatically—owing to scale economies, technological change, and lower input prices.3 Stavins and Bauer (1999), on the other hand, estimated ACH demand elasticities by exploiting FedACH price changes over time—finding ACH demand to be highly inelastic. More recently, two papers studied network externalities for ACH. Gowrisankaran and Stavins (2004) find support for significant network externalities, which they ascribe to technological advancement, peer-group effects, economies of scale, and market power. Ackerberg and Gowrisankaran (2006) identify large fixed costs of bank adoption as the barrier to greater use of ACH transactions and thus to society’s capturing the accompanying potential cost savings. Small Business Credit Scoring. Banks use a number of different approaches to lending to informationally opaque small businesses (Berger and Udell, 2006). One method that was introduced in the 1990s and continues to evolve is small business credit scoring (SBCS). This screening technology involves analyzing consumer data about the owner of the firm and combining it with relatively limited data about the firm itself, using statistical methods to predict future credit performance. Credit scores had long been pervasive in consumer credit markets (e.g., mortgages, credit cards, and automobile loans)—and resulted in widely available, low-cost, commoditized credits that are often packaged and sold into secondary markets. The empirical literature that has studied SBCS has focused on the determinants of bank adoption and diffusion of this technology, as well as on how SBCS has affected credit availability. Two studies have statistically examined the determinants of the probability and timing of large US banks’ adoption of SBCS. Both Frame, Srinivasan, and Woosley (2001) and Akhavein, Frame, and White (2005) find an important role for size and organizational structure in the adoption decision: Larger banking organizations with fewer bank charters and more bank branches were not only more likely to adopt, but also to adopt sooner. This suggests that large banks with a more “centralized” structure were more likely to adopt SBCS. More recent research suggests, however, that the use of credit scores for small business lending has subsequently diffused to small banks (Berger, Cowan, and Frame, 2007) and community development organizations (Fracassi et al., 2016). Several studies have focused on the relationship between SBCS adoption and credit availability. Three studies documented increases in the quantity of lending (Frame, Srinivasan, and Woosley, 2001; Frame, Padhi, and Woosley, 2004; Berger, Frame, and Miller,  2005). One found evidence that is consistent with more lending to relatively opaque, risky borrowers (Berger, Frame, and Miller, 2005); another with increased lending within low-income as well as high-income areas (Frame, Padhi, and Woosley, 2004); and another with lending over greater distances (DeYoung et al., 2011). In instances in which SBCS is used in conjunction with traditional underwriting methods to reduce information asymmetries, it is also shown to result in increased loan maturity (Berger et al., 2005) and reduced collateral requirements (Berger et al., 2011). 3  Using a much smaller sample, Bauer and Ferrier (1996) also found support for the existence of ACH scale economies as well as significant allocative inefficiencies.

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Technological Change and Financial Innovation in Banking   267 A continuing puzzle with respect to SBCS is why a secondary market for securitized small business loans has not developed in the way that credit scoring for consumer loans led to securitization of those credits.

9.3.2  FinTech Process Innovations Blockchain/Distributed Ledgers. One new production process that is being touted as potentially revolutionizing banking (as well as other areas of finance and even broader areas of databases and contracts generally) is the blockchain and related technologies. Interest in blockchain technology was sparked by a white paper by Nakamoto (2008), which developed peer-to-peer “electronic cash” using blockchain technology that allowed electronic payments to be made without going through a financial intermediary. Nakamoto’s paper has sparked a variety of innovative initiatives. Some of these are intended to replace financial institutions, including commercial banks and even central banks. Other initiatives have more modest goals, such as improving the efficiency of existing financial intermediation. Blockchains are an example of a distributed ledger, or a database that is shared across nodes in a network. In a blockchain, data are added to the ledger in blocks that are ordered by time and linked to each other using cryptology.4 Blockchain technology is highly resistant to efforts to tamper with prior records in the database. Bitcoin, along with similar cryptocurrencies, uses blockchains to record ownership of a token (cryptocurrency) that its users value as a store of wealth and form of payment. In principle, these tokens could represent ownership of any asset, including physical assets such as gold or sovereign-issued fiat currency such as the US dollar. However, almost all cryptocurrencies are simply electronic tokens on a blockchain and do not represent a claim to any external asset. Distributed ledger technology is potentially useful wherever two or more parties need to share a common understanding about current conditions—such as who owns a particular asset or the terms of a financial contract to which they are both parties. Blockchains’ potential for disrupting existing financial intermediaries arises from their ability to provide tamper-resistant records—indeed some claim the records are immutable. Catalini and Gans (2017) observe that an immutable record would facilitate costless verification and thereby facilitate new markets. In essence, the blockchain would substitute for the “trusted-third-party” role that large payment intermediaries currently serve, and for which they often charge fees that—to casual observers and blockchain enthusiasts—seem relatively high. However, Cong and He (2018) note that blockchains 4  The blockchain does this by creating a “cryptographic hash,” or unique digital summary, for each block that includes the hash from the prior block. If any change is made to any given block, it will alter that block’s hash and the change will carry through to every block that is subsequently added to the blockchain. (This occurs because the prior block’s hash is part of each block in the chain.) Thus, if one wants to rewrite the history of one block, then every subsequent block will have to be revised. Otherwise, anyone seeking to verify the blockchain will be able tell that an effort has been made to change one of the blocks.

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268   Activities and Performance could also be used to facilitate collusion. In addition, instead of trusting the “trusted-third party,” users must trust the technology and the developer of the technology. Unlike ACH, distributed ledgers do not necessarily benefit from network effects or exhibit economies of scale. The central concern—but also the potential source of disruption, as we discussed above—is how to determine which transactions are valid when there is no trusted central party to verify their authenticity. The solution adopted by some distributed ledgers is to limit the set of participants to a group of firms that have some trust in each other and some capital at risk if they are caught making invalid entries to the ledger, the so-called private, permissioned blockchains. Other distributed ledgers, especially the permissionless public blockchains, see openness to participation by any interested party as a key virtue. These blockchains benefit from network effects in that more people using the blockchain for more purposes increases the potential uses for all of the users. On the other hand, the very openness of these blockchains means that they must adopt measures that raise the cost of trying to change existing records. The way this is done by some blockchains, such as Bitcoin, has the effect of imposing limits on the number of transactions that may be made on that blockchain—that is, imposing infinite diseconomies of scale beyond some transactions volume. Machine Learning. The increasing capability of artificial intelligence (AI) and machine learning (ML) is another important technological advance affecting banking in recent years. Although there are not universal definitions of AI and ML, for current purposes AI can be defined as the development of computer systems to perform tasks that ordinarily require human intelligence. This definition incorporates expert systems—where humans teach machines—and also machine learning, where the machines learn from data. Interest in ML in particular has become increasingly popular, due to a combination of more digitized data, faster computers, and better algorithms to analyze data. ML is similar to statistics in that both seek to learn from the data and use many of the same tools, and the two disciplines are increasingly learning from each other. The biggest difference is that statistics has historically emphasized hypothesis testing and statistical inference, whereas ML emphasizes obtaining the best prediction. As a result, ML is not guided by economic (or other social sciences) theory (which would generate the hypotheses for statistical testing), which has the advantage that ML sometimes identifies relationships that are not (currently) predicted by theory. The disadvantage is that some of the relationships ML identifies will not be causal and, hence, may not be able to be usefully exploited. AI and ML are general-purpose technologies that may be used in a wide variety of areas within a financial institution. These include refinements to existing products, such as better credit and risk management, tools for uncovering asset pricing anomalies, and helping institutions comply with regulatory requirements—this is a related field called “RegTech.” However, AI and ML are also essential inputs into the creation of a variety of new financial services. At the consumer level, AI and ML are being used in personal financial management products that analyze an individual’s expenses and revenues to provide recommendations that help users obtain their financial goals. Another new product that relies on AI and ML is a “robo-advisor,” which provides automated personalized

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Technological Change and Financial Innovation in Banking   269 investment advice and, with the customer’s agreement, automated portfolio selection and rebalancing based on each investor’s goals, financial assets, and risk tolerance. Machine learning algorithms generally benefit from access to large amounts of high quality data that are pertinent to the question they are addressing. According to Wall (2018c), firms that are able to assemble such datasets may have a competitive advantage that can be leveraged to increase their market shares and build even larger datasets. The author notes that one way of reducing this advantage is through the sharing of data across firms—provided that the sharing satisfies appropriate privacy concerns. Another way of reducing the advantage would be for governments to take the position that consumers own—that is, have property rights with respect to—their own data and have the right to share it as they choose, as is currently being done in the European Union under Payments Systems Directive 2 (sometimes called PSD2). Although there is extensive academic literature in computer science on AI and ML algorithms and a growing body of literature on their application to finance, the academic literature on their application to new bank products, such as personal financial management and robo-advising, is not very well developed. The banking application that has received the most academic attention is credit analysis, which is discussed later in this chapter in the context of marketplace lending.

9.4  Product Innovation The increased reliance on hard information for lending decisions over time has improved credit market efficiency, as evidenced by greater use of risk-based pricing and expanded credit availability to marginal borrowers. However, the US subprime mortgage crisis raised questions about the efficacy of this approach, as a staggering number of such borrowers defaulted on their home mortgages and lost their homes. The secular decline in the cost and quality of computing resources in recent decades, coupled with the Internet, resulted in substantial improvement in payment system efficiency. Most recently, blockchain and distributed ledger technology appears to have the potential to disrupt payments further through cryptocurrencies and initial coin offerings.

9.4.1  Research Evidence from Past Product Innovations Subprime Lending. Subprime lending to US households has become mainstream over the past few decades. As a general matter, these are loans to borrowers with weak credit histories and limited down payments available for financing homes and automobiles. Historically, such borrowers had been rationed out of fixed-price loan markets and were hence credit-constrained. However, the availability of large historical performance databases has allowed for the development of statistical models that improve risk measurement and facilitate risk-based loan pricing. Subprime lending has the potential

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270   Activities and Performance benefit of expanding access to credit to potentially creditworthy borrowers who had previously been denied credit. However, it also raises the question about whether subprime borrowers are using expanded access wisely; and also whether the lenders are properly pricing and managing the increased risk exposure. The recent US mortgage crisis highlighted the personal and social costs associated with subprime lending in the face of a macroeconomic shock. Before discussing subprime mortgage lending in depth, we note some key recent empirical studies of subprime automobile and credit card lending. Two papers study the US subprime auto loan market using loan-level data from a single institution. Evidence that expanded access to credit may be valuable comes from Adams, Einav, and Levin (2009), who find that subprime auto loan demand is highly sensitive to down payment requirements and rises sharply during tax rebate season—consistent with the presence of credit constraints. Evidence that lenders are managing this risk may be found in their response to risk factors. Auto loan default rates are found to increase in loan size, and riskier borrowers demand larger loans; but lenders are found to limit loan sizes and use credit scores to price risk-based borrowers in an effort to reduce moral hazard. Evidence that borrowers may not be using the credit wisely is found in a closely related paper by Einav, Jenkins, and Levin (2012). Using the same data as Adams, Einav, and Levin, they show how car prices have little effect on borrower purchase or down payment decisions, but rather simply translate into larger loans. For the lender, down payment requirements create a tradeoff between loan volume and quality that is managed using credit scores to risk-base the pricing of these loans. Additional evidence that borrowers may not be using their expanded access wisely may be found from a study of subprime credit card lending by Alan and Loranth (2013). They study borrower price sensitivity using a randomized interest rate experiment for existing loans. The authors find that for a large increase in interest rates (five percentage points), overall credit demand declines only modestly for their sample. These results reflect substantial heterogeneity as the lowest-risk borrowers reduce credit demand significantly, while the highest-risk borrowers do not.5 As for the subprime mortgage market: The boom in subprime mortgage lending demonstrates the extent to which borrowers were taking advantage of the expanded access. During that time, the US subprime mortgage market grew rapidly and averaged about 20 percent of residential mortgage originations between 2004 and 2006. This credit boom facilitated an expansion in the pool of potential homeowners and helped to lead the US to a record homeownership rate in 2004 of 69.2 percent—even in the face of declining housing affordability in many areas of the country. The number of outstanding subprime mortgages ultimately peaked at $1.2 trillion in 2007, but has declined steadily since the onset of the market meltdown as new loan originations ceased.6 5  This finding is consistent with earlier research by Ausubel (1991) describing the “failure of competition” in the US credit card market. The notion is that the riskiest borrowers have inelastic credit demand owing to liquidity constraints and always intend to use cards to finance purchases. 6  An overview is provided by Gerardi et al. (2008).

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Technological Change and Financial Innovation in Banking   271 Whether borrowers were using their access wisely or were being exploited is the subject of ongoing debate. Some of the early arguments that borrowers were being exploited were based on a comparison of the structure of subprime mortgages versus those taken by prime borrowers. A thirty-year fixed rate loan with an embedded prepayment option is the most common type of residential mortgage in the US. By contrast, the typical subprime mortgage during the housing boom was a thirty-year adjustable rate mortgage (with a fixed rate for the initial two to three years) that included a prepayment penalty. Mayer, Pence, and Sherlund (2009) provide a set of “subprime mortgage facts” through the financial crisis period, including information about various loan contract structures, the degree of underwriting documentation, the presence of second liens, and the borrower occupancy status.7 However, the mere fact that subprime contract terms were different from those on prime mortgages does not mean that subprime borrowers were being exploited. A series of theoretical papers by Piskorski, and Tchistyi (2010, 2011), and Mayer, Piskorski, and Tchistyi (2013) suggest that subprime borrowers benefited from the contract terms that distinguish their mortgages from prime mortgages. Another hypothesis is that reliance on the originate-to-distribute model created a moral hazard problem for loan underwriters (e.g., Ashcraft and Schuermann, 2008). A large fraction of the subprime loans were packaged together and sold as securities, transferring a substantial fraction of the credit risk from underwriters to investors. As a result, underwriters were not sufficiently rigorous in underwriting subprime mortgages. One line of inquiry focuses on the quality of loan-level information provided to investors. For example, Piskorski, Seru, and Witken (2015) provide evidence that there was incomplete information about the presence of subordinate financing (i.e., second liens). Jiang, Nelson, and Vytlacil (2014) and Griffin and Maturana (2016) find that borrowers misrepresented their income and occupancy status, respectively. According to Griffin and Maturana (2016) such data problems led to higher default propensities and loss severities than would have otherwise been the case. However, it is not clear that the deleterious effects were disproportionately borne by outside investors. Papers by Jiang, Nelson, and Vytlacil (2013) and Elul (2016) suggest that securitized and non-securitized subprime loans performed similarly (conditional on observable information) due to investor-required loan seasoning prior to securitization. There is also research that suggests that subprime mortgage lenders were lax in their screening of applicants with FICO credit scores above 620 (Keys et al., 2010; Keys, Seru, and Vig, 2012), although this interpretation has recently come into doubt (Bubb and Kaufman, 2014).8 See Frame (2018) for a review of the literature pertaining to agency conflicts in residential mortgage securitization.

7  Related to documentation, the authors describe the concomitant rise in the so-called Alt-A market, which is characterized by lower observed risk (e.g., better credit scores and larger down payments), but little/no documentation/verification of borrower income/assets. 8  Standard FICO credit scores range from 300 to 850. About 70 percent of US consumers have a score greater than 650. Most financial institutions perceive consumers with FICO scores below 620 as definitely being subprime, although some lenders use slightly higher score cut-offs (e.g., 640) for this definition.

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272   Activities and Performance Another hypothesis is that borrowers and lenders acted rationally, given their expectations for residential real estate price appreciation. That is, the greater risk of distress among subprime borrowers was not a problem so long as house prices continued to appreciate. Distressed borrowers with positive equity could borrow against this equity or simply sell the home and pocket any net proceeds. Hence, negative equity (owing more than the home is worth) is a necessary condition for mortgage default (see, for example, Foote, Gerardi, and Willen, 2008). The problem is that the massive expansion of subprime mortgage lending in the mid-2000s was concurrent with rapid house price appreciation, and both borrowers and lenders began to form unreasonably favorable expectations about future home price growth (e.g., Brueckner, Calem, and Nakamura,  2012). Escalating prices reduced housing affordability, and an assumption of continued future price growth would have made parties more comfortable with extreme leverage as borrowers would be expected to “grow out of it” soon. In this view, the declining underwriting standards likely emanated from the recent and expected growth in home prices, which seemingly masked the heightened risk (Bhardwaj and Sengupta, 2014). Once housing prices stopped appreciating and then started declining, distressed borrowers were unable to sell or remortgage their house, leading to the observed sharp increase in delinquencies and foreclosures. Thus, subprime lending in general has seemingly been successful at expanding credit availability to marginal borrowers. However, that success in residential mortgage lending depended to a very large degree on the factor that was ultimately its downfall: a dependence on expectations of increasing housing prices. This experience is a reminder that it often takes an economic downturn to reveal fully the weaknesses in an innovation. Whether privately financed subprime lending on a smaller scale could have been a successful product absent the boom is unclear. What is clear is that the combination of the scale and scope of the recent crisis, the findings of negligence and malfeasance, the political and legal uncertainty, and the sensitivity to housing displacement among vulnerable populations mean that private subprime mortgage lending is unlikely to return en masse anytime soon.9

9.4.2  Payment Services Recent retail banking service innovations primarily relate to enhanced deposit account access and new methods of payment—each of which better meets consumer demands for convenience and ease. Debit cards, which bundle ATM access with the ability to make payments from a bank account at the point-of-sale, became ubiquitous in the 1990s. In the 2000s, online banking, which allows customers to monitor accounts and originate payments using “electronic bill payment,” became widely used. Notably, 9  Nevertheless, subprime borrowers continue to have broad access to mortgage finance through US Government mortgage insurance programs (through the Federal Housing Administration, the Department of Veterans Affairs, and the Department of Agriculture)—and such loans have been very popular since the onset of the 2007–9 crisis.

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Technological Change and Financial Innovation in Banking   273 besides improving convenience and ease, retail payment innovations may also improve access to the banking system for unbanked consumers (e.g., Gross, Hogarth, and Schmeiser, 2012; Hayashi, 2016). Debit Cards. Debit cards are essentially “pay-now” instruments linked to a checking account whereby transactions can happen either instantaneously using online (PIN-based) methods or in the near future with offline (signature-based) methods. Consumers typically have the choice of using online or offline methods, and their selection often hinges on the respective benefits: Online debit allows the cardholder also to withdraw cash at the point-of-sale, while offline provides float. According to the US Federal Reserve (2016), there were approximately 69.5 billion debit transactions in the US during 2012 that totaled almost $2.6 trillion. Much of the research that pertains to debit cards relates to identifying the most likely users of this payment instrument. Such demand-side explorations have been conducted individually as well as jointly across multiple payment options. Stavins (2001), for example, uses data from the 1998 Survey of Consumer Finances (SCF) and finds that debit usage is positively related to educational attainment, homeownership status, marital status, business ownership, and being a white collar worker; and usage is negatively related to age and net worth. Klee (2006) extends this analysis to consider the 1995, 1998, and 2001 SCFs and reports a secular increase in adoption driven by similar demographic factors.10 Additional US evidence is provided by: Mantel and McHugh (2001), who use survey data from Vantis International; Hayashi and Klee (2003), who use data from a 2001 survey conducted by Dove Consulting; Borzekowski and Kiser (2008) and Borzekowski, Kiser, and Ahmed (2008), who use 2004 data from the Michigan Surveys of Consumers; and Hayashi and Stavins (2012), who use the Federal Reserve Bank of Boston’s Consumer Payment Choice surveys. Some additional analysis by Hayashi and Klee (2003) studied the circumstances under which consumers are likely to use debit cards and found that these are more often used at grocery stores and gas stations than at restaurants. Related to this, the authors also find that debit card usage is positively related to the incidence of self-service transactions. Zinman (2009) finds that the choice of debit cards is positively related to being near credit card balance limits; and Fusaro (2013) shows that debit cards are used to pay-down credit card balances. Finally, Hayashi and Stavins (2012) provide evidence that a recent US law raising the cost of debit card transactions had an especially negative effect on low credit score consumers, who tend to have lower and more volatile incomes and to be less educated. Online Banking. As households and firms rapidly adopted Internet access during the late 1990s, commercial banks established an online presence. According to DeYoung (2005), the first bank websites were launched in 1995; and by 2002 nearly one-half of all US banks and thrifts operated transactional websites. Today virtually all US commercial banks offer transactional websites. 10  See Anguelov, Hilgert, and Hogarth (2004) for the relevant statistics that pertain to these surveys.

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274   Activities and Performance The primary line of research that related to online banking has been aimed at understanding the determinants of bank adoption and how the technology has affected bank performance. In terms of online adoption, Furst, Lang, and Nolle (2002) found that US banks were more likely to offer transactional websites if they were: larger, younger, affiliated with a holding company, located in an urban area, and had higher fixed expenses and non-interest income. Hernandez-Murillo, Llobet, and Fuentes (2010) later confirmed many of these findings using updated data, but also found that online adoption was positively related to county-level demographics (median household income, education, Internet access) and market concentration and was negatively related to additional bank characteristics (branching intensity, ratio of capital-to-total assets, and non-performing loans). Finally, Dow (2007) analyzes data for US credit unions and finds that online banking adoption is related to institution size and having a lower proportion of non-performing loans. On the flip side, Goddard, McKillop, and Wilson (2009) find that credit unions that do not provide transactional websites are more likely to fail and/or be acquired. With respect to online bank performance, DeYoung, Lang, and Nolle (2007) report that Internet adoption improved US community bank profitability—primarily through deposit-related charges. In a related study, Hernando and Nieto (2007) find that, over time, online banking was associated with lower costs and higher profitability for a sample of Spanish banks. Both papers conclude that the Internet channel is a complement to—rather than a substitute for—physical bank branches. Additional evidence is offered by Ciciretti, Hasan, and Zazzara (2009), who also find that Italian banks that offered Internet-related services had higher profitability (and stock returns) relative to their peers. However, a contemporaneous study of US credit unions found no relationship between online banking adoption and profitability, but did find significantly higher operating expenses (Dandapani, Karels, and Lawrence, 2008). Other studies examine the demand-side for online banking services. Mantel (2000) studies the demographic characteristics of users of electronic/online bill payment. Among other things, the author finds that electronic bill payers tend to be: older, female, higher income, and homeowners. Bauer and Hein (2006), who analyze data from the Survey of Consumer Finances, find that younger customers and those with previous experience with remote banking technologies are more likely to use online banking.

9.4.3  FinTech Product Innovations Two specific applications of blockchain technology—cryptocurrencies and initial coin offerings—have garnered the most attention from the public and academics.11 Bitcoin, the oldest and largest blockchain (by market value in July 2018), has been studied from a variety of perspectives. Huberman, Leshno, and Moallemi (2017) observe that no one 11  A potential substitute for cryptocurrency for some uses is government-issued digital currency. Government-issued digital currency could, but need not, use a blockchain for record-keeping. See Chapter 10, this volume, for a discussion of government-issued digital currency.

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Technological Change and Financial Innovation in Banking   275 owns Bitcoin and that the blockchain’s protocol is “almost immutable.” This raises the question of the underlying economics of the system: Specifically, what is the source of the revenue for financing Bitcoin’s operations? The answer is that the equilibrium level of transaction fees and infrastructure level is set by a congestion queuing game arising from limits set by the Bitcoin protocol on the blockchain’s throughput (transactions volume). Budish (2018) analyzes the economics of Bitcoin’s operations in terms of the incentive of infrastructure-providers (called “miners”) to rewrite the blockchain in a way that would allow them to spend the same Bitcoin twice. He notes that Bitcoin has not been subject to such a successful attack through mid-2018 but argues that this is due in part because the size of Bitcoin transactions has been small, limiting the gains from double-spending. Bitcoin and some other cryptocurrencies are being traded against each other and against some sovereign-issued fiat currencies (such as the US dollar), prompting the development of a small amount of literature analyzing the returns, and return volatility, of cryptocurrencies.12 However, most cryptocurrency trading takes place outside the direct supervision of securities regulators and, thus, may be more open to manipulation than are financial instruments that trade on securities and derivatives exchanges. Gandal et al. (2018) analyze pricing data on one of the cryptocurrency exchanges, Mt. Gox, and find that prices rose an average of four percent on days with suspicious trades but were slightly down on days without such trading. Similarly, Griffin and Shams (2018) find evidence consistent with market manipulation. Along with cryptocurrencies, a popular use of blockchain tokens is as a vehicle for obtaining financing for start-up technology firms. Indeed, this form of financing— called initial coin offerings (ICOs)—provided more start-up financing than did venture capitalists in June and July of 2017.13 Catalini and Gans (2018) analyze ICOs where the token on sale may be redeemed for the firm’s product (which is the form the tokens often take) and find that tokens may help entrepreneurs by revealing aspects of consumer demand. Howell, Niessner, and Yermack (2018) analyze post-issuance transaction data for tokens listed on CoinMarketCap and find that liquidity is greater for issuers that engage in voluntary disclosure and credibly commit to the project.

9.5  Organizational Innovation New organizational forms for financial institutions have emerged in the United States and other countries over the past few decades. While some of these forms arose from 12  See Athey et al. (2016) for a theoretical model of Bitcoin pricing and some descriptive analysis of the market. A listing of major cryptocurrency exchanges—along with some volume and price data—may be obtained from CoinMarketCap at https://coinmarketcap.com/exchanges/volume/24-hour/. 13  Kharpal (2017) documents the role of ICOs in providing more early-stage financing than did venture capitalists in the early summer of 2017. See Wall (2018a, 2018b) for an overview of the issues raised by ICOs as a funding tool for new ventures.

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276   Activities and Performance regulatory developments, two related structures—Internet-only banks and marketplace lenders—are directly tied to technological change. Internet-Only Banks. The rapid rise in Internet access and usage during the 1990s created the possibility of a new organizational form for intermediaries: the Internetonly (or Internet-primary) banks. Research by Delgado, Hernando, and Nieto (2007) reports that, as of mid-year 2002, there were some thirty-five Internet-only banks operating in Europe and another twenty in the US. In Europe, virtually all of these banks were affiliated with existing institutions, while in the US they tended to be de novo operations. This may explain why US-based Internet-only banks have disappeared (through acquisition, liquidation, or closure) or established a physical presence to supplement their Internet base. DeYoung (2001, 2005) finds that, as compared with conventional de novo banks, the Internet de novo banks are less profitable due to low business volumes (fewer deposits and lower non-interest income) and high labor expenditures. However, the author also reports that the financial performance gaps narrow quickly over time due to scale effects. Relatedly, Cyree, Delcoure, and Dickens (2009) find that Internet-primary banks are larger and have lower net interest margins and loan losses. Delgado, Hernando, and Nieto (2007) report that European Internet banks demonstrate technology-based scale economies. Although Internet-only banks failed to take hold in the early 2000s, new opportunities opened for innovative organizational forms in the 2010s as a result of two developments: (i) the continuing advance of technology; and (ii) the need to recover from the 2007–9 financial crisis in the US and from the sovereign debt crisis in the EU that started in 2009. The introduction of the iPhone in 2007 was one marker of the continuing advancement of a broad array of technologies.14 These advances allowed technology firms to enter a wide variety of commercial and financial activities, often providing superior service to that provided by incumbent firms. Moreover, while technology firms were looking for profitable opportunities to disrupt existing industries, the need to recover from the financial crisis distracted bank management and reduced the resources that banks had to invest in new technology and to make new loans. One of the most well-known sets of new online financial institutions is marketplace lenders. Marketplace Lenders. Marketplace lenders, which match consumers and small firms as borrowers with lenders/investors using online platforms, have been popping up all over the world. In the United States, these lending arrangements generally work in the following way: First, borrowers apply on the platform and are subject to automated underwriting based on standard criteria (such as a credit score) plus additional information, and assigned a proprietary risk rating. Second, institutional investors purchase loans in 14  Mobile retail payments using cellular phones are widespread in Africa, most notably in Kenya with Safaricoms’ M-Pesa program. See Beck and Frame (2018) for further details and a review of the related literature.

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Technological Change and Financial Innovation in Banking   277 bulk from the marketplace lenders, principally based on the risk ratings.15 The online marketplaces themselves generally have no direct exposure to the credit risk of the loans through their platforms, as they do not typically hold the loans or otherwise retain an interest in them or guarantee their performance.16 Instead, marketplace lenders principally generate revenue from loan origination and servicing fees. Marketplace lending is growing rapidly, but it remains a very small part of the $3.3 trillion US consumer lending market. Much of what constitutes marketplace lending is actually not new. As discussed above, for many years, larger banks and finance companies have used credit registry data, credit scores, and borrower income information as inputs for statistical models to estimate risk and price consumer loans. However, marketplace lenders appear to be increasingly supplementing their models with additional information. Jagtiani and Lemieux (2018) find that LendingClub’s credit scores had an 80 percent correlation with FICO scores in 2007, but that the correlation drops about 35 percent for loans originated in 2014–15. The authors suggest that the change is likely due to LendingClub using a combination of alternative data and machine learning as the platform gains more experience with consumer lending.17 In complementary research that uses information from Prosper (which is a prominent marketplace lender), Balyuk and Davydenko (2018) discuss that lender’s use of secondary screening to identify suspicious applications and to verify automatically some borrower-provided information. The authors report that this additional screening has led to the cancellation of 27 percent of the previously accepted loan applications since 2013. Vallee and Zeng (2018) observe that, while the FinTech platforms are using their own models to grade loans and determine credit spreads, informationally sophisticated investors may be able to differentiate credit quality within these ratings grades. The authors derive a model allowing for such a split in investor sophistication, which results in a trade-off for the platform in terms of the contribution of sophisticated investors in improving loan quality but also creating adverse selection for less sophisticated investors. The volume-maximizing solution for the platform is to provide intermediate levels of screening and information to investors. Consistent with their model, the authors find that loans purchased by more informationally sophisticated investors were less likely to

15  While marketplace lending originally involved raising funds from individuals, it is institutional investors who provide the bulk of financing today. 16  For legal reasons, marketplace loans in the US are actually originated on the balance sheet of a partner bank. This allows the marketplace lender to: (1) purchase the loans without needing to obtain individual state banking/lending licenses; and (2) charge interest rates that are legal in the partner bank’s state but may not be legal in the borrower’s state. The partner bank holds the loan for a few days before selling it to the marketplace lender, which in turn sells it to investors. 17  Berg et al. (2018) discuss the use of alternative data to improve default prediction by a German e-commerce company. The authors identify various pieces of a customer’s digital footprint as aiding in prediction: access device type, operating system, access channel, allowing for location tracking, time of day, email service provider, and various customer typing conventions.

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278   Activities and Performance default for the universe of investments made through LendingRobot from 2014–17.18 They also observe that one marketplace lender, LendingClub, reduced the amount of information it provided to investors and this caused a reduction in the ability of sophisticated investors to “cherry-pick” loans with lower default rates. Beyond marketplace lenders specifically, there has been a general increase in online lending. According to Fuster et al. (2018), FinTech mortgage lenders have increased their market share from 2 to 8 percent between 2010 and 2016. The authors find the biggest benefit provided by FinTech lenders is an average reduction in the time from application to closing of ten days (20 percent) after controlling for borrower and loan characteristics. They also find that FinTech lenders can scale up the volume of mortgages they process more readily than can other lenders. The information technology underlying such an automated approach to underwriting is subject to significant scale economies (large fixed costs and very low marginal costs), which provides strong incentives to grow large quickly. This suggests that the consolidation of the marketplace lending industry is very likely. Moreover, as marketplace lenders become more successful, they are likely to find themselves facing increased competition from incumbent consumer lenders.

9.6 Conclusions This chapter reviewed some of the more developed literature relating technological change and financial innovation in banking over the past thirty years. In terms of process and product innovations, the empirical research record provides us with information about the characteristics of users and adopters of technology-driven financial innovations and the attendant welfare implications. Faster computing and widespread adoption of the Internet has resulted in a more efficient payment system with related product innovations quickly diffusing to a large part of the population. Technological change has also transformed consumer lending by moving from human to automated underwriting based on credit scores and other pieces of hard information. This has resulted in expanded credit availability along both intensive and extensive margins. The recent emergence of FinTech has greatly expanded interest in financial innovation as new products, services, production processes, and organizational forms are being created and deployed. Blockchain and distributed ledger technologies are currently being used for the issuance and transfer of widely distributed cryptocurrencies as well as  for early-stage funding for technology companies via initial coin offerings. Artificial intelligence and machine learning are being used: in lending environments for 18  LendingRobot is an automated tool for investors in loans that are originated by LendingClub and Prosper.

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Technological Change and Financial Innovation in Banking   279 marketing and monitoring account activity; to provide low-cost advisement services; and to further improve credit decisions through the use of expanded information. This is a very exciting time to study financial innovation and the continued evolution of the banking business.

References Ackerberg, D.  A. and Gowrisankaran, G. (2006). “Quantifying Equilibrium Network Externalities in the ACH Banking Industry,” RAND Journal of Economics, 37(3), 738–61. Adams, W., Einav, L., and Levin, J. (2009). “Liquidity Constraints and Imperfect Information in Subprime Lending,” American Economic Review, 99(1), 49–84. Akhavein, J., Frame, W. S., and White, L. J. (2005). “The Diffusion of Financial Innovations: An Examination of the Adoption of Small Business Credit Scoring by Large Banking Organizations,” Journal of Business, 78(2), 577–96. Alan, S. and Loranth, G. (2013). “Subprime Consumer Credit Demand: Evidence from a Lender’s Pricing Experiment,” Review of Financial Studies, 26(9), 2353–74. Anguelov, C. E., Hilgert, M. A., and Hogarth, J. M. (2004). “US Consumers and Electronic Banking: 1995–2003,” Federal Reserve Bulletin, 90(1), 1–18. Arestis, P., Demetriades, P. O., and Luintel, K. B. (2001). “Financial Development and Economic Growth: The Role of Stock Markets,” Journal of Money, Credit, and Banking, 33(1), 16–41. Ashcraft, A. and Schuermann, T. (2008). “Understanding the Securitization of Subprime Mortgage Credit,” Federal Reserve Bank of New York Staff Report No. 318, March. Athey, S., Parashkevov, I., Sarukkai, V., and Xia, J. (2016). “Bitcoin Pricing, Adoption, and Usage: Theory and Evidence,” Stanford Working Paper, available at: https://www.gsb.stanford.edu/gsb-cmis/gsb-cmis-download-auth/423411. Ausubel, L.  M. (1991). “The Failure of Competition in the Credit Card Market,” American Economic Review, 81(1), 50–81. Balyuk, T. and Davydenko, S. (2018). “Reintermediation in FinTech: Evidence from Online Lending,” available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3189236. Bauer, K. and Hein, S. (2006). “The Effect of Heterogeneous Risk on the Early Adoption of Internet Banking Technologies,” Journal of Banking and Finance, 20(10), 1713–25. Bauer, P. W. and Ferrier, G. D. (1996). “Scale Economies, Cost Efficiencies, and Technological Change in Federal Reserve Payment Processing,” Journal of Money, Credit, and Banking, 28(4), 1004–39. Bauer, P. W. and Hancock, D. (1995). “Scale Economies and Technological Change in Federal Reserve ACH Payment Processing,” Economic Review, Federal Reserve Bank of Cleveland, 31(3), 14–29. Beck, T., Chen, T., Lin, C., and Song, F. M. (2016). “Financial Innovation: The Bright and the Dark Sides,” Journal of Banking and Finance, 72, 28–51. Beck, T. and Frame, W. S. (2018). “Technological Change, Financial Innovation, and Economic Development,” in T.  Beck and R.  Levine (eds.), Handbook of Finance and Development (Cheltenham: Edward Elgar), 369–390. Beck, T. and Levine, R. (2004). “Stock Markets, Banks, and Growth: Panel Evidence,” Journal of Banking and Finance, 28(3), 423–42. Beck, T., Levine, R., and Loayza, N. (2000). “Finance and the Sources of Growth,” Journal of Financial Economics, 58(1–2), 261–300.

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280   Activities and Performance Berg, T., Burg, V., Gombovic, A., and Puri, M. (2018). “On the Rise of FinTechs—Credit Scoring using Digital Footprints,” available at SSRN: https://papers.ssrn.com/sol3/papers. cfm?abstract_id=3163781. Berger, A. N. (2003). “The Economic Effects of Technological Progress: Evidence from the Banking Industry,” Journal of Money, Credit and Banking, 35(2), 141–76. Berger, A.  N., Cowan, A., and Frame, W.  S. (2007). “The Surprising Use of Credit Scoring in  Small Business Lending by Community Banks and the Attendant Effects on Credit Availability, Risk, and Profitability,” Journal of Financial Services Research, 39(1–2), 1–17. Berger, A. N., Espinosa-Vega, M., Frame, W. S., and Miller, N. (2005). “Debt Maturity, Risk, and Asymmetric Information,” Journal of Finance, 60(6), 2895–923. Berger, A. N., Espinosa-Vega, M., Frame, W. S., and Miller, N. (2011). “Why Do Borrowers Pledge Collateral? New Empirical Evidence on the Role of Asymmetric Information,” Journal of Financial Intermediation, 20(1), 55–70. Berger, A. N., Frame, W. S., and Miller, N. (2005). “Credit Scoring and the Availability, Price, and Risk of Small Business Credit,” Journal of Money, Credit, and Banking, 37(2), 191–222. Berger, A. N. and Udell, G. F. (2006). “A More Complete Conceptual Framework for SME Finance,” Journal of Banking and Finance, 30(11), 2945–66. Bhardwaj, G. and Sengupta, R. (2014). “Subprime Cohorts and Loan Performance,” Journal of Banking and Finance, 41(2), 236–52. Borzekowski, R. and Kiser, E. (2008). “The Choice at the Checkout: Quantifying Demand Across Payment Instruments,” International Journal of Industrial Organization, 26(4), 889–902. Borzekowski, R., Kiser, E., and Ahmed, S. (2008). “Consumers’ Use of Debit Cards: Patterns, Preferences, and Price Response,” Journal of Money, Credit, and Banking, 40(1), 149–72. Brueckner, J., Calem, P., and Nakamura, L. (2012). “Subprime Mortgages and the Housing Bubble,” Journal of Urban Economics, 71(2), 230–43. Bubb, R. and Kaufman, A. (2014). “Securitization and Moral Hazard: Evidence from Credit Score Cutoff Rules,” Journal of Monetary Economics, 63(1), 1–18. Budish, E. (2018). “The Economic Limits of Bitcoin and the Blockchain,” National Bureau of Economic Research Paper No. 24717. Campbell, T. S. (1988). Money and Capital Markets (Glenview, IL: Scott, Foresman). Catalini, C. and Gans, J. S. (2017). “Some Simple Economics of the Blockchain,” available at SSRN: https://ssrn.com/abstract=2874598 or http://dx.doi.org/10.2139/ssrn.2874598. Catalini, C. and Gans, J.  S. (2018). “Initial Coin Offerings and the Value of Crypto Tokens,” available at SSRN: https://ssrn.com/abstract=3137213 or http://dx.doi.org/10.2139/ ssrn.3137213. Ciciretti, R., Hasan, I., and Zazzara, C. (2009). “Do Internet Activities Add Value? Evidence from Traditional Banks,” Journal of Financial Services Research, 35(1), 81–98. Cong, L. W. and He, Z. (2018). “Blockchain Disruption and Smart Contracts,” NBER Working Paper No. w24399, available at SSRN: https://ssrn.com/abstract=3138382. Cyree, K. B., Delcoure, N., and Dickens, R. (2009). “An Examination of the Performance and Prospects for the Future of Internet-Primary Banks,” Journal of Economics and Finance, 33(2), 128–47. Dandapani, K., Karels, G.  V., and Lawrence, E.  R. (2008). “Internet Banking Services and Credit Union Performance,” Managerial Finance, 34(6), 437–46. Delgado, J., Hernando, I., and Nieto, M. J. (2007). “Do European Primarily Internet Banks Show Scale and Experience Efficiencies?” European Financial Management, 13(4), 643–71. DeYoung, R. (2001). “The Financial Performance of Pure Play Internet Banks,” Economic Perspectives, Federal Reserve Bank of Chicago, 25(Q1), 60–75.

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Technological Change and Financial Innovation in Banking   281 DeYoung, R. (2005). “The Performance of Internet-Based Business Models: Evidence from the Banking Industry,” Journal of Business, 78(3), 893–947. DeYoung, R., Frame, W. S., Glennon, D. and Nigro, P. (2011). “The Information Revolution and Small Business Lending: The Missing Evidence,” Journal of Financial Services Research, 39(1–2), 19–33. DeYoung, R., Lang, W.  W., and Nolle, D.  L. (2007). “How the Internet Affects Output and Performance at Community Banks,” Journal of Banking and Finance, 31(4), 1033–60. Dow, J.  P. (2007). “The Adoption of Web Banking at Credit Unions,” Quarterly Review of Economics and Finance, 47(3), 435–48. Einav, L., Jenkins, M., and Levin, J. (2012). “Contract Pricing in Consumer Credit Markets,” Econometrica, 80(4), 1387–432. Elul, R. (2016). “Securitization and Mortgage Default,” Journal of Financial Services Research, 49(2), 281–309. Foote, C. L., Gerardi, K., and Willen, P. (2008). “Negative Equity and Foreclosure: Theory and Evidence,” Journal of Urban Economics, 64(2), 234–45. Fracassi, C., Germaise, M., Kogan, S., and Natividad, G. (2016). “Business Microloans for U.S. Subprime Borrowers,” Journal of Financial and Quantitative Analysis, 51(1), 55–83. Frame, W. S. (2018). “Agency Conflicts in Residential Mortgage Securitization: What Does the Empirical Literature Tell Us?” Journal of Financial Research, 41(2), 237–51. Frame, W.  S., Padhi, M., and Woosley, L. (2004). “The Effect of Credit Scoring on Small Business Lending in Low- and Moderate-Income Areas,” Financial Review, 39(1), 35–54. Frame, W. S., Srinivasan, A., and Woosley, L. (2001). “The Effect of Credit Scoring on Small Business Lending,” Journal of Money, Credit, and Banking, 33(3), 813–25. Frame, W. S. and White, L. J. (2004). “Empirical Studies of Financial Innovation: Lots of Talk, Little Action?” Journal of Economic Literature, 42(1), 116–44. Furst, K., Lang, W., and Nolle, D. (2002). “Internet Banking,” Journal of Financial Services Research, 22(1–2), 95–117. Fusaro, M. (2013). “Why do People Use Debit Cards: Evidence from Checking Accounts?” Economic Inquiry, 51(4), 1986–2001. Fuster, A., Plosser, M., Schnabl, P., and Vickery, J. (2018). “The Role of Technology in Mortgage Lending,” Federal Reserve Bank of New York Staff Report No. 836. Gandal, N., Hamrick, J. T., Moore, T., and Oberman, T. (2018). “Price Manipulation in the Bitcoin Ecosystem,” Journal of Monetary Economics, 95, 86–96. Gennaioli, N., Shleifer, A., and Vishny, R. (2012). “Neglected Risks, Financial Innovation, and Financial Fragility,” Journal of Financial Economics, 104(3), 452–68. Gerardi, K., Lehnert, A., Sherlund, S. M., and Willen, P. (2008). “Making Sense of the Subprime Mortgage Crisis,” Brookings Papers on Economic Activity, 2, 69–159. Goddard, J., McKillop, D., and Wilson, J. O. S. (2009). “Which Credit Unions Are Acquired?” Journal of Financial Services Research, 36(2–3), 231–52. Gowrisankaran, G. and Stavins, J. (2004). “Network Externalities and Technology Adoption: Lessons from Electronic Payments,” RAND Journal of Economics, 35(2), 260–76. Griffin, J. and Maturana, G. (2016). “Did Dubious Mortgage Origination Practices Distort House Prices?” Review of Financial Studies, 29(7), 1671–708. Griffin, J.  M. and Shams, A. (2018). “Is Bitcoin Really Un-Tethered?” Available at SSRN: https://ssrn.com/abstract=3195066 or http://dx.doi.org/10.2139/ssrn.3195066. Gross, M., Hogarth, J., and Schmeiser, M. (2012). “Use of Financial Services by the Unbanked and Underbanked and the Potential for Mobile Financial Services Adoption,” Federal Reserve Bulletin, 98(4), 1–20.

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282   Activities and Performance Hayashi, F. (2016). “Access to Electronic Payments Systems by Unbanked Consumers”, Federal Reserve Bank of Kansas City, Economic Review, 101(3), 5–30. Hayashi, F. and Klee, E. (2003). “Technology Adoption and Consumer Payments: Evidence from Survey Data,” Review of Network Economics, 2(2), 175–90. Hayashi, F. and Stavins, J. (2012). “Effects of Credit Scores on Consumer Payments Choice,” Federal Reserve Bank of Kansas City Working Paper 2012–13. Henderson, B. J. and Pearson, N. D. (2011). “The Dark Side of Financial Innovation: A Case Study of the Pricing of a Retail Financial Product,” Journal of Financial Economics, 100(2), 227–47. Hernández-Murillo, R., Llobet, G., and Fuentes, R. (2010). “Strategic Online Banking Adoption,” Journal of Banking and Finance, 34(7), 650–1663. Hernando, I. and Nieto, M.  J. (2007). “Is the Internet Delivery Channel Changing Banks’ Performance? The Case of Spanish Banks,” Journal of Banking and Finance, 31(4), 1083–99. Howell, S., Niessner, M., and Yermack, D. (2018). “Initial Coin Offerings: Financing Growth with Cryptocurrency Token Sales,” NBER Working Paper No. 24774. Huberman, G., Leshno, J., and Moallemi, C. C. (2017). “Monopoly without a Monopolist: An Economic Analysis of the Bitcoin Payment System,” available at SSRN: https://ssrn.com/ abstract=3025604 or http://dx.doi.org/10.2139/ssrn.3025604. Jagtiani, J. and Lemieux, C. (2018). “The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the Lending Club Consumer Platform,” Federal Reserve Bank of Philadelphia Working Paper No. 18–15. Jiang, W., Nelson, A., and Vytlacil, E. (2013). “Securitization and Loan Performance: Ex Ante and Ex Post Relations in the Mortgage Market,” Review of Financial Studies, 27(2), 454–83. Jiang, W., Nelson, A., and Vytlacil, E. (2014). “Liar’s Loan? Effects of Origination Channel and Information Falsification on Mortgage Delinquency,” Review of Economics and Statistics, 96(1), 1–18. Keys, B., Mukherjee, T., Seru, A., and Vig, V. (2010). “Did Securitization Lead to Lax Screening? Evidence from Subprime Loans,” Quarterly Journal of Economics, 125(1), 307–62. Keys, B., Seru, A., and Vig, V. (2012). “Lender Screening and the Role of Securitization: Evidence from the Prime and Subprime Mortgage Markets,” Review of Financial Studies, 25(7), 2071–108. Kharpal, A. (2017). “Initial Coin Offerings have Raised $1.2 Billion and Now Surpass Early Stage VC Funding,” CNBC website (August 9), available at: https://www.cnbc.com/2017/08/09/ initial-coin-offerings-surpass-early-stage-venture-capital-funding.html. Klee, E. (2006). “Families’ Use of Payment Instruments During a Decade of Change in the US Payment System,” Federal Reserve Board, Finance and Economics Discussion Series, #2006-01. Krugman, P. R. (2007). “Innovating our Way to Financial Crisis,” New York Times, December 3, available at: http://www.nytimes.com/2007/12/03/opinion/03krugman.html. Lerner, J. and Tufano, P. (2011). “The Consequences of Financial Innovation: A Counterfactual Research Agenda,” NBER Working Paper No. 16780, available at: http://www.nber.org/ papers/w16780.pdf. Levine, R. (1997). “Financial Development and Economic Growth: Views and Agenda,” Journal of Economic Literature, 35(2), 688–726. Levine, R. (1998). “The Legal Environment, Banks, and Long-run Economic Growth,” Journal of Money, Credit, and Banking, 30(3), 596–613. Levine, R. (1999). “Law, Finance, and Economic Growth,” Journal of Financial Intermediation, 8(1–2), 36–67.

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Technological Change and Financial Innovation in Banking   283 Levine, R., Loayza, N., and Beck, T. (2000). “Financial Intermediation and Growth: Causality and Causes,” Journal of Monetary Economics, 46(1), 31–77. Levine, R. and Zervos, S. (1998). “Stock Markets, Banks, and Economic Growth,” American Economic Review, 88(3), 537–58. Mantel, B. (2000). “Why do Consumers Pay Bills Electronically? An Empirical Analysis,” Economic Perspectives, Federal Reserve Bank of Chicago, 24(4), 32–47. Mantel, B. and McHugh, T. (2001). “Competition and Innovation in the Consumer E-Payments Market? Considering Demand, Supply, and Public Policy Issues,” Federal Reserve Bank of Chicago, Emerging Payments Occasional Working Paper No. EPS-2001–4. Mayer, C., Pence, K., and Sherlund, S. (2009). “The Rise in Mortgage Defaults,” Journal of Economic Perspectives, 23(1), 27–50. Mayer, C., Piskorski, T., and Tchistyi, A. (2013). “The Inefficiency of Refinancing: Why Prepayment Penalties Are Good for Risky Borrowers,” Journal of Financial Economics, 107(3), 694–719. Merton, R. C. (1992). “Financial Innovation and Economic Performance,” Journal of Applied Corporate Finance, 4(4), 12–22. Merton, R. C. (1995). “Financial Innovation and the Management and Regulation of Financial Institutions,” Journal of Banking and Finance, 19(3–4), 461–81. Miller, M. H. (1986). “Financial Innovation: The Last Twenty Years and the Next,” Journal of Financial and Quantitative Analysis, 21(4), 459–71. Miller, M. H. (1992). “Financial Innovation: Achievements and Prospects,” Journal of Applied Corporate Finance, 4(4), 4–12. Nakamoto, S. (2008). “Bitcoin: A Peer-to-Peer Electronic Cash System,” available at: https:// bitcoin.org/bitcoin.pdf. Piskorski, T. and Tchistyi, A. (2010). “Optimal Mortgage Design,” Review of Financial Studies, 23(8), 3098–140. Piskorski, T. and Tchistyi, A. (2011). “Stochastic House Appreciation and Optimal Mortgage Lending,” Review of Financial Studies, 24(5), 1407–46. Piskorski, T., Seru, A., and Witken, J. (2015). “Asset Quality Misrepresentation by Financial Intermediaries: Evidence from the RMBS Market,” Journal of Finance, 70(6), 2635–78. Stavins, J. (2001). “Effect of Consumer Characteristics on the Use of Payment Instruments,” New England Economic Review, Federal Reserve Bank of Boston, 3(Q3), 19–31. Stavins, J. and Bauer, P. W. (1999). “The Effect of Pricing on Demand and Revenue in Federal Reserve ACH Payment Processing,” Journal of Financial Services Research, 16(1), 27–45. Thakor, A. (2012). “Incentives to Innovate and Financial Crises,” Journal of Financial Economics, 103(1), 130–48. Tufano, P. (2003). “Financial Innovation,” in G. M. Constantinides, M. Harris, and R. Stulz, (eds.), Handbook of the Economics of Finance: Vol. 1A Corporate Finance (Amsterdam: North-Holland), 307–35. US Federal Reserve (2016). “Federal Reserve Payments Study,” available at: https://www.federalreserve.gov/newsevents/press/other/2016-payments-study-20161222.pdf. Vallee, B. and Zeng, Y. (2018). “Marketplace Lending: A New Banking Paradigm?” Available at SSRN: https://ssrn.com/abstract=3102984 or http://dx.doi.org/10.2139/ssrn.3102984. Van Horne, J. C. (1985). “Of Financial Innovations and Excesses,” Journal of Finance, 40(3), 621–36. Volcker, P. A. (2009). “Paul Volcker: Think More Boldly,” Wall Street Journal, December 14, available at: http://online.wsj.com/article/SB100014240527487048255045745863309605971 34.html.

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284   Activities and Performance Wall, L. D. (2018a). “The Initial Coin Offerings Market (Part 1),” Notes from the Vault, Federal Reserve Bank of Atlanta (March), available at: https://www.frbatlanta.org/cenfis/publications/notesfromthevault/03-the-initial-coin-offerings-market-2018-03-09.aspx. Wall, L. D. (2018b). “The Initial Coin Offerings Market (Part 2),” Notes from the Vault, Federal Reserve Bank of Atlanta (April), available at: https://www.frbatlanta.org/cenfis/publications/notesfromthevault/04-the-initial-coin-offerings-market-part-2-2018-04-20.aspx. Wall, L. D. (2018c). “Some Financial Regulatory Implications of Artificial Intelligence,” Journal of Economics and Business, 100, 55–63. Zinman, J. (2009). “Debit or Credit?” Journal of Banking and Finance, 33(2), 358–66.

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chapter 10

Paym en ts David Humphrey

10.1  Payments Overview Over the last 100 years the most important change in payments has been the shift from an essentially cash-based payment system (using gold and silver coins as well as paper currency) to one where checks or paper giro transactions played a dominant role in the value of payments. More recently, paper instruments have been replaced by electronic substitutes. Checks have been increasingly replaced by Automated Clearing House (ACH) payments and debit cards. Paper-based credit card transactions and paper-initiated giro payments have been replaced by electronic versions of the same instruments. For large-value payments, large shipments of currency or gold by rail or boat were replaced by accounting entries among correspondent banks and telegraph messages for intercity and regional settlement. Currently, highly secure real-time gross settlement (RTGS) networks are used for large-value payments, while interbank, and payments over card and giro networks, are settled using central bank balances. These changes lowered transaction costs and improved security. It also eliminated US domestic exchange rates that reflected the cost (and risk) of physically transporting gold, and later currency, among regions for interbank settlement (Garbade and Silber, 1979). The many different retail payment instruments are best distinguished by their average transaction value. This largely determines the type of transaction they are used for and the cost and risk issues associated with their use. Smaller value retail transactions include cash, checks, and debit and credit cards (some tied to a mobile phone) and are used at the point of sale. Another type of retail payment concerns medium value consumer and business bill payments using checks and electronic ACH transfers in the US, or postal and bank giro networks in Europe. This includes direct debits for consumer bill payments (with cards used on the Internet) along with credit transfers for business and employee disbursements. Large-value or wholesale payments primarily use wire transfers (in the US, Europe, and elsewhere). These represent large-value transactions among businesses, between

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286   Activities and Performance business and government, and importantly lay behind almost all large-value financial transactions in foreign exchange, government security, corporate bond, equity, and derivative markets. A country’s payment system is comprised of the payment instruments used, and the banking institutions directly involved, in offering transaction services. There are also bank and non-bank firms that process the payments, transportation firms (for cash), and telecommunications facilities (for electronic payments) needed to move the payment information between individual and business deposit accounts at banks. Telecommunication facilities are also needed to transfer funds between individual bank reserve accounts at central banks for final settlement of retail and wholesale transactions. Cash does not require final settlement—the transfer of good and final funds between accounts or persons—since coin and currency already represent final payment. Central banks are used for final settlement, rather than private banks, due to their low cost and the presumption that they cannot fail (as governments could print money or tax to support them if needed). In the US and Europe, banks have an effective monopoly in offering retail and wholesale payment services since deposit accounts contain the funds needed for almost all types of transactions. This is enforced by the legal definition of what a bank is and does as only banks are typically allowed access to central bank payment settlement accounts. Some countries (e.g., Canada, Australia) allow non-bank financial firms to have limited access to central bank settlement services and in many countries non-bank institutions may offer limited payment services outside of usual banking channels (e.g., money order firms, money transmitters of inter-country remittances). Even so, almost all payments go through banks and are an important source of revenue. The contribution of payment-related activities to bank operating revenues was estimated to be 42 percent at the twenty-five largest US bank holding companies. Most of this revenue is associated with the deposit function (service charges, card revenues, transaction fees) with the remaining amount coming from fiduciary (trust) and trading activities (Radecki, 1999). Banks also provide large-value payment services to the public. In the US (and similarly in Europe) large-value payment volumes are around 0.1 percent of all non-cash retail transactions but over six times the value of retail payments. Due to the importance of these transactions underpinning financial markets, central banks are typically a primary supplier of wire transfers to banks (Fedwire in the US, Target 2 in Europe, and BOJ-NET in Japan). However, in some specialized financial markets, bank-owned organizations initiate and process large-value transactions among their members for themselves and their customers (CHIPS in the US, Euro1 and CLS Bank for Europe, CHAPS in the UK, and similar entities in other countries). In this process they use a portion of central bank reserve account funds for initial funding (in the US) or post collateral for intraday exposures (in the UK and Europe) with later final net settlement in good funds. This is an improvement over practices some forty years ago when there was almost no cover for intraday credit exposures on these large-value net settlement networks. International payments are made via SWIFT, a message transfer network. Here funds are “moved” using accounting entries to interbank correspondent accounts at banks in

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Payments   287 sending and receiving countries. As there is no world central bank, there is no final ­settlement in the usual sense: banks in different countries carry as an asset (liability) the various “due from” (“due to”) deposit amounts of other banks in their interbank correspondent accounts. This enables them to provide foreign exchange for customers paying for imports, receive foreign exchange from customers selling exports, or facilitate f­ oreign investment and other capital flows for their customers (all for a fee).

10.1.1  Payment Theory Current payment instruments evolved from earlier forms, such as seashells, peppercorns, or precious metals. The main attributes of money have always been that it is easily divisible for transactions; has an agreed upon stable nominal value; is easy to transfer and store; and (importantly) has scarcity value. When money is not scarce, due to gold discoveries when gold was money or when countries print too much currency after currency replaced gold, inflation resulted and the purchasing power of money was markedly reduced. Using simplified models for mathematical tractability, payment theory largely focuses on how different payment arrangements evolved among transactors as a substitute for barter and how they trade off with one another today. These analyses offer insights on the reasons behind the development and (slow) adoption of different types of retail payment instruments over time. This involves the use of cash versus different types of debit or credit instruments (checks, cards) due to their attributes of transferability and finality (Kahn and Roberds, 2007). In contrast, most empirical payment analyses rely on wellaccepted microeconomic theory dealing with payment pricing principles; demand estimation; payment instrument substitution; analysis of payment cost; scale economies; and assessing competition among payment suppliers. Perhaps the most important recent development in payment theory concerns recasting traditional demand theory into a two-sided market framework (Rochet and Tirole, 2003; Rochet and Wright, 2010). It is applied to credit and debit card pricing arrangements (the interchange fee), as well as to other markets, and forms the basis for recent theoretical work in the retail payments area (a survey is provided by Chakravorti (2003) and numerous models are outlined and criticized in Katz (2001)). Most other theoretical developments in this field are related to antitrust and competition issues that have dominated policy debates, regulatory actions, and legal cases. Papers on these topics can be found in the Review of Network Economics (2005 and 2006).

10.1.2  Differences in Payment Structure The current transition from paper (checks, paper-based giros) to electronic non-cash payments (cards, electronic giros, and ACH) is mostly due to technical change allowing greater convenience and lower costs in making payments. Often, an electronic transaction

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288   Activities and Performance costs only one-third to one-half as much as the all-in social or private cost of a paperbased one for the same purpose. While individual consumer payment transactions are not usually priced, businesses can face a fee for each transaction made. Consumer payments do not differ markedly across users, so a minimum balance requirement or monthly fee is charged based on the average number of transactions to cover most of the cost. The volume of business transactions is much more variable across firms. Using an average here would not be appropriate and a fee per transaction plus a monthly deposit account fee are common. In Europe, checks (except for France) and paper-based giro transactions have been effectively eliminated and replaced with electronic giro payments and cards. In contrast, checks markedly reduced cash use in the US after WWII but only relatively recently has check use been falling (about 5 percent a year) with the expansion of cards and the ACH. This is occurring even as checks are now being collected electronically (via Check 21), substantially lowering the resource and float cost of check use in the US. Demographic as well as technical change plays an important role here since new generations grow up without having any experience in using a particular payment instrument and are more open to change compared to their parents. Differences in the intensity of payment instrument use across countries are often associated with historical institutional “accidents” rather than any clear plan to shape payment use. One major institutional difference was the development of a paper-based postal giro system in Europe before 1900 but never in the US. Another was the low cost of obtaining a US banking charter over 125 years ago compared to a very high charter cost in Canada and a history of royal or state monopolies in most European countries. These two institutional differences resulted in many thousands of small banks in the US compared to a far more concentrated banking structure in Europe and Canada. In turn, Europe was able to offer nationwide paper-based giro payments using postal banks (and now also commercial banks) while the US had no alternative but to rely on checks for transactions among thousands of small banks since no national payment service supplier existed. And when technology made electronic payments possible, Europe—with a national giro network already in place—was able to shift more rapidly to electronics for bill payments and business disbursements than was the US. Similarly, the heavy use of cash in Japan compared to either Europe or the US was facilitated by the fact that Japan was, and still is, considered to be a safer country. While this remains the case for retail payments in Japan, bill payments are largely electronic. Another institutional development concerned the early US practice of discounting the face value of a check to cover the cost of collection (non-par banking). In attempting to reduce collection costs, checks were often routed using cheaper (and slower) paths for collection. This resulted in payment delays that were at times inordinately long and disrupted commerce. One reason the Federal Reserve was established was to transport and process checks at face (par) value and at no charge. This eliminated circuitous routing of checks, which hindered commerce. Today, alone among central banks, the Federal Reserve processes about one-half of all check and ACH payments (now for a fee).

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Payments   289 Europe, not having an overabundance of checks (debit transfers) to begin with, due to a reliance on cash and giro (credit transfer) payments, instead covered payment costs by debiting accounts prior to the value date to earn float revenues. This helps to explain why European central banks are not involved in processing retail transactions in competition with banks but do provide final settlement for interbank giro and other transactions.

10.2  Retail Payments The main issue related to retail payments has been the substitution of electronic payment instruments for cash and/or checks over the last forty years. While cash use has fallen in the past, this has slowed recently (except in Scandinavia) while the replacement of checks is still progressing and has been almost eliminated in many countries. The use of cash is approximated by the ratio of cash in circulation to GDP or the value of cash to population. The countries shown in Table 10.1 are ordered by their use of cash, both as a percent of GDP (column 1) and as a value held per person (column 2). This is shown in US dollars for comparison. The ranking of cash use by country is basically the reverse of that for per-person use of non-cash payment instruments shown in the last column.

Table 10.1  Payment Instrument Use, 2016 Cash/GDP

Cash/Population

Percent

Value Held

Check

Card

Giro/ACH

Total Non-Cash

US1

3.4

$1,980

51

326

83

460

UK

3.5

$1,408

7

249

127

383

Canada

Annual Transactions Per Person:

3.8

$1,664

14

276

60

350

Euro Area2

10.7

$3,756

–

–

–

–

Germany

–

–

1,800 as “highly concentrated” (Salop, 1987).

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Competition in the Banking Sector   779

Table 24.1  Evolution of Research on the Impact of Bank Concentration and Competition on Bank Performance Element

Early 1990s

Current

Model

SCP Hypothesis

Various Models of Competition

Measures of Concentration

Herfindahl–Hirschman Index or Concentration Ratio for n Banks

Bank Size and Type (Foreign, State) Broader Measures of Competition

Measures of Conduct

Bank Prices Bank Profitability

Bank Efficiency, Service Quality, Risk Firms’ Access to Credit Banking System Stability

Empirical Models

Static Cross Section Short Run

Dynamic Effects over Time of Bank Consolidation

Data

US Metropolitan Statistical Areas or Non-MSA Counties

Differently Defined US Markets Other Countries

Note: The figures contrast the models, the measures of concentration, the measures of conduct, the empirical models, and the data sources that were used in the early 1990s with those that are used today. Source: Berger, Hasan, and Klapper (2004).

rate–­concentration link. Nevertheless, their study is representative for the SCP approach given their measurement of concentration, reduced-form estimation, and interpretation. They use both a three-bank concentration ratio (CR3) and the HHI.5 Their results overall show a negative impact of market concentration on deposit rates, independent of the concentration measure being used. While the early SCP approach was successful in documenting the importance of ­market structure for various bank interest rates, Berger et al. (2004) surely presents the consensus view when they write that empirical banking literature “has now advanced well past this simple approach” (p. 434). We summarize the notable differences between the SCP and more recent studies, both within an SCP framework and beyond in Table 24.1.

24.2.1.2  Efficient-Structure Hypothesis The efficiency hypothesis provides an alternative explanation for the positive link between bank profitability and concentration or market share. The efficiency hypothesis (see Demsetz, 1973; Peltzmann, 1977) entails that more efficient banks will gain market share. Hence market concentration is driven (endogenously) by bank efficiency. Demsetz (1973) argues that if all firms are able to produce at the same cost, then the rate of return to successfully collude should be independent of the size of the firms. However, if one size of firm earns higher rates of return than another size, given a collusion, then there 5  As control variables they include time dummies, the one-year growth in market deposits, the proportion of bank branches in total number of branches of financial institutions (including S&L branches), a wage rate, per capita income, and a Metropolitan Statistical Area dummy variable.

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780   Regulatory and Policy Perspectives might exist differences in the cost of production that favor the firm that earns the highest rate of return. Two types of efficiency can be distinguished (Berger,  1995). In an X-efficiency narrative, banks with superior management and/or production technologies enjoy higher profits and as a result grow larger market shares. Alternatively, some banks may produce at more efficient scales than others, again leading to higher per unit profits, larger market shares, and higher market concentration. The positive relationship between structure and performance reported in the SCP literature is spurious in the two versions of the efficiency hypothesis, as both structure and performance are determined by efficiency. Initially, the empirical literature aimed to disentangle the SCP and efficiency hypotheses through the following regression specification:

Πijt = α 0 + α1CR jt + α 2 MSijt + ∑γ k X k ,ijt + ε ijt , (2) k

with MSijt the market share of bank i in market j for period t (the notation for the other variables remains the same). The coefficient α2will capture the effect of efficiency, due to production technologies or efficiency scales, on the bank’s profits, but it may also reflect a bank’s relative market power. SCP implies that α1 > 0, whereas both efficiency hypotheses imply that α2 > 0. Most studies find a positive and statistically significant α2, but an α1 close to zero and insignificant. These findings support both efficiency hypotheses, that is, larger market shares go together with higher profitability.6 Berg and Kim (1994) argue that conduct has an important effect on both (in)efficiency and scale measurements and therefore the estimation of such should not be carried out independently of market structure and conduct. Berger (1995) goes one step further than the standard bank efficiency study and aims to further differentiate between the SCP and efficiency hypotheses by including direct measures of both X-efficiency and scale efficiency into the regression specification (as additional variables in the Xk,ijt vector). He argues that after controlling for efficiency, MSijt only captures the relative market power of banks. Berger derives both efficiency measures from the estimation of a translog cost function. X-efficiency is separated from random noise by assuming that X-efficiency differences will persist over time while random noise will not. The X-efficiency measure for bank i then equals the ratio of the predicted costs for the most efficient bank in the sample to the predicted costs for bank i for any given vector of outputs and inputs. Berger (1995) estimates a cost function using data from 4,800 US banks during the 1980s. Including both computed efficiency measures in the performance equation that also contains market share and concentration, Berger finds that in 40 out of 60 regressions, market share actually retains its positive sign. However, the economic significance 6  Hannan and Prager (2009), for example, interact market concentration with the market share of large (small) (not) primarily-out-of-market banks to account for the impact in the market of large banking organizations on the profitability of small single-market banks.

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Competition in the Banking Sector   781 of market share seems very small: a 1 percent increase in market share boosts return on assets by less than 0.1 percent. Nevertheless, Berger interprets these findings as evidence in favor of the relative market power hypothesis: market share does represent market power of larger banks, and their market power may be grounded in advertising, local networks, or business relationships. Results further show that X-efficiency also contributes positively in explaining profits, whereas the results on scale efficiency are mixed and never economically important. Similarly, De Jonghe and Vander Vennet (2008) aim to discriminate between theories establishing a link between market structure and bank performance and alternative explanations based on efficiency considerations. They argue that the effects of competition and efficiency take time to materialize. Therefore, they analyze the competition–­ performance relationship using a longer-term concept of firm rents, the franchise value. They find that banks with better management or production technologies possess a long-run competitive advantage. They also find that bank market concentration does not affect all banks equally. Only the banks with a large market share in a concentrated market are able to generate non-competitive rents. For more on X-efficiency studies analyzing financial institutions, we refer the reader to surveys by Allen and Rai (1996), Molyneux, Altunbas, and Gardener (1996), Berger and Humphrey (1997), or work by Turati (2001). Another traditional method corresponds to studies of economies of scale and scope,7 which address the question whether financial institutions produce the optimal output mix both in terms of size and composition. Literature on this method can be found in Kim (1986), Allen and Rai (1996), Berger and Humphrey (1997), Cavallo and Rossi (2001), Hughes and Mester (2013) and Davies and Tracey (2014).

24.2.2  New Empirical Industrial Organization A fundamental criticism leveled against the SCP and the efficiency hypotheses relates to the embedded—assumed—one-way causality from market structure to performance. In other words, most SCP studies do not take into account the conduct of the banks in the market and the impact of performance of the banks on market structure. In fact, studies that have attempted to determine the degree of competition relying on various indexes of concentration such as the C3, the HHI, and the like, reach conflicting and troublesome results. Carbo et al. (2009) document that the coefficients of determination among these various indexes for both the within and between countries are very weak (most $2B (right scale)

Figure 31.5  The Changing Distribution of US Commercial Banks by Asset Size (in 2009 dollars) between 1980 and 2017. Source: National Information Center (call reports) and author’s calculations.

from regulators to expand their membership bases and to increase lending to small businesses. Kim and McKillop (Chapter 11, this volume) provide a deeper discussion of credit unions and other financial cooperatives. Thus, there is every reason to believe that the number of very small community banks will dwindle further in the coming decade. While some of these tiny banks may remain profitable as dominant banks in small rural towns—where they can use their local market pricing power to offset their very high unit costs—they are simply too small to be financially viable in most competitive settings. In very sharp contrast, between 2010 and 2017 the number of commercial banks with assets greater than $2 billion increased by about 35 percent (see Figure 31.5). Banks in this size class comprise only about 3 percent of the population of all depository institutions, but they hold about 87 percent of all depository assets in the US (see Figure 31.6). While this heavy concentration of assets raises concerns about systemic risk, there is little evidence of pricing power in local banking markets. For the most part, banks became this large by making market-extension mergers, in which they purchased banks in states where they did not previously operate. This method of expansion changed the ownership of the acquired banks but had no impact on local market shares. Hence, US antitrust authorities have little justification for halting industry consolidation, even though the largest US banks have increased by about ten times in size since 1990.7 7  In 1990, CitiCorp was the largest US banking company with assets of $217 billion. In 2017 CitiCorp (now known as CitiGroup) was the fourth largest US banking company with assets over $1.8 trillion.

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Banking in the United States   993 Panel A, Number of Banks

Panel B, Asset Shares of Banks small banks, 8% savings banks, 6%

credit unions, 50%

credit unions, 8% savings banks, 7%

large banks, 3% small banks, 40%

large banks, 78%

Figure 31.6  Commercial Banks, Savings Banks, and Credit Unions in the US in 2017. Note: Panel A shows the relative number of firms. Panel B shows the distribution of assets across those firms. Commercial banks are split into small banks with assets < $2 billion and large banks with assets > $2 billion. Source: Federal Deposit Insurance Corporation and Credit Union National Association.

The very largest US banking companies are also large by global standards. At year-end 2017, eleven US banks were ranked among the top 100 banking companies in the world (see Table 31.3).8 And US banking companies dominate global investment banking. The five largest investment banks in the world are all US banking companies, with a combined 33 percent global market share (see Table 31.4). Despite their competitive success both at home and abroad, large US banks have historically exhibited substantial levels of risk. With their high and largely un-hedged exposures to real estate-backed investments, their liberal use of financial leverage, their disproportionate reliance on noninterest income (see Table 31.2), and the illiquidity of their balance sheets, large US banks were far riskier than small banks going into the 2008–9 financial crisis.9 Four of the ten largest commercial banking companies in the US became insolvent during the financial crisis and either had to be acquired (Wachovia, Washington Mutual) or bailed out by government capital injections (Bank of America, Citigroup). Three of the five largest investment banks in the US (Merrill Lynch, Bear Stearns, Lehman Brothers) became illiquid and/or insolvent during the crisis. By contrast, only about 6 percent of commercial banks smaller than these behemoths failed during or after the crisis. The primary objective of bank re-regulation discussed above was to reduce the riskiness of large banking companies. The data plotted in Figure 31.3 show how re-regulation has affected large bank condition and performance. (Given that the largest banks in the US hold the lion’s share of industry assets, these aggregate industry data closely track large banks.) While financial leverage had been on the decline at US banks since the late-1980s, there was a clear and sustained jump to higher equity-to-assets ratios in 8  JPMorgan Chase, Bank of America, Wells Fargo, Citigroup, US Bancorp, PNC Financial Services, and Bank of New York Mellon are long-time commercial banking companies. Goldman Sachs and Morgan Stanley are long-time investment banks that more recently reorganized as financial holding companies. Capital One specializes in credit card and consumer lending, while State Street provides investment services (securities custody, accounting, asset valuation, asset management, investment advice) for other large financial services firms. 9  See DeYoung and Roland (2001), Clark et al. (2007), and Demirgüc-Kunt and Huizinga (2010) for theory and evidence that non-interest income tends to be less stable than net interest income.

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994   Banking Systems Around the World

Table 31.3  Largest US Banking Companies as of December 31, 2017 by Total Assets ($ billions) Assets ($ billions)

World ranking (derivatives netted)

World ranking (derivatives not netted)

2,533 2,281 1,951 1,842 917 951 462 391 372 366 238

6 9 11 13 35 38 63 71 73 76 100

4 7 12 10 23 24 64 71 72 76 100

JPMorgan Chase & Co. Bank of America Corp. Wells Fargo & Co. Citigroup Inc. Goldman Sachs Group Inc. Morgan Stanley US Bancorp PNC Financial Services Group Inc. Bank of New York Mellon Corp. Capital One Financial Corp. State Street Corp

Note: World rankings based on two accounting methods: US accounting standards which allows banks to net counterparty derivative exposures, and international accounting standards under which ­counterparty derivative exposures are not netted. Source: S&P Global Market Intelligence.

Table 31.4  Global Investment Banking Revenue in 2017 Rank

Bank

1 2 3 4 5 6 7 8 9 10

JP Morgan Goldman Sachs & Co Bank of America Merrill Lynch Morgan Stanley Citi Credit Suisse Barclays Deutsche Bank UBS RBC Capital Markets

Global revenue ($ billions)

% Global market share

6.61 5.84 4.99 4.74 4.36 3.69 3.47 2.63 1.81 1.78

8.1 7.2 6.1 5.8 5.4 4.6 4.3 3.2 2.2 2.2

Note: US Banking Companies are in bold. Source: Dealogic.

expectations of the coming Basel III Accords (2010–11). At the same time, industry ROA declined to the 1 percent range, from its higher pre-crisis range of about 1.2 percent, a change that is consistent with bank activity restrictions imposed in the Dodd–Frank Act (2010). Taken together, these data are consistent with a reduction in large bank risk due to both less financial risk (lower leverage) and less business risk (lower ROA).

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Banking in the United States   995

31.5  The Future of Banking in the US In your author’s opinion, two issues stand out as most important for the future of the US banking industry: The impact of FinTech on competition among all commercial banks, and the regulatory challenges of large insolvent commercial banks.

31.5.1 FinTech The greatest unknown facing commercial banks is the extent to which advancements in information and communications technologies will alter the competitive landscape of the banking industry. “FinTech” is a catch-all term for new technologies that allow ­non-banking companies to produce and/or deliver financial services from outside the traditional banking system. It is a fearsome word that keeps some bankers awake at night. Among other potential disruptors, FinTech’s leading edge includes new payments systems that circumvent the banking system, “big data” models for screening loan applications, substituting cryptocurrencies for fiat currencies, and the inexorable expansion of mobile finance applications.10 To predict how banks are likely to respond to the current competitive threats posed by FinTech, it is useful to review banks’ past reactions to similar phenomena. Two examples are instructive: credit scoring and discount brokerage. Credit scores can be thought of as early antecedents of using big data to measure credit risk. The initial credit-scoring model was introduced in 1989 by the data analytics firm Fair Isaac and Company (FICO), based on consumer information from the credit bureaus Experian, Equifax, and TransUnion. US banks rapidly adopted FICO scores to screen, or help screen, their mortgage and consumer loan applications. Eventually, some of the larger banks entered the market, using internal data on customer credit histories to build their own credit scoring models. Banks used consumer credit scores to reduce the amount of skilled labor time necessary to screen consumer loan applications (i.e., mortgages, credit cards, auto loans), and in competitive markets these production efficiencies were passed along as lower interest rates and fees on consumer loans. Thus, credit scoring was instrumental in expanding the size of consumer credit markets for both banks and non-bank lenders. Discount brokerage is a low cost, low value-added business strategy for producing retail securities trading services. Traders do their own research, go online to enter their buy or sell orders, and are charged a low fixed fee per trade. These online trading platforms began appearing in the late-1980s, and enabled non-banking companies like 10  Frame, Wall and White (Chapter 9, this volume) provide an in-depth discussion of financial i­ nnovation in banking, including “FinTech.” Humphrey (Chapter 10, this volume) provides an overview of retail and wholesale payment systems.

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996   Banking Systems Around the World Charles Schwab, Fidelity, and E*Trade to rapidly grow their retail brokerage businesses. Although these low-price firms did take away some business from higher priced ­traditional financial institutions, the primary effect was to expand the retail brokerage market by making trading affordable for moderate-income households. A number of large US commercial banking companies (e.g., Wells Fargo, US Bancorp, Bank of America) responded by launching their own online discount brokerage platforms. These examples illustrate that, while new financial technologies developed outside of the banking industry may at first appear to pose a competitive threat, the efficiencies generated by these innovations can end up benefiting banks nimble enough to adapt. And while large banks—with greater R&D resources and financial expertise—have adapted more quickly than small banks, these technologies have nonetheless spread quickly to smaller banks, via competition among financial services venders. As FinTech innovators begin to operationalize big data credit risk models, and introduce the next generation of platforms for the delivery and analysis of financial services, this history is likely to repeat itself. The future of FinTech in payments services is less predictable. Commercial banks have long had a legal near-monopoly on payments services, because (a) bills and other financial obligations are paid with money, (b) households and businesses store their money in bank accounts where it is safe from theft and bank failure, and (c) the money in question is the US dollar which has stable value in the short- to moderate-run. These advantages have made commercial banks and other depository institutions the central players in payments services such as check clearing, direct deposit, automatic bill pay, and debit cards.11 Moreover, even the largest nonbank payments providers—such as Visa, MasterCard, and American Express—cannot operate without banks. Merchants that accept credit cards receive payments into their bank accounts from their customers’ banks, and credit card users have the option of financing their purchases with loans from their banks. However, if a FinTech payments innovation allowed merchants and customers to bypass the banking system—and thus not require users to have bank deposit accounts— this would pose a serious competitive threat to commercial banks. New electronic monies, known as “cryptocurrencies,” could make non-bank payments systems possible. Cryptocurrencies can be stored in non-bank “wallets,” transferred to merchants in exchange for goods and services over the web, and, if necessary, converted to and from dollars on independent cryptocurrency exchanges. But these non-bank payments systems have thus far failed to gain much traction, largely because of the instability of the electronic currencies on which they are based. The value of a Bitcoin, the best known of the cryptocurrencies, has fluctuated wildly. Over the two-year period from July 2016 to July 2018, Bitcoin rose from a low of $600 to a high of $19,000 and then back down to $6,000. Non-bank payments systems based upon cryptocurrencies cannot be viable 11  Banks seldom charge explicit fees for these payments services. By providing payments services for their depositors, banks are able to attract low cost (federally insured) deposits to fund their lending operations, and earn non-interest income by cross-selling other financial services to their captive depositors.

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Banking in the United States   997 until the currencies upon which they are based stop being speculative investments and start being stores of value.

31.5.2  Resolving Large Banks Despite regulators’ best efforts to make banks failure-proof by mandating high levels of equity capital and low levels of business risk, bank failures are inevitable. Eventually, one or more large complex banks will fail due to risks that are unforeseen today—just like the risks associated with real estate securitization were unforeseen by bankers and regulators prior to the financial crisis. To prepare for this eventuality, the Dodd–Frank Act gave the FDIC new “orderly liquidation authority (OLA)” to seize systemically important financial institutions (SIFIs) upon their insolvency and then resolve these institutions without bailing them out. The key objective is to defuse the systemic riskiness of the failed financial institution while shutting it down, and thus avoid financial market disruptions or financial damage to other banks. To implement OLA, the FDIC has proposed a “single point of entry” approach in which it will: (1) seize the insolvent holding company, (2) fire senior management, (3) impose a 100 percent loss on stockholders, (4) impose further losses on bondholders and other creditors, and (5) place the assets and remaining liabilities of the holding company into a temporary bridge bank structure with a three-year charter. The FDIC will hire new managers to run the bridge holding company and its affiliates (e.g., the commercial bank, the investment bank, the brokerage, or the insurance company). These temporary managers will use the information contained in the “resolution plans” (which under Dodd–Frank must be revised annually and kept on file) to wind down financial contracts and otherwise stabilize the holding company and its affiliated firms. The bridge institution will receive additional funding from the FDIC as needed to finance the affiliate operations while they are being stabilized. The FDIC will interfere as little as possible with the day-to-day operations of these affiliated firms, other than to make sure that insured bank deposits suffer no losses. Once stabilized, management will sell off the holding company, as a whole or in parts, to healthy financial institutions without any further expense to the FDIC. Ordinary liquidation authority is designed to resolve failed systemically important banks in a transparent, credible, and disciplinary fashion. If allowed to work, OLA would yield four substantial benefits. Because none of the principal players at the failed bank (shareholders, uninsured creditors, or senior managers) would be bailed out or receive any subsidies, a sense of fairness would be re-established with the banking public. Because no banking company would any longer be too-big-to-fail or too-complex-toresolve, moral hazard incentives would decline and bank risk-taking associated with those incentives would be reduced. Because actually shutting down large insolvent banks would establish regulatory credibility, participants in financial markets would know what to expect (and what not to expect) during financial downturns, and this reduction in market uncertainty would limit systemic risk. And because it would identify

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998   Banking Systems Around the World and minimize the spillover costs from large bank failures, a credible post-failure ­resolution policy would make room for less pre-failure prudential regulation, thus ­easing regulatory burden on the industry. But there is a real danger that the OLA resolution approach will not be fully and ­faithfully implemented during a crisis. The Dodd–Frank Act requires that the Treasury Department, the Federal Reserve, and the FDIC must mutually agree to implement OLA on an insolvent banking company; if one or more of these agencies feels that a bailout is the preferable course of action, then an OLA resolution will not occur. This eventuality is most plausible during a severe financial crisis when the fear of short-run disruptions from multiple large bank insolvencies is considered more costly than the long-run damage from allowing large banks to operate with too-big-to-fail incentives.

31.6  In Summary The past forty years has witnessed a near total transformation of the US banking industry, punctuated by the near total disaster of the financial crisis. The bank regulatory framework established during the Great Depression was dismantled, new technologies revolutionized how banks produce and distribute financial services, and dramatic increases in competition have pressured banks to operate more efficiently. The population of commercial banks has been halved by a wave of acquisitions and the largest banks have increased ten-fold in size. A strategic dichotomy has emerged, with small “community” banks providing person-to-person retail and small business banking services, and large commercial banks providing high-volume retail banking services in domestic markets and corporate and investment banking services around the world. These changes have brought great efficiencies to the banking industry and its customers, but have also introduced new instabilities to the system. A decade of historically high profits was followed by large investment losses and government bailouts during the financial crisis of 2008–9. A partial re-regulation of the industry has followed, and both bankers and policymakers now seek to balance market efficiencies with financial stability as this dynamic industry moves further into the twenty-first century.

References Berger, A.N. (2003). “The Economic Effects of Technological Progress: Evidence from the Banking Industry,” Journal of Money, Credit, and Banking, 35, 141–76. Berger, A.N., Frame, W.S., and Miller, N.H. (2005). “Credit Scoring and the Availability, Price, and Risk of Small Business Credit,” Journal of Money, Credit, and Banking, 37, 191–222. Berger, A.N., Kashyap, A.K., and Scalise, J.M. (1995). “The Transformation of the US Banking Industry: What a Long, Strange Trip It’s Been,” Brookings Papers on Economic Activity, 2, 55–218.

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Banking in the United States   999 Clark, T., Dick, A., Hirtle, B., Stiroh, K., and Williams, R. (2007). “The Role of Retail Banking in the US Banking Industry: Risk, Return, and Industry Structure,” Economic Policy Review—Federal Reserve Bank of New York, 13, 39–56. Davies, R. and Tracey, B. (2014). “Too Big To Be Efficient? The Impact of Implicit Funding Subsidies on Scale Economies in Banking,” Journal of Money, Credit and Banking, 46(s1), 219–53. Demirgüç-Kunt, A. and Huizinga, H. (2010). “Bank Activity and Funding Strategies: The Impact on Risk and Returns,” Journal of Financial Economics, 98, 626–50. DeYoung, R. (2005). “The Performance of Internet-based Business Models: Evidence from the Banking Industry,” Journal of Business, 78, 893–947. DeYoung, R. and Roland, K.P. (2001). “Product Mix and Earnings Volatility at Commercial Banks: Evidence from a Degree of Total Leverage Model,” Journal of Financial Intermediation, 10, 54–84. DeYoung, R., Gron, A., Torna, G., and Winton, A. (2015). “Risk Overhang and Loan Portfolio Decisions: Small Business Loan Supply Before and During the Financial Crisis,” Journal of Finance, 70, 2451–87. DeYoung, R., Hunter, W.C., and Udell, G.F. (2004). “The Past, Present, and Probable Future for Community Banks,” Journal of Financial Services Research, 25, 85–133. DeYoung, R., Lang, W.W., and Nolle, D.L. (2007). “How the Internet Affects Output and Performance at Community Banks,” Journal of Banking and Finance, 31, 1033–60. Federal Deposit Insurance Corporation (2012). FDIC Community Banking Study, December. Frame, W.S., Srinivasan, A., and Woosley, L. (2001). “The Effect of Credit Scoring on Small Business Lending,” Journal of Money, Credit, and Banking, 33, 813–25. Gerdes, G.R. and Walton, J.K. (2002). “The Use of Checks and Other Retail Noncash Payments in the United States,” Federal Reserve Bulletin, August, 360–74. Goddard, J., Liu, H., McKillop, D., and Wilson, J.O.S. (2014). “The Size Distribution of US Banks and Credit Unions,” International Journal of the Economics of Business, 21, 139–56. Hughes, J. and Mester, L. (2013). “Who Said Banks Don’t Experience Scale Economies? Evidence From a Risk–Return-Driven Cost Function,” Journal of Financial Intermediation, 22, 559–85. Humphrey, D. (2002). “US Cash and Card Payments Over 25 Years,” Florida State University, unpublished manuscript. Kroszner, R.S. and Melick, W. (2009). “The Response of the Federal Reserve to the Recent Banking and Financial Crisis,” University of Chicago Booth School of Business, December. Porter, M.E. (1985). Competitive Advantage: Creating and Sustaining Superior Performance (New York: The Free Press). Rossi, C.V. (1998). “Mortgage Banking Cost Structure: Resolving an Enigma,” Journal of Economics and Business, 50, 219–34. Wheelock, D. and Wilson, P. (2012). “Do Large Banks Have Lower Costs? New Estimates of Returns to Scale for US Banks,” Journal of Money, Credit and Banking, 44, 171–200.

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chapter 32

Ba n k i ng i n Eu rope Integration, Reform, and the Road to a Banking Union John Goddard, Philip Molyneux, and John O.S. Wilson

32.1 Introduction This chapter provides an overview of the evolution of the banking industry in the European Union since the signing of the Treaty of Rome in 1957 to the present day. We provide an overview of developments in the regulation, financial integration, and the structure and performance of the European banking industry. A brief discussion of the global financial crisis and its resultant impact on European banks together with coverage of the later Eurozone sovereign debt crisis is also presented, along with structural reforms, and the ongoing progress in creating a fully integrated banking and financial services industry throughout the Eurozone. The signing of the Treaty of Rome in 1957 by six countries (Belgium, France, Italy, Luxembourg, the Netherlands, and West Germany) forming the European Economic Community (EEC) was a major historical moment in the foundation of modern Europe. The Treaty of Rome proposed the establishment of a customs union as well as the free flow of goods, services, and capital across member states. Over the following three decades the EEC expanded, and by the next major landmark event, the introduction of the Maastricht Treaty in 1993, member countries had increased to twelve.1 The Treaty marked the official start of the European Union (EU) single market project leading to the establishment of the single currency, the euro (€), a single monetary policy and the establishment of a European Central Bank (ECB) in 1999. The constitutional basis of 1  The founding six members (Belgium, France, Germany, Italy, Luxembourg, the Netherlands) followed by Denmark, Ireland and the UK (1973), Greece (1981), and Spain and Portugal (1986).

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Banking in Europe   1001 the EU changes somewhat infrequently, and it is currently enshrined in the Treaty of Lisbon that came into force in 2009. Since its inception, the EU has expanded and now comprises twenty-eight member states2 with combined GDP (in 2016) of €14.8 trillion. This equates to just over 20 percent of global GDP.3 Similarly, the Eurozone has also grown, with nineteen member countries, which account for approximately threequarters of EU GDP. Notable non-members of the Euro Area are Sweden and the UK (which voted to leave the EU in June 2016).4 Since the late 1970s a major theme of the EU legislative process has focused on the harmonization of rules and regulations aimed at creating a more integrated financial system where banks in individual member states would be regulated in a similar fashion. This would facilitate greater cross-border banking activity either with or without physical establishment. The EC First Banking Directive of 1977 (77/780/EEC) aimed to harmonize banking supervision by establishing the concept of home country control with regulatory responsibility being shifted from the host to home country for banks operating in multiple EU member states. Integration was expected to boost trade in financial services as well. Moreover, integration would increase competition if rules were harmonized sufficiently so that banks from different member states competed on a “level playing field.” Integration therefore went hand-in-hand with product market and geographic deregulation. The integration process was given further impetus in 1985 when the European Commission published a White Paper on The Completion of the Internal Market. This White Paper provided for the free circulation of persons, goods, and capital throughout the EU. In the case of banking, the White Paper called for a single banking license, home country control, and mutual recognition. These principles were incorporated into the 1989 Second Banking Directive (89/646/EEC), which had to be implemented in member states by the end of 1992. Under the terms of the Second Banking Directive, all credit institutions authorized in a given EU member state would be able to establish branches or supply cross-border financial services in the other members of the EU without further authorization, provided that the bank was authorized to provide such services in the home state. This became known as the single banking license (Dermine, 2006). The Second Banking Directive also defined banking business based on the German system. From 1992, banks operating in EU countries were permitted to adopt a universal banking business model, which allowed them to undertake investment banking, insurance, wealth management and other non-bank financial activities. The

2  Since 1986 when there were twelve members, see footnote 1; Austria, Finland, and Sweden joined in 1995; ten countries joined in 2004 (the Czech Republic, Cyprus, Estonia, Latvia, Lithuania, Hungary, Malta, Poland, Slovakia, and Slovenia); Romania and Bulgaria (2007); and Croatia (2013). The UK voted to leave the EU in June 2016. 3  Germany is the leading EU economy, accounting for over a fifth (21.1%) of EU GDP in 2016, followed by the UK (16.0%), France (15.0%), Italy (11.3%), Spain (7.5%), and the Netherlands (4.7%). Source: http:// ec.europa.eu/eurostat/web/products-eurostat-news/-/DDN-20170410-1. 4  Using a synthetic counterfactual approach, Campos, Coricelli, and Moretti (2014, 2016) show that the benefits from being a member of the EU substantially outweigh the costs.

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1002   Banking Systems Around the World new legislation left it up to national regulators to oversee financial conglomerates and the ownership structure of banks.5 As the Second Banking Directive legislation was about to be implemented across member states in 1992, the European Commission had already announced that the next phase of integration would feature the establishment of the Economic and Monetary Union (EMU). The EMU entailed the: coordination of economic policymaking between EU member states; coordination of fiscal policies (notably through limits on government debt and deficits); an independent monetary policy run by the European Central Bank (ECB); single rules and supervision for financial institutions operating within the Eurozone; and establishment of a single currency. The aforementioned changes were expected to facilitate more robust economic conditions across EU member states as well as: furthering financial and non-financial market integration; and creating a more competitive and efficient Single Market for banking and other financial services. These initiatives, combined with a relatively buoyant macroeconomic environment, helped spur banking sector growth. According to Liikanen (2012) total EU banking sector assets increased from around €35 trillion in 2001 (230 percent of GDP) to €43 trillion in 2008 (€32 trillion in the Eurozone), or approximately 350 percent of EU GDP. There were marked differences in banking sector growth across member states. Inside the Eurozone, Ireland and Spain experienced double-digit annual growth between 2001 and 2008. High growth rates in banking sector assets were also experienced in France and the UK. Other member states grew more slowly in the years preceding the global financial crisis. As a consequence, there were also substantial differences in the impact of the financial crisis across member states. This is discussed later in this chapter. The European banking industry has been subject to major shocks since the mid-2000s, including the turmoil that ensued following the US subprime crisis of 2007–8, and the European sovereign debt crisis between 2010 and 2013. The former led to large losses and the failure and closure of many banks, and forced large-scale interventions by central banks and governments on an unprecedented scale (Goddard, Molyneux, and Wilson, 2009, 2010, 2014). Government interventions to deal with the financial crisis included: guarantees for bank liabilities; bank recapitalizations; asset support (measures to provide relief for troubled assets); and increased deposit insurance coverage. Between 2008 and 2016 the European Union’s European Commission approved €5 trillion (approximately 34 percent of EU gross domestic product (2016 nominal GDP)) in government support to the banking sector (EU State Aid Scoreboard, 2017). In 2008 alone, €3.5 trillion was approved, mainly in the form of guarantees, afterwards the main emphasis of state support shifted toward recapitalization and impaired asset relief. Major changes to deposit insurance schemes (increased limits of coverage) were also introduced in 2008. 5  Features of the overall White Paper on Completing the Internal Market were incorporated in the Single European Act, which entered into force on July 1, 1987 and set a deadline of December 31, 1992 for completion of the internal market. This was probably the most important early legislation impacting integration and deregulation across many sectors as it made it easier to introduce EU legislation (and therefore member state legislation) that took account of the free provision of services, free movement of capital and approximation of national legislation.

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Banking in Europe   1003 EU member states did not take up their full quota of approved aid. The amount of state support actually deployed between 2008 and 2016 stood at €1.94 trillion (around 13 percent of EU 2016 GDP, the equivalent of 4.5 percent of EU 2016 banking sector assets). Around €1.3 trillion took the form of guarantees and other liquidity measures, and the remainder (around €654 billion) took the form of recapitalizations and support to banks with impaired assets. Between October 2008 and the end of 2016, almost 300 decisions were taken regarding state support to the banking industry. The large-scale injection of state funds, coupled with an array of regulatory reforms aimed at bolstering capital and liquidity and curtailing excessive risk, was successful in averting a collapse of the banking system.6 By 2017, a substantial proportion of the aid granted since 2008 had been repaid to public authorities in the form of dividends, guarantee fees and interest (EU State Aid Scoreboard, 2017). From late 2009 through 2013, the aforementioned financial crisis evolved into a European sovereign debt crisis. Since the introduction of the euro in 1999, the financial sector (in both the Eurozone as well as in countries including the UK and Switzerland) experienced rapid expansion. At this time several southern European economies, including Greece, Italy, Portugal, and Spain, ran large current account deficits, in contrast to the surpluses generated in Germany and some other northern European countries (Arnold, 2012; Lane, 2012; Correa and Sapriza, 2014; Correa, Sapriza, and Zlate, 2016). Credit extended within the financial systems at the core of the Eurozone fueled property market price bubbles in several EU member states, including Ireland and Spain. Spiraling government deficits and debt, exacerbated by the bailouts of troubled banks, triggered a crisis of confidence, reflected in a widening of bond yields and credit default swap spreads. The first crisis hit Greece in May 2010. The Eurozone authorities and the International Monetary Fund (IMF) agreed a €110 billion loan, conditional on the implementation of tough austerity measures. Later in May, the European Financial Stability Facility (comprising a broad rescue package amounting to $1 trillion) was established with the aim of ensuring financial stability in the Eurozone. Following this, further support programs were approved for Ireland (€85 billion in November 2010) and Portugal (€78 billion in May 2011). This benefited many banks, which were substantial holders of sovereign debt. In some countries, however, banks were forced to raise large amounts of new capital, which impacted adversely on subsequent performance. In March 2013, Cyprus was awarded a €10 billion bailout to stabilize its financial system and finance a large fiscal deficit. The support provided to the aforementioned countries was relatively successful with Ireland and Portugal exiting their bailout programs in the summer of 2014. Other countries such as Greece and Cyprus, both managed to gain market access to sovereign bond financing over 2014–15. Eurozone ministers announced the end of the Greek debt crisis in June 2018. Spain never formally had a bailout package, but did rely on funding from the ECB for the establishment of a bank recapitalization fund. 6  Marquez, Correa, and Sapriza (2013), in a large cross-country study, find that more government support is linked to greater bank risk-taking, particularly between 2009 and 2010.

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1004   Banking Systems Around the World The Eurozone sovereign debt crisis has been described as a continuation of the global financial crisis of 2007–9 by alternative means. On the one hand, the perception that bank balance sheets remained contaminated by hidden or undeclared delinquent lending raised concerns over the implications for fiscal sustainability in the context of future bank bailouts. On the other hand, banks themselves were (and indeed continue to be) major investors in government debt, and recognition of the possibility that a euro member state might default on its debt and withdraw from the single currency heightened the prospects of additional bank failures. To address these concerns the EU announced in 2012 that it was to establish a banking union, which would entail pooling responsibility at EU level for the rescue of ailing banks. The aim being to break the symbiotic relationship that had developed between distressed banks and distressed member states. The banking union comprises a single supervisory mechanism (SSM) and a single resolution mechanism (SRM) for banks. In late 2015, the European Commission proposed the introduction of a European deposit insurance scheme (EDIS) as a further step to completing the banking union. The banking union applies to countries in the Eurozone, although non-Eurozone countries can also join. In October 2017, the European Commission announced further measures to facilitate greater financial sector integration. This included developing a fiscal backstop to the banking union. In the remainder of the chapter we provide an overview of the structure and performance of the European banking industry (section 32.2); a brief discussion of the global financial crises and its impact on European banks, together with coverage of the later Eurozone crisis (section 32.3); and a discussion of the key features of the banking union and the ongoing push to create a fully integrated banking and financial system throughout the Eurozone (section 32.4). Section 32.5 provides a summary.

32.2  Structure and Performance of European Banking 32.2.1  Deregulation and Integration European banking has changed dramatically since the passing of the First Banking Directive in 1977 (77/780/EEC). In response to financial deregulation, the creation of the single market in financial services and the introduction of a single currency, banks have increased the range of products and services offered to customers. This blurred the distinction between banks, investment firms, insurance companies, and other financial services firms. Market entry by foreign-owned banks led to increased competition in some segments of the financial services industry. This placed additional pressure on banks to reduce costs, and find ways of increasing revenues via the sale of new types of products and services. Since the passing of the First Banking Directive, EU legislation covering the banking system has been directed consistently toward boosting financial integration by reducing

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Banking in Europe   1005 barriers to cross-border bank ownership and activities. Deregulation of financial markets at member state level has also eroded the lines of demarcation between banks and nonbank financial firms, thus facilitating both domestic and cross-border competition. From the introduction of the single currency in 1999 to the start of the global financial crisis, wholesale and capital market-related bank activities showed clear signs of increasing integration, while retail banking remained somewhat fragmented (ECB, 2008). Retail banking and small business lending in Western Europe remained primarily nationally oriented, with only limited cross-border ownership or activity. In Eastern Europe, by contrast, there was extensive foreign ownership of retail banking. With regard to banking, the financial crisis constituted a major setback to the project of European financial integration (Sapir and Wolff,  2013). The scaling back of interbank lending sharply reduced the level of banking activity in the area where integration had been furthest advanced. The fragmentation of bank resolution authorities along national lines engendered divergence, as did home country bias in the arrangements for assistance to distressed banks. Overall, the financial crisis, “ . . . reduced the cross-border provision of financial services and, in particular, wholesale and securities-related activities. Banks have clearly been relying more on domestic than on foreign counterparties in their transactions” (ECB, 2010a, p. 32). During the 1990s and 2000s, many European banks expanded the scale of their operations, in some cases through mergers and acquisitions (M&A). Consolidation was motivated by the objectives of realizing scale and scope economies; reducing labor and other variable costs; cutting operational inefficiencies; and spreading risk through product or geographic diversification. Rapid growth in the loan portfolios of some banks was financed via the securitization of prospective cash flows from sources such as mortgages and credit card debt, which commonly took place off-balance sheet. Growth in European banks’ non-interest income reflected the growing use of securities-based financing by private sector companies, the increased demand by the household sector for insurance and personal pensions, and the investment in mutual funds. Changes embodied in the European Company Statute allowed banks to form single legal entities operating freely across the EU, and enabled the conversion of subsidiaries to branches. However, subsidiaries remained the predominant cross-border organizational form, suggesting that the benefits associated with risk spreading between various legal entities within a banking group are of strategic importance (ECB, 2007). The introduction of the Financial Services Action Plan between 1999 and 2004 provided further momentum toward increased integration of the banking system, and increased crossborder inter-connections between financial institutions. Technological advances also impacted on bank behavior through the proliferation of Internet banking and the emergence of new payments media. Technology revolutionized delivery systems, and led to the adoption of different business models by small and large banks (Goddard, Molyneux, and Wilson, 2001, 2010, 2014; Goddard et al., 2007). The growing emphasis on performance and shareholder value also encouraged many banks to reappraise their asset and liability management strategies. In the two decades preceding the global financial and sovereign debt crises, European banking was transformed by an array of developments including: globalization,

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1006   Banking Systems Around the World deregulation, technological change, as well as integration resulting from legislative changes specifically designed to create a European single banking market (Goddard, Molyneux, and Wilson,  2014). These forces impacted on the industrial structure of European banking. Between 1985 and 2007, the total number of banks declined substantially in all major countries. Over the same period the combined nominal total assets of French, German, Italian, Spanish, and UK banks increased by over 350 percent. In addition, in France, Greece, Italy, Spain, and Portugal, the number of bank branches increased owing to the lifting of branching restrictions. The number of branches declined in Belgium and the UK, where banks sought to increase efficiency by rationalizing branch networks (ECB,  2010b). Banking sector employment also increased by more than 11 percent over the same period, reaching 2.75 million by 2007 with German banks employing the largest number of staff (685,000), followed by the UK (463,000). Typically, employment in the banking industry accounts for around two-thirds of total financial sector employment. Another general trend since the 1970s has been the increased presence of female and part-time employees.7 Since the global financial crisis the integration process has stalled somewhat, perhaps not surprising given the extent of the adverse financial shock, which was then followed by the Eurozone sovereign debt crisis. The financial integration of Eurozone banking markets improved slightly in 2014. However, “The level of integration remains lower than before the financial crisis, which may reflect financial fragmentation as well as cross-country differences in the riskiness of banks and borrowers. The wedge between the borrowing costs paid by non-financial corporations (NFCs)—particularly small to medium-sized enterprises (SMEs)—in distressed and non-distressed countries has narrowed, but has not yet returned to pre-crisis levels, suggesting prevailing fragmentation” (ECB, 2015, p. 27). In fact, even by 2018, progress toward further integration in European banking remained somewhat muted.8 The area where there has been least success relates to integration in retail credit markets, mainly as a consequence of limited cross-border bank mergers and acquisitions (M&A) throughout the Eurozone and Europe more generally. According to the European Central Bank there is a need to facilitate more (and larger) cross-border bank consolidation in the Eurozone area as this is “. . . the only realistic path toward greater retail bank integration, which could improve risk sharing via credit markets as well as the functioning of the Monetary Union” (ECB, 2017a, p. 5). Figure 32.1 shows price and quantity indicators of financial sector integration highlighting some of the aforementioned trends. Following the rapid growth of European banking systems in the run-up to the financial crisis, the post-crisis period has been characterized by an ongoing rationalization 7  In the UK, for example, the top ten banks employed 288,100 staff in 2012, of which 60 percent were female. Around 37 percent of female employees, but only 4 percent of male employees, were part-time (British Bankers Association, 2012). 8  Emter, Schmitz, and Tirpák (2018) examine the reduction in cross-border banking in the European Union (EU) since the global financial crisis and note that cross-border claims of banks in the Euro Area and the rest of the EU fell by 25 percent over the period.

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Banking in Europe   1007 Price-based and quantity-based financial integration composite indicators 1.00

quantity-based financial integration composite indicator price-based financial integration composite indicator Lehman Brothers default

0.75 subprime crisis

0.50

sovereign crisis

euro introduction

0.25

0.00 Q1/95

OMT and banking union announcement

Q1/98

Q1/01

Q1/04

Q1/07

Q1/10

Q1/13

Q1/16

Figure 32.1  Price-based and Quantity-based Financial Integration Composite Indicators. Source: ECB (2017a, p. 6).

process driven by the ongoing pressure to increase efficiency. Most member states have witnessed a reduction in banking sector capacity, occurring mainly through “. . . a reduction in business volumes rather than the exit of firms from the market” (BIS, 2018, p. 1). This can be seen in Table 32.1 which shows an overall decline in Eurozone banking sector assets between 2008 and 2016, most noticeably in Germany, Ireland, Greece, Cyprus, and the Netherlands. For other banking sectors in the Eurozone and the EU, asset growth has been flat. The UK experienced a steep decline in the asset size of the banking sector. The Eurozone also experienced a sizable decline in bank numbers, dropping from 6,768 in 2008 to 5,073 in 2016 (ECB, 2017b; and Table 32.2). Concentration in the banking sectors of Eurozone member states typically tended to increase in countries which had major restructuring (such as Greece and Spain) as well as in relatively small countries (Malta and Lithuania). However, even in larger systems such as Italy and Germany, concentration increased over the period 2008–16. Overall, for the EU the average five-bank asset concentration level increased from 44 percent in 2008 to just over 47 percent in 2014, but has since declined. Greece has the most concentrated banking system (97 percent) and Germany the least (31 percent) (ECB, 2017b). Table 32.3 illustrates these structural trends by highlighting the five-bank assets concentration ratio and the Herfindahl index measures. The concentration trend has been fueled mainly by domestic M&A activity. As noted earlier, the global financial crisis halted cross-border M&A, which peaked in Europe in 2007, and since then the majority of banking sector consolidation has been forced by regulators to remove capacity. It remains an open question as to whether future largescale cross-border deals will materialize, albeit policymakers have set a future policy agenda where one aim is to promote this goal (ECB, 2017a). For this to happen, policymakers will have to consider reducing barriers to M&A activity (particularly in retail financial services). Such barriers include: difficulties in selling generic products across borders; differences in competition, employment legislation and practices, regulatory and

Credit Institutions

Foreign Branches

2008

2009

2010

2011

2012

2013

2014

2015

2016

2008

2009

2010

2011

2012

2013

2014

2015

2016

Belgium 49 Germany 1,882 Estonia 6 Ireland 472 Greece 36 Spain 282 France 672 Italy 729 Cyprus 137 Latvia 21 Lithuania 77 Luxembourg 120 Malta 23 Netherlands 266 Austria 771 Portugal 147 Slovenia 21 Slovakia 17 Finland 334 Eurozone 6,062

48 1,840 7 468 36 271 660 717 130 21 78 118 23 262 760 139 22 15 328 5,943

48 1,819 7 461 36 255 635 697 127 21 77 118 26 254 750 133 22 15 318 5,819

47 1,789 7 448 34 249 611 672 116 22 83 114 26 250 736 131 22 14 305 5,676

44 1,762 8 442 30 230 596 635 110 20 86 112 28 224 721 129 20 14 290 5,501

39 1,734 24 431 21 204 579 611 74 54 84 121 27 204 701 127 20 13 279 5,347

43 1,698 30 414 21 144 413 592 32 49 82 110 24 177 677 130 20 13 241 4,910

37 1,666 32 382 18 134 416 575 32 51 82 102 25 161 648 127 19 13 249 4,769

33 1,600 31 337 18 125 391 527 31 50 80 98 24 51 586 127 16 13 247 4,385

56 104 11 32 30 87 99 84 23 6 7 40 3 32 30 28 3 9 22 706

55 104 10 33 30 89 98 82 25 6 7 37 3 33 29 27 3 11 22 706

58 108 11 34 26 88 95 77 25 10 9 37 3 33 30 26 3 14 24 711

61 110 10 38 23 87 92 79 25 9 9 35 3 35 30 24 3 17 24 714

59 106 8 36 22 85 87 73 27 9 8 36 3 36 29 23 3 14 22 691

64 108 7 34 20 85 91 81 27 9 7 37 3 39 30 24 3 15 22 706

65 108 7 33 20 84 90 79 24 10 7 40 3 39 30 22 4 15 25 705

60 107 7 34 22 84 91 80 24 10 8 40 3 42 30 18 4 14 27 705

57 102 7 32 20 82 89 83 23 7 8 42 3 40 28 19 3 15 28 688

EU

8,383

8,237

8,062

7,868

7,747

7,331

7,111

6,648

983

976

983

990

965

977

984

981

964

8,570

Source: ECB (2017b, table 5, p. 72).

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Table 32.1  Number of Credit Institutions and Foreign Branches

Table 32.2  Total Assets of Domestic Banking Groups and Foreign-Controlled Subsidiaries and Branches Domestic Banking Groups (EUR billions)

2009

2016

2008

2009

2010

2011

2012

2013

2014

2015

2016

1,201 590 590 556 520 469 495 493 516 9,005 7,767 7,517 7,577 7,257 6,457 6,750 6,649 6,583 0 0 0 1 1 1 1 1 2 538 517 448 381 352 275 260 249 227 358 386 395 343 346 356 358 344 295 3,287 3,404 3,498 3,604 3,595 3,271 3,345 3,471 3,450 6,874 6,101 6,173 6,451 6,583 6,154 6,760 6,563 6,853 2,522 2,475 2,536 2,547 2,603 2,405 2,476 2,511 2,469 87 96 111 98 87 51 49 59 53 11 10 10 10 11 12 15 17 15 4 5 6 2 1 2 2 2 2 133 91 62 98 90 90 94 98 103 8 9 10 10 12 13 15 16 19 2,874 2,530 2,364 2,514 2,415 2,252 2,359 2,346 2,358 830 868 857 874 848 788 751 720 720 376 401 414 399 385 368 337 313 299 38 41 41 38 35 30 27 27 22 2 3 4 6 6 7 10 10 12 116 118 126 140 149 150 163 178 185 28,247 25,397 25,144 25,639 25,283 23,136 24,265 24,066 24,183

219 1,005 37 1,083 100 350 276 236 39 22 25 875 36 121 345 101 15 60 270 5,071

600 861 33 822 104 328 215 236 48 19 23 783 34 116 272 109 15 49 264 4,860

561 379 30 732 98 309 212 229 44 19 20 704 41 349 274 118 15 50 337 4,454

591 419 19 812 82 309 223 247 40 16 21 697 41 318 293 114 15 49 494 4,761

528 309 20 647 63 289 227 252 38 17 21 650 42 273 316 112 14 49 450 4,280

491 278 20 514 13 217 189 227 26 17 20 628 38 161 301 94 13 50 372 3,653

501 312 21 243 11 231 427 225 27 16 22 717 37 169 328 87 14 53 410 3,829

477 306 22 233 6 193 377 213 14 15 22 713 31 162 337 93 14 57 369 3,677

506 501 23 212 6 141 363 231 14 15 24 742 28 175 227 87 19 61 352 3,727

Source: ECB (2017b, table 6, p. 73).

2010

2011

2012

2013

2014

2015

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Belgium Germany Estonia Ireland Greece Spain France Italy Cyprus Latvia Lithuania Luxembourg Malta Netherlands Austria Portugal Slovenia Slovakia Finland Eurozone

2008

Foreign Subsidiaries and Branches

Herfindahl index for credit institutions1 (index ranging from 0 to 10,000)

Belgium Germany Estonia Ireland Greece Spain France Italy Cyprus Latvia Lithuania Luxembourg Malta Netherlands Austria Portugal Slovenia Slovakia Finland Eurozone EU

Share of total assets of the five largest credit institutions2 (percentage share of the five largest credit institutions)

2008

2009

2010

2011

2012

2013

2014

2015

2016

2008

2009

2010

2011

2012

2013

2014

2015

2016

1,881 191 3,120 661 1,172 497 681 307 1,017 1,205 1,714 309 1,236 2,167 454 1,114 1,268 1,197 3,160 676 648

1,622 206 3,090 714 1,183 507 605 298 1,085 1,181 1,693 310 1,250 2,034 414 1,150 1,256 1,273 3,120 649 629

1,439 301 2,929 700 1,214 528 610 410 1,125 1,005 1,545 343 1,181 2,049 383 1,207 1,160 1,239 3,550 688 669

1,294 317 2,613 647 1,278 596 600 407 1,030 929 1,871 346 1,203 2,067 423 1,206 1,142 1,268 3,700 710 685

1,061 307 2,493 632 1,487 654 545 410 1,007 1,027 1,749 345 1,313 2,026 395 1,191 1,115 1,221 3,010 677 662

979 266 2,483 674 2,136 719 568 406 1,645 1,037 1,892 357 1,458 2,105 405 1,197 1,045 1,215 3,080 689 674

981 300 2,445 677 2,195 839 584 424 1,445 1,001 1,818 330 1,648 2,131 412 1,164 1,026 1,221 3,310 730 692

998 273 2,409 678 2,254 896 589 435 1,443 1,033 1,939 321 1,620 2,104 397 1,215 1,077 1,250 2,730 720 677

1,017 277 2,406 644 2,332 937 572 452 1,372 1,080 1,938 260 1,599 2,097 358 1,181 1,147 1,264 1,790 697 661

81 23 95 50 70 42 51 31 64 70 81 30 73 87 39 69 59 72 83 44 44

77 25 93 53 69 43 47 31 65 69 80 29 73 85 37 70 60 72 83 44 44

75 33 92 50 71 44 47 40 64 60 79 31 71 84 36 71 59 72 84 47 47

71 34 91 47 72 48 48 39 61 60 85 31 72 84 38 71 59 72 81 47 47

66 33 90 46 79 51 45 40 63 64 84 33 74 82 36 70 58 71 79 47 47

64 31 90 48 94 54 47 40 64 64 87 34 76 84 37 70 57 70 84 47 47

66 32 90 48 94 58 48 41 63 64 86 32 81 85 37 69 56 71 80 48 47

65 31 89 46 95 60 47 41 68 65 87 31 61 85 36 72 59 72 75 48 46

66 31 88 44 97 62 46 43 66 67 87 28 80 85 34 71 61 73 66 48 46

Note: 1. The Herfindahl index (HI) refers to the concentration of banking business. The HI is obtained by adding the squares of the market shares of all the credit institutions in the banking sector. 2. Banking sector and individual figures are reported on an unconsolidated basis. Source: ECB (2017b, table 11, p. 81).

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Table 32.3  Concentration in European Banking Herfindahl index for credit institutions and share of total assets of the five largest credit institutions

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Banking in Europe   1011 supervisory policy; variation in consumer protection legislation, political interference; and a lack of consumer trust in foreign banks.

32.2.2  Profitability and Efficiency Europe has a varied and dynamic banking sector, highlighted by the Final Report of the High-level Expert Group on Reforming the Structure of the EU Banking Sector (the so-called Liikanen Report): The EU banking sector is diverse, which is valuable. Banking sectors differ substantially across Member States, in terms of size, market concentration, foreign ownership, asset and liability structure, supervision, credit cycle, and public involvement. Diversity strengthens the resilience of the banking system as it mitigates vulnerability to systemic interconnections and promotes effective competition. Diversity is explicitly protected by the EU treaty.  (Liikanen, 2012, p. 32)

Commercial banks traditionally depended upon interest margins as the main driver of profits. Profitability depended on banks’ ability to maintain a sizable gap between interest income and interest cost, while attempting to maximize operational efficiency. As banking systems were liberalized, competition in loan and deposit markets intensified. This was an observable trend from the early 1980s to the early 2000s in many European countries. Reductions in margins encouraged banks to augment their income (where possible) by diversifying into non-interest income, or non-traditional areas of business such as insurance and securities underwriting. Following the EU Second Banking Directive of 1989, non-interest income as a proportion of total income increased from 26 percent in 1989 to 41 percent in 1998 (ECB, 2000). Non-interest income has increased slightly since 2007, and has remained at a similar level, albeit with big variations across countries.9 The crisis of 2007–9 caused a rethink in the business models adopted by big banks. Prior to the crisis, such banks focused on the co-existence of investment and commercial banking, and the creation of complex and large corporate entities that sought to realize the various benefits associated with size. Post-crisis, the costs associated with ‘Too-Big-To-Fail (TBTF) bailouts heightened the policy debate concerning the relative benefits of bank size, and the influence of safety net subsidies on the behavior of large banks (Inanoglu et al., 2016). The role of large banks and recent regulatory proposals have directed renewed attention to the issue of economies of scale in banking and there is some evidence that scale economies remain important for large European banks (Beccalli, Anoli, and Borello, 2015). In addition to economies of scale, banks’ business models have also been 9  Eurozone fee and commission income has remained relatively flat since 2008 up to 2016, but trading income has increased from 2014. See ECB (2017b, p. 40).

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1012   Banking Systems Around the World driven by economies of scope and deregulation (Gambacorta and van Rixtel, 2013). The trend toward diversification adopted by large European banks is associated with increased consolidation that results in fewer, larger, and more complex banking conglomerates. Empirical evidence suggests significant benefits for banks that are potential TBTF candidates (Molyneux, Schaeck, and Zhou,  2014). A related (and substantial) strand of research has focused on diversification. Some studies have examined the risk implications of diversification in non-European banking industries (DeYoung and Torna, 2013; Engle et al., 2014; De Jonghe, Diepstraten and Schepens, 2015, Abedifar, Molyneux, and Tarazi, 2018). Such studies show that (when combined with traditional financial intermediation), non-interest activities generally contribute to higher stand-­ alone bank risk and systemic risk. Other recent European studies present mixed findings (Maudos, 2017; Saghi-Zedek, 2016). Post-crisis regulatory reforms in Europe have resulted in a range of restrictions on banks’ non-interest activities (particularly in higher-risk trading areas). These regulations, however, do not include explicit size restrictions. Instead they seek to reduce scope economies and eliminate implicit TBTF subsidies. Other proposed structural reforms that included explicit bank size restrictions in relation to the financial system as a whole or relative to GDP (Tarullo, 2012; Haldane, 2013) appear to have diminished as conditions in the banking industry have improved. The scope for banks to exploit economies of scale and scope will depend on any restrictions on size imposed by other regulations, such as the leverage rule in Basel III to be implemented by 2019 (see Chapter 2, this volume). The general recognition that a reliance on non-interest revenue, particularly securities trading and investment banking, creates risk for financial stability has resulted in reforms in the UK to “ring-fence” retail banking from investment banking, and in the EU to separate high-risk activities from low-risk deposit-taking within each banking group. Post-global financial crisis, it is noticeable that the business models of banks, particularly large institutions have changed: Broadly speaking, banks have reassessed their earlier ventures into trading activities as well as a growing dependence on wholesale sources of funding, in association with stricter capital and liquidity regulation. Use of deposit funding has increased, while businesses have tended to be repositioned toward less complex and less capital-intensive activities, including retail banking and, in some cases, wealth management. These patterns have been evident in the strategic changes implemented by many banks, and in their balance-sheet compositions and revenue mix. There has also been a re-focus on home market business or core foreign markets. (BIS, 2018, p. 14)

Changes to business models are also most noticeable for the largest (globally systemically important) banks (or G-SIBS) that have significantly reduced their investment banking and trading activities, particularly the Royal Bank of Scotland in the UK and the Union Bank of Switzerland and Credit Suisse in Switzerland. Advances in technology have substantially reduced the costs associated with the collection, storage, processing and transmission of data, and transformed the means

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Banking in Europe   1013 whereby customers gain access to banking services and products. Front-office innovation is reflected in the growth in number and usage of automated teller machines (ATMs), electronic funds transfer at the point of sale (EFTPOS), Internet banking, e-money and new FinTech services. FinTech services are offered by both traditional and new operators aiming to dis-intermediate traditional bank value chains (in foreign exchange, retail payments, retail/SME lending, wealth management, and so on). Back-office operations have also been transformed by the adoption of new internal systems, such as customer relationship management and business management technologies, core processing technologies and various support and integration technologies.10 Many of these innovations involve large set-up costs relative to marginal costs, and the impact is not always cost saving. Even if technology reduces costs, revenues might adversely be affected (customers might be unhappy with a new technology, and demand less service). The cost-to-income ratio provides a crude measure of cost efficiency. In the 1980s and 1990s, a cost-toincome ratio of around 70 percent was considered excessive, and indicative of a bank or system that was badly managed and relatively inefficient. By the mid-2000s, a ratio below 60 percent was considered respectable. By 2016, Eurozone bank cost-to-income ratios stood at a median of 58 percent with substantial country variation. This ratio exceeded 70 percent for German and Italian banks, and was around 70 percent in France. The high cost-to-income ratios in these countries is attributed in part to the higher cost of banks that focus on trading/investment banking as well as to their relatively fragmented banking markets.11 While bankers and industry analysts often focus on the cost-to-income ratio efficiency metric, academics have used more sophisticated modeling techniques to compute efficiency scores for banks. These more technical measures can be obtained via parametric or non-parametric statistical methods, allowing controls for variations in the mix of inputs, and of outputs. Berger and Humphrey (1997) review 133 earlier efficiency studies. In general, large banks are more efficient than their smaller counterparts, and there is greater potential for realizing cost savings by emulating best practice than by increasing size (scale economies) or product diversification (scope economies). Weill (2009) reports evidence that European integration has coincided with convergence in bank efficiency across countries. Using both parametric and non-parametric modeling approaches, Casu and Girardone (2010) report that bank efficiency has generally improved as a result of European integration. Closely related literature explores European bank productivity. Altunbas, Goddard, and Molyneux (1999) report that technical change reduced EU banks’ average costs during the 1990s, whereas Battese, Heshmati, and Hjalmarsson (2000) in a study of Swedish banks find that the cost-saving effects of technical change became exhausted, as “average” banks caught up with the industry best practice. Casu, Girardone, and Molyneux (2004) report that banks in some European countries benefited from productivity growth during the 1990s. Several studies suggest 10  Frame, Wall, and White, Chapter 9 in this volume, provide a detailed overview of technological changes in the banking industry. 11  See chart 2.31, ECB (2017b, p. 42).

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1014   Banking Systems Around the World deregulation often had a negative impact on bank productivity (Lozano-Vivas, 1998; Canhoto and Dermine, 2003). This is somewhat surprising, as studies for countries outside the US and Europe typically find that liberalization boosts productivity. Casu et al. (2016) investigate the total factor productivity growth of commercial banks in nine Eurozone countries between 1992 and 2009, allowing for heterogeneous technology and the presence of “technology gaps” between countries. The analysis suggests that, while technical improvements have occurred, there is variation between countries in the benefits to each banking industry. There are signs that all banking industries are converging toward use of the best available technology. The speed of convergence accelerated after the introduction of the single currency, but decelerated following the 2007–9 financial crisis. Other recent studies on European bank efficiency, perhaps unsurprisingly, continue to find a decline in efficiencies after the global financial crisis and around the timing of the Eurozone sovereign debt crisis. However, the observed declines are relatively modest (Matousek et al., 2015; Tsionas, Assaf, and Matousek, 2015). Other studies report a decline in productivity growth over a similar period (Degl’Innocenti et al., 2017). Galema and Koetter (2016) examine the efficiency features of Eurozone banks that started to be regulated under the Single Supervisory Mechanism (SSM), which commenced with the ECB overseeing around 100+ of the Euro Area’s largest banks from November 2014 onwards. They compare the performance of these systemically important banks with those (smaller) banks solely regulated by national authorities. Banks supervised under the SSM were more cost and profit inefficient and this typically tended to increase once under supervision by the ECB. As perhaps one might expect, substantial variations in European bank profitability persist although the double digit return-on-equity common for many banks in 2005–6 has not been repeated since the global financial crisis.12 Table 32.4 highlights profits trends in select Euro Area and other EU countries (as well as in the US). The table highlights the particularly low level of profits, suggesting that many banks are failing to cover their cost-of-capital. One can also see the impact of the sovereign debt crisis on Spain and Italy over 2011–13, with Italian banks yet to fully recover. The table also reveals the relatively better performance of US banks in recent years compared with all the largest European banking markets.

32.2.3  Competition and Risk Since the banking crisis there has been much discussion in both policy and academic circles as to which type of business model will yield the safest and most profitable banking system. According to Liikanen (2012), while the adverse effects of the crisis 12  Prior evidence suggests that there is significant persistence in bank profitability throughout the 1990s, but that this declines (as integration increases) following the introduction of the single currency and the Financial Services Action Plan (Goddard, Molyneux, and Wilson,  2004a, 2004b; Goddard et al., 2013).

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Banking in Europe   1015

Table 32.4  Bank Profitability—Return on Equity (%) 2001–02 2003–04 2005–06 2007–08 2009–10 2011–12 2013–14 2015–16 Eurozone Belgium France Germany Italy Luxembourg Netherlands Spain Other Europe Sweden Switzerland United Kingdom United States

6.3 11.8

5.1 14.7

10.7 20.4

3.7 7.8

0.1 8.3

7.1 10.5

14.2

14.9

13.7

14.3

16.1 16.3 19.7 17.1 15.7 12.5

3.6 −11.6 5.5 0.1 6.7 3.2 −9.0 14.7 3.9 17.1 −3.3 4.9 3.4

3.6 4.0 5.9 −0.7 2.7 8.9 3.8 8.3 5.8 7.8 7.7 4.8 2.2

0.2 1.9 3.6 2.3 −3.3 9.0 5.0 −12.4 4.2 12.0 4.7 2.6 8.2

3.2 6.8 4.7 2.4 −3.9 7.8 4.4 6.3 4.5 12.5 5.0 2.7 9.2

4.4 9.2 6.3 3.1 −1.7 7.0 7.4 5.8 3.9 12.7 4.0 2.2 9.3

Source: Adapted from BIS (2018, annex table 1.27, p. 104).

were universal, those banks that were “less resilient” typically relied heavily on short-term wholesale funding, excessive leverage and trading activity, and were characterized by excessive lending and weak corporate governance. The impact of the crisis on competition in banking, together with state support for ailing banks, has been debated widely. Until the 1980s there was a general consensus that competition between banks was damaging for financial stability. Competition encouraged excessive risk-taking on the assets (loans) side of banks’ balance sheets, increasing the likelihood of individual bank failure. More recently it has been suggested that competition may be helpful in reducing risk. According to theory, the allocation of bank assets is determined by solving a portfolio problem, emphasizing the liabilities side of the balance sheet. Upon confronting increased competition on the deposits side, banks tend to increase their rates in order to attract depositors. When paying higher deposit rates, neglecting the effects of competition in the loans market, earnings decline. In an attempt to recapture lost profits, banks tend to accept more risky investments. By contrast, when competition is restrained, banks exercise market power by paying lower deposit rates, and can thereby increase their profits. Banks that are subject to limited competition are less willing to invest in high-return–high-risk projects, reducing the likelihood of failure. The counter-argument that competition lowers risk is developed by Koskela and Stenbacka (2000) and Boyd and De Nicolo (2005), who develop a theoretical model of competition on both the deposits and loans sides of the balance sheet. Project risk is determined by the interest rates charged to borrowers. The portfolio problem is transformed into a contracting problem that is subject to moral hazard. Banks with market power charge lower rates on deposits and higher rates on loans. In this context, portfolio theory suggests that banks with market power have little incentive to take on risk, because they can earn monopoly profits without doing so. However, the contracting problem reverses this logic. Higher loan rates force bank borrowers to seek out more

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1016   Banking Systems Around the World risky projects, increasing portfolio risk for (monopoly) banks. By contrast, banks subject to competitive pressure offer lower loans rates in order to reduce moral hazard, and face reduced risk because their borrowers are less likely to pursue risky investments. In line with the competition stability view, by studying commercial, savings, and cooperative banks from ten European countries from 1999 to 2005, Schaeck and Cihák (2012) find that banks operating in more competitive environments have higher capital ratios. A later analysis by the same authors (Schaeck and Cihák, 2014) also finds that competition leads to soundness as it has a positive impact on the distance to default. Other research by Martinez-Miera and Repullo (2010) suggests that the relationship between competition and stability may be non-linear. Following the financial and sovereign debt crises, moral hazard issues concerning large banks too-big-, too-interconnected—or too-systemically-important-to-fail have been debated extensively in academic and policy circles (Strahan,  2013; Barth and Wihlborg, 2017; Chapter 4, this volume). Large banks obtain implicit (or explicit) subsidies via government safety nets, which encourage excessive risk-taking (O’Hara and Shaw, 1990; Stern and Feldman, 2004, 2009; Brown and Dinç, 2011; Demirgüç-Kunt and Huizinga, 2013; Chapter 4, this volume). Empirical evidence on the competition-fragility and competition-stability hypotheses is mixed (Turk-Ariss, 2010; Beck, De Jonghe, and Schepens,  2013; Jiménez, López, and Saurina,  2013). Using data for EU-25 countries, Uhde and Heimeshoff (2009) show that national banking market concentration has a negative impact on banking sector stability. Berger, Klapper, and Turk-Ariss (2009) examine market power and risk issues for a sample of more than 8,000 banks in twentythree developed countries for the period 1999–2005. Banks with more market power have lower risk exposure. The results provide some support for both the competitionfragility and competition-stability hypotheses: market power increases credit risk, but banks with more market power are less exposed to other types of risk. Liu, Molyneux, and Wilson (2013) construct measures of competition and economic activity using regional data to examine bank risk in ten European countries over the period 2000–8. They find a U-shaped relationship exists between regional bank competition and stability, implying that too little or too much competition is associated with bank fragility. Regional economic conditions are also found to play a significant role in  determining the stability of European banks. Leroy and Lucotte (2017) examine European listed banks between 2004 and 2013 and find that competition (using the Lerner index) increases individual bank risk but reduces systemic risk (measured in various ways, including Brownlees and Engle’s, 2017 SRISK measure). Overall, both the theoretical and the empirical evidence concerning the nature of the relationship between competition and risk in banking are inconclusive.

32.3  Crisis in European Banking The impact of the financial crisis on European banking began in the summer of 2007, with the failure of a structured investment vehicle (known as Rhineland) of IKB

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Banking in Europe   1017 Deutsche Industriebank, a small German lender. This event prompted a state-led rescue. Liquidity within the banking system evaporated, and overnight interest rates increased dramatically. An injection of liquidity into the Eurozone banking system was effective in averting any major bank failure. The outlook deteriorated dramatically in September 2008, however, following the collapse of the US investment bank Lehman Brothers (DeYoung, Chapter 31, this volume). These events created a crisis of confidence that brought the US and European banking systems perilously close to the brink of collapse in September and October 2008 (European Economy, 2009; Goddard, Molyneux, and Wilson, 2009). Between 2007 and 2010, the largest European banks reported huge credit losses. Several major UK and Swiss banks were among the largest casualties. Since October 2008 the capitalization of many of Europe’s largest banks was bolstered through injections of public funding, predominantly in the form of government purchase of preference shares and other quasi-equity instruments. In response to the crisis, most European governments announced a combination of loan guarantee schemes, bank rescue plans and fiscal stimulus packages (Pisani-Ferry and Sapir, 2010; Stolz and Wedow, 2010; ECB, 2011; EU State Aid Scoreboard,  2017). In terms of explicit government support packages, German banks had the largest recapitalization (€80bn), followed by the UK (€56bn), France (€40bn) and the Netherlands (€36.8bn). For guarantees, the Irish authorities provided support amounting to (€485bn), followed by Germany (€400bn), France (€320bn) and the UK (€280bn) (see ECB, 2009, table 2, p. 42). Since this wave of government-backed bank bailouts, recapitalization plans, liquidity injections, and credit guarantee schemes, there has been widespread concern over the business models of European banks. Large-scale banking rescues have raised serious worries about the social and economic costs of “too-big-to-fail” or “too systemically important to fail.” Such concerns are not confined to the largest banks: for example, the UK’s Northern Rock was bailed out with public funds because it was perceived to be of systemic importance. An important question for policymakers is whether limits should be placed on bank size, growth or concentration, to minimize the moral hazard concerns raised by banks having achieved TBTF or related status. However, as noted earlier there have been no such size restrictions imposed. Besides the actions of national governments, the European Commission has issued several communications concerning aspects of the crisis: the application of state aid rules to the banking sector; the treatment of banks’ impaired assets; the recapitalization of financial institutions; and the provision of restructuring aid to banks. Many of the regulatory or supervisory frameworks for dealing with problems in the financial system at an EU level were found to be deficient in key respects (Fonteyne et al., 2010). National approaches to crisis management and depositor protection proved inadequate, and sometimes produced adverse spillover effects on banking systems in other EU member states. There was a lack of cooperation and agreement over arrangements for sharing the burden of fiscal costs arising from the crisis. Effective regulation has also been constrained by a lack of transparency concerning banks’ business models. At first many governments took national measures to deal with the shock of the global financial crisis and it was apparent that an effective EU-wide response was lacking.

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1018   Banking Systems Around the World This led to broad policy debate on how to develop EU institutional arrangements so they are more effective when dealing with banking crises, and particularly in relation to the resolution of large cross-border banking groups. Recognition of these deficiencies led to the de Larosière Report (2009) that outlined issues surrounding the regulation and supervision of EU financial markets. An important area highlighted was the lack of a common rulebook across EU member states that led to inconsistencies in crisis management. The report proposed the establishment of a new systemic risk board to oversee financial markets as well as high-level coordination among national supervisors. The report recommended the creation of a European Systemic Risk Council (ESRC), chaired by the President of the European Central Bank. Most of the recommendations of the report were adopted by the EU and a new structure for European financial supervision evolved in late 2010 when the EU Council of Finance (ECOFIN) agreed upon the creation of a new European Systemic Risk Board (ESRB) and a European System of Financial Supervisors (ESFS), comprising three functional authorities: the European Banking Authority (EBA), the European Insurance and Occupational Pensions Authority (EIOPA) and the European Securities and Markets Authority (ESMA). The European System of Financial Supervisors facilitated greater cooperation between national supervisors and also helped develop a single rulebook for financial services. In 2012, the European Commission put forward a longer-term plan known as the Van Rompuy plan (Van Rompuy, 2012) establishing a banking union (see section 32.4). In addition, proposals for the set-up of a banking union were also driven by the serious fiscal challenges posed to various Eurozone countries as a result of the sovereign debt crisis. This started late 2009 when in various countries worries grew that problems in the banking sector would spill over into government financing, making it difficult for certain sovereigns to borrow in international markets. As noted earlier, evidence of the problems became apparent in April 2010 when Greece had to request emergency financing from the EU, the IMF and the ECB. These fiscal problems caused substantial stress in financial markets, which spread to peripheral Eurozone countries (namely, Ireland, Italy, Portugal, and Spain). These events pushed up sovereign bond yields and the EU, the IMF, and the ECB engineered a series of interventions to improve market liquidity with the aim of supporting banks that would feed through into growth and employment. In an attempt to deal with the sovereign debt crisis, the ECB established the Securities Market Programme (SMP) in May 2010, this enabled the ECB to purchase bonds (particularly sovereign bonds) on the secondary market (it was replaced by a similar scheme known as Outright Monetary Transactions (OMT) in September 2012). Also the ECB used longer-term refinancing operations where the ECB provided banks with central bank money longer than was the case in its normal refinancing activities. As the sovereign debt crisis developed, traditional LTROs were joined by refinancing activity of one year or longer. The most high-profile being two unconventional LTROs with a three-year maturity, which were implemented in December 2011 and February 2012. The loans amounted to some €1 trillion to the banking sector.

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Banking in Europe   1019 Later the ECB introduced Targeted Longer-Term Refinancing Operations (TLTROs) which are modified longer-term refinancing operations, intended to improve bank lending to the Eurozone’s non-financial sector. The first TLTRO program (TLTRO I) was undertaken in September 2014 with a maturity of up to four years. Banks’ borrowings are based on the total amount of their outstanding loans to the non-financial private sector. Four more TLTROs, each with a maturity of four years, were conducted in 2016 and March 2017. The interest rate for these loans (TLTRO II) corresponds to the Main Refinancing Operations (MRO) rate (namely, the standard one-week liquidity operations rate of the ECB). Finally, an asset purchase program (APP) was adopted at the beginning of 2015. This initially comprised three parts: the covered bond purchase program (CBPP 3; launched in October 2014), the asset-backed securities purchase program (ABSPP; launched in November 2014) and the public sector purchase program (PSPP; launched in March 2015). The corporate sector purchase program (CSPP) was added as a further component in June 2016. Under the APP, the ECB purchased around €60 billion worth of securities every month from March 2015 to March 2016; and €80 billion a month from April 2016 to March 2017. From January to April 2018 monthly purchasing volume totaled €30 billion. The APP is sometimes referred to as “quantitative easing.” The APP ended in December 2018. A number of studies highlight the impact of the ECB’s SMP and liquidity injections on the sovereign bond market and banking sector. For instance, De Pooter, Martin, and Pruitt (2018) find that the SMP helped lower the sovereign bond liquidity premium, and Eser and Schwaab (2016) find the interventions lowered yield spreads and volatilities of European sovereign bonds. Garcia-de Andoain et al. (2016) find that liquidity injections helped stabilize the overnight unsecured interbank market. Acharya, Pierret, and Steffen (2016) find that LTROs increased banks’ holding of risky sovereign debt. More recent studies have looked at the impact of the ECB’s actions on banks; for instance, Acharya et al. (2017) show that banks increased their lending to corporations following the Outright Monetary Transactions (OMT) program in mid-2012. Daetz et al. (2017) find that Eurozone firms did not increase investments even when their banks retained LTRO funds for a long period, although counterfactual evidence suggests that LTROs helped Eurozone corporations sustain investments better than European corporations outside the Eurozone.

32.4  New Regulatory Architecture and Banking Union There is a general recognition that before the global financial crisis European banks focused too heavily on high-risk non-interest revenue generation, particularly through securities trading and investment banking activity. In response, a series of major structural

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1020   Banking Systems Around the World proposals and legislation have aimed to reduce bank risk and minimize the likelihood of further taxpayer-financed bank bailouts.13 In the UK, the Independent Commission on Banking (or Vickers Commission after its Chair Sir John Vickers) was tasked with considering structural and non-structural reforms to the UK banking industry, to promote competition and financial stability. The recommendations of the Commission’s Final Report, published in September 2011, suggested that retail banking activity should be “ring-fenced” from wholesale and investment banking; systemically important banks with large retail banking activities should have a minimum 10 percent equity-to-assets ratio; contingent capital and debt should be available to absorb future losses; and risk management should become a self-contained, less-complex business for retail banking, but remain complex for wholesale and investment banking (Vickers, 2011). The recommendations of the Report were incorporated into the Banking Reform Act of 2014. The annual cost of these reforms to the UK economy are estimated to range between £1 billion and £3 billion, which compares favorably with an estimated annual cost of £40 billion in lost output following the financial crisis. Ring-fencing has to be in place for UK banks by January 1, 2019 (Britton et al., 2016). The recommendations made by the EU High-level Expert Group on Reforming the Structure of the EU Banking Sector chaired by Erkki Liikanen (Liikanen, 2012) suggests proprietary trading and other significant trading activities should be assigned to a separate legal entity if the activities to be separated amount to a significant share of a bank’s business. Banks now have to draw up and maintain effective and realistic recovery and resolution plans, as outlined in the EU’s Recovery and Resolution Directive adopted in May 2014. The Directive stipulates that the resolution authority is able to request wider separation than the mandatory level described above, if deemed necessary. Banks also have to build up a sufficiently large layer of bail-in debt, and such debt should be held outside the banking system. More robust risk weightings have been introduced in the determination of minimum capital standards, and there have been moves to try and ensure that risk is treated more consistently in internal models. Running in parallel with the aforementioned legislation has been the Fourth Capital Requirements Directive (2013) in the EU and Basel III (BCBS, 2010a, 2010b, 2013, 2014, 2017) internationally. The former seeks to implement the latter (with a few changes) into EU law and the new capital and liquidity requirements have to be in place by 2019. Banks hold capital as a buffer against losses as well as a resource for investment. Capital is predominantly built up through retained earnings and the issuance of equity and quasi-equity instruments. If losses occur, these are covered out of existing capital. 13  Risk-based tax schemes (or so-called bank levies) have also been introduced in a number of EU member states since the financial crisis. The United Kingdom introduced a permanent bank tax in January 2011, comprising initially of a tax of 0.04 percent on risky bank liabilities. Besides the UK, there has been a proliferation of bank levies in many other EU countries including Austria, Belgium, Cyprus, France, Germany, Hungary, Latvia, Netherlands, Portugal, Romania, Slovakia, Slovenia, and Sweden. Chronopoulos, Sobiech, and Wilson (2017) provide a summary of the risk-based schemes introduced in various countries. See also Celerier, Kick, and Ongena (2018) who present evidence that suggests that changes to taxation arrangements which increase the cost of leverage to banks, lead to an increase in equity relative to debt and a reallocation of assets toward loans (without any resultant increase in risk).

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Banking in Europe   1021 The role of capital in regulating banks has been widely studied (see, for instance, Demirgüç-Kunt, Detragiache, and Merrouche (2013) for an assessment of the role of capital over the crisis). There have also been attempts to investigate how changes in capital impact on bank risk-taking behavior. Some find that the level of bank equity (the highest quality type of capital) has little impact on reducing bank risk-taking (Delis and Staikouras, 2011; Abedifar, Molyneux, and Tarazi, 2013), whereas others find strong evidence that more capital reduces the probability of bank failure (Berger and Bouwman, 2013). Beltratti and Stulz (2012) and Demirgüç-Kunt, Detragiache, and Merrouche (2013) find that better capitalized banks improved stock performance during the financial crisis. More recently, Gropp et al. (2019) investigate the effects of higher capital requirements (by exploiting the 2011 capital exercise by the European Banking Authority) on bank lending to corporate and retail customers. The results of the empirical analysis suggest the presence of a strong link between bank capital and lending. This is particularly evident for corporates that have a high dependence on external finance. The capital rules as set out in Basel III and also the EU’s Fourth Capital Requirements Directive (2013) relate to weightings aligned to the riskiness of bank assets and offbalance-sheet items. As such, the regulatory classification of the riskiness of particular bank assets and off-balance-sheet activities should accurately reflect their individual and combined risks. Overall risk-weightings should be sensitive to the portfolio risks faced by banks and reforms to the rules were expected to boost bank capital. Supportive empirical evidence is limited in this regard. Using a sample of large banks from twentyone OECD countries, Mariathasan and Merrouche (2014) find that reported bank-risk levels were lowered after the introduction of new capital rules (Basel II internal ratingsbased approach). In another cross-country study covering forty-one countries (including banks from Europe) Vallascas and Hagendorff (2013) also demonstrate that that riskweights assigned to bank assets do not reflect overall bank portfolio risks. In fact, the Basel Committee have revised the earlier risk scheme to try and deal with these inconsistencies (BCBS, 2017). Capital regulations are put in place to try and ensure that banks have sufficient resources to cover losses overall. However, even if banks have sufficient capital they may at times be faced with extreme short-term financial pressures. A short-term liquidity crisis (such as the inability of banks to pay depositors on demand) can rapidly turn into a solvency (capital) crisis. Therefore, together with capital regulations, policymakers have sought to strengthen liquidity standards since the financial crisis (BCBS, 2010b, 2013, 2014). A study by Chiaramonte and Casu (2017) models the link between capital, liquidity, and bank distress for a large sample of EU banks, using various logistic probability models. The authors find that the likelihood of bank failure and distress decreases with increased liquidity. The EU Fourth Capital Requirement Directive (2013) also seeks ongoing reform of bank corporate governance in order to strengthen boards and management; promote the risk management function; amend compensation for bank management and staff; improve risk disclosure; and strengthen sanctioning powers. For executive pay, new EU rules stipulate that the variable part of total compensation cannot exceed 100 percent of

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1022   Banking Systems Around the World the fixed component. This is tougher than rules in the UK introduced by the Remuneration Code in 2009 (FSA, 2009). This code compels executives to defer a larger proportion of their bonuses (at least 50 percent) for three years. Work on the impact of these regulations is now emerging, for instance, Kleymenova and Tuna (2017) examine the influence of the UK and EU regulations and find that the market reacted positively to the Remuneration Code, but negatively to the EU bonus cap. UK banks also deferred more bonuses and reduced risk, although executive compensation became more complex. Evidence on Europe is further confirmed by Díaz, García-Ramos, and García Olalla (2017) who also find that the EU bonus cap legislation was perceived negatively by investors.

32.4.1  European Banking Union In June 2012, the European Council outlined proposals to create a European banking union as part of a program aimed toward strengthening the resilience of the European financial system (European Council,  2012; Dermine,  2013; Véron,  2013; Véron and Wolff, 2013). By addressing the entanglement of non-performing bank debt with sovereign debt, the proposals for the banking union are designed to tackle a fundamental cause of the ongoing European financial and sovereign debt crises. The banking union comprises three pillars. First, responsibility for bank supervision is undertaken by the ECB for Eurozone banks. Second, common mechanisms are instituted for the effective resolution of ailing banks and particularly large cross-border institutions. Third, common arrangements are to be put in place for the insurance of customer deposits. The first pillar of banking union involved the transfer of supervisory responsibilities for around 120 banks deemed to be “significant,” from national supervisors to a Single Supervisory Mechanism (SSM) operated by the European Central Bank (ECB). The objective is to implement a single harmonized supervisory rulebook based on Basel III, rather than divergent national arrangements. Differences in standards applied at the national level lead to differences between countries in the availability and cost of credit, inhibiting the emergence of an integrated market in financial services. National supervision inhibits or distorts cross-border capital flows: in a crisis, banks with subsidiaries abroad are encouraged by their home-country supervisors to repatriate capital or liquidity; while subsidiaries of foreign banks are encouraged by their host-country supervisors not to repatriate funds to their parent banks abroad (Gros, 2012). The initial criteria for a bank to qualify for direct ECB supervision were one or more of the following: assets above €30 billion; assets above €5 billion and 20 percent of GDP in the EU member state in which the bank is located; one of the top three banks in the state in which the bank is located; significant cross-border activity; or recipient of bailout assistance. The role of the European Banking Authority (EBA) was adapted to the new regulatory arrangements and, as mentioned in the previous section, new rules on capital regulation (including the EU Capital Requirements Regulation and the Fourth Capital Requirements Directive CRD IV) have come into force (effectively implementing Basel III into European legislation). Prior to the establishment of the SSM in 2014,

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Banking in Europe   1023 the ECB undertook an asset quality review (AQR) of the banks that would fall under its jurisdiction. The AQR was a key element in establishing the ECB’s supervisory credibility, and in dealing with legacy issues of undeclared non-performing assets, which may constitute a major barrier to the implementation of Pan-European resolution and deposit insurance arrangements. At this early stage there were concerns about the ECB’s lack of financial resources to recapitalize banks whose balance sheets were revealed to contain gaps, and the lack of legal authority to enforce either recapitalization by other means or resolution. However, it seems that these concerns were overblown and the ECB (to date) has had a strong and credible supervisory track record. Some have questioned the regulatory focus of the ECB on the largest systemically important banks. If the ECB does not exercise supervisory responsibility over small banks, it is also (in theory) debarred from providing liquidity or emergency support. However, small bank failure has been a source of systemic risk in various countries, evidenced by the role of the Spanish savings banks, or the small German lender Hypo Real, in the financial and sovereign debt crises (Beck, 2012; Wyplosz, 2012). Finally, potential tensions may emerge between the ECB’s dual responsibilities for price stability through monetary policy on the one hand, and financial stability through supervision of the banking system on the other. With respect to the latter Schoenmaker (2013) advocates a separation of the functions of macro-prudential (systemic) and micro-prudential (individual bank) supervision within the ECB. The second pillar, a Pan-European resolution scheme to be mainly funded by the banks, aims to provide a mechanism for the orderly shutdown of non-viable banks, so minimizing the likelihood of taxpayer-funded bank bailouts. Features of the resolution scheme are incorporated into the Bank Recovery and Resolution Directive (BRRD) that came into force on January 1, 2015, which is applicable to all credit institutions and most investment firms, including financial groups.14 The Directive requires firms to make “living wills”; affords supervisors early intervention powers; specifies minimum harmonized resolution tools (including the power to sell businesses to third-parties, to transfer a business to a state-owned bridge institution, or “bad” assets to a publicly owned asset management firm); requires institutions to issue bail-in debt that can convert to equity; requires EU member states to set up pre-funded resolution funds; and configures national deposit guarantee schemes for resolution-funding purposes. From January 1, 2016, the bail-in requirements for banks in resolution under the Bank Resolution and Recovery Directive entered into force in all member states that had not already implemented them in 2015. Resolution contributions from the Single Resolution Fund can only be made after a bail-in of at least 8 percent of the bank’s total liabilities. This can require the conversion of senior debt and uncovered (uninsured) deposits. Any contribution of the Fund is subject to a State Aid Decision by the Commission.15

14  See World Bank (2017) for a detailed evaluation of the BRRD. 15  State aid: How the EU rules apply to banks with a capital shortfall—Factsheet, Brussels, June 25, 2017. See http://europa.eu/rapid/press-release_MEMO-17-1792_en.htm.

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1024   Banking Systems Around the World The recent development of using bail-in debt to help refinance a bank when in financial difficulties has had a somewhat mixed impact.16 In the run-up to the introduction of tougher bail-in laws under the BRRD, which came into force in January 2016, regulatory authorities in various countries used such approaches to resolve troubled banks. In Italy in late 2015, four small regional banks, Banca Eutiria, Banca Marche, Carichieti, and Carife had to be supported to the amount of €3.6 billion euros from a fund financed by the country’s healthy lenders. That move caused political uproar because many of the banks’ junior bonds had been sold to retail investors as savings products, including one pensioner who later committed suicide. Retail investors were generally unaware of the risks posed by holding such bonds. Senior bondholders and depositors were protected in this case. A rescue package announced in November forced losses on some retail investors after the European Union rejected an alternative scheme that would have spared them, saying it violated EU state aid rules. Other bail-ins that have also been somewhat controversial include the December 2015 heavy losses imposed on nearly €2bn of senior bondholders at the Portuguese bank, Novo Banco, the bank that emerged from the restructuring of Banco Espírito Santo. This controversial move prompted threats of lawsuits from some major international investors. Also bond bail-ins have occurred for the major Greek banks in 2015 and depositor bail-ins in 2012, all of which have not been politically popular. It still remains to be seen whether bail-ins will be an effective resolution tool in the case of major bank failure (Honohan, 2017; Philippon and Salord, 2017). In Europe, existing insolvency frameworks are fragmented along national lines, and major reform would be required for a single resolution scheme to be established along the lines of prompt corrective action (PCA) in the US.17 Banking systems in Europe, as noted in section 32.1 (see Table 32.3) are highly concentrated, and TBTF moral hazard is likely to be pervasive. Sapir and Wolff (2013) argue that broader steps in the direction of European financial integration are required. The fragmentation of retail banking along national lines raises barriers to the creation of an effective pan-European resolution scheme, because it increases the exposure of banks to shocks at the national level, and limits the options for cross-border merger as a means of achieving resolution. The national orientation of most European banks also translates into a bias toward lending to their own governments, or providing funds for state-sponsored projects that are not financially or commercially viable. In exchange, implicit or explicit guarantees offered to banks by national governments effectively subsidize the banks’ funding costs. All of this strengthens the dangerous ties between banks and sovereigns, to the detriment of 16  Cutura (2018) finds that bank bonds subject to BRRD bail-in carry a bail-in premium in the form of a higher yield spread. This bail-in premium is more pronounced for non-GSIB banks and banks located in peripheral European countries. 17  PCA has provided extensive experience of bank resolution; but a report by the US Government Accountability Office suggests that PCA did not always operate effectively during the financial crisis, and recommends that additional early warning triggers (related to asset quality and asset concentration) be adopted (US Government Accountability Office, 2011).

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Banking in Europe   1025 the prospects for financial stability and resolution of the debt crisis. Acharya (2012) identifies the need to curb excessive sovereign borrowing from home-country banks as a further prerequisite (and as a natural counterpart to the banking union) for addressing the crisis. Realistic (rather than zero-) risk weightings should be applied to sovereign debt on banks’ balance sheets, and sovereign credit risk should be recognized in the application of liquidity requirements in bank regulation. Limits on individual bank lending to a single sovereign borrower could be imposed. The cases of countries such as Ireland and Spain during the financial and sovereign debt crises demonstrate that existing national deposit insurance and resolution funds can rapidly be depleted, creating a need for government support which, in turn, pushes sovereigns in the direction of insolvency. The third pillar of the banking union is the creation of a European deposit insurance scheme (EDIS) that would operate, along with the resolution fund, under a common resolution authority. This pillar, however, is hugely controversial because it implies a form of debt mutualization, whereby deposit protection funded by a member with an orderly banking system would be used to protect depositors in a country with a failing banking system. The question whether an effective banking union can be achieved in a gradual manner with the implementation of the first and second pillars and the third (EDIS) still appears some way off. However, the European Commission in October 2017 announced further measures with regard to the introduction of the banking union which included: accelerating the introduction of EDIS (planned to be in place by 2024); a package of measures aimed at reducing the level of existing NPLs and preventing the build-up of NPLs in the future; a fiscal backstop to the banking union; measures to promote the issuance of sovereign bond-backed securities; and other proposals aimed at ensuring high quality bank/financial firm supervision.18 It seems that the introduction of the banking union is on track and it does not look like the UK leaving the EU, by an expected 2019, will derail the process. In May (2017) the ECB outlined its financial stability assessment of “Brexit,” where they argue that “it is likely to have limited implications for the Eurozone economy and financial stability” (ECB,  2017c, p. 7). This view was ­further confirmed by the ECB’s President Mario Draghi when he testified before the European Parliament’s Economic and Monetary Affairs Committee in Brussels, Belgium on September 24, 2018.19 Having said this, Brexit could have a sizable adverse impact on UK banks, given that approximately 25 percent of their revenue is believed to be in some way linked to EU clients. Major banks with significant wholesale activities in the Eurozone are considering various passporting requirements post-Brexit, and there has already been movement of key trading parts of various institutions to Frankfurt and Paris.

18  See http://europa.eu/rapid/press-release_IP-17-3721_en.htm?locale=en. 19 See https://www.reuters.com/article/us-britain-eu-ecb/ecbs-draghi-sees-muted-impact-to-eurozone-from-brexit-idUSKCN1M41ND.

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1026   Banking Systems Around the World

32.5 Summary This chapter focuses on the evolution of the banking industry in the European Union since the signing of the Treaty of Rome in 1957 to the present day. Particular attention is paid to the operating environment since the global financial and sovereign debt crises. The aforementioned crises have had an adverse impact on the banking sector integration process and bank profitability remains low by historical standards. The EU has introduced a wide range of reforms aimed at boosting banking (and financial sector) stability including new capital and liquidity requirements (in line with those set out under Basel III) as well as new governance rules for banks. It has also set out a roadmap for the establishment of a banking union comprising three pillars: the single supervisory mechanism (SSM) including ECB oversight of the largest banks; a single resolution mechanism (SRM) to deal with troubled banks; and a single European deposit insurance scheme (EDIS). The EU is also continuing its ongoing push to create a fully integrated banking and financial services industry throughout the Eurozone. A major challenge for the industry relates to restoring profitability back to pre-crises levels. This will inevitability require greater attention to improving efficiencies and, where possible, boosting income. At present many banks remain encumbered by regulatory demands that, while helping their solvency, act as a drag on performance. Many of the largest institutions are yet to fully implement the (ring-fencing) separation of their retail and investment banking activities. It remains an open question as to how this impacts on bank performance going forward. Moreover, the impact of Brexit may force large securities trading banks to contemplate relocating from London to other major financial centers (such as Frankfurt and Paris) within the Eurozone. Overall, it seems likely, given the regulatory and economic environment, that European bank performance will be subdued for some time to come.

References Abedifar, P., Molyneux, P., and Tarazi, A. (2013). “Risk in Islamic Banking,” Review of Finance, 17, 2035–96. Abedifar, P., Molyneux, P., and Tarazi, A. (2018). “Non-interest Income and Bank Lending,” Journal of Banking & Finance, 87, 411–26. Acharya, V. (2012). “Banking Union in Europe and Other Reforms,” in T. Beck (ed.), Banking Union for Europe: Risks and Challenges (London: Centre for Economic Policy Research), 43–52. Acharya, V., Eisert, T., Eufinger, C., and Hirsch, C. (2017). “Whatever It Takes: The Real Effects of Unconventional Monetary Policy,” CEPR Discussion Paper Number DP12005. Acharya, V., Pierret, D., and Steffen, S. (2016). “Lender of Last Resort versus Buyer of Last Resort—Evidence from the European Sovereign Debt Crisis,” Working Paper. Altunbas, Y., Goddard, J., and Molyneux, P. (1999). “Technical Change in Banking,” Economics Letters, 64, 215–21.

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Banking in Europe   1027 Arnold, I.J.M. (2012). “Sovereign Debt Exposures and Banking Risk in the Current EU Financial Crisis,” Journal of Policy Modelling, 34, 906–20. Bank for International Settlements (2018). “Structural Changes in Banking After the Crisis,” Report prepared by a Working Group established by the Committee on the Global Financial System (CGFS), No. 60, Bank for International Settlements, Basel. Barth, J. and Wihlborg, C. (2017). “Too Big to Fail: Measures, Remedies, and Consequences for Efficiency and Stability,” Financial Markets, Institutions & Instruments, 26, 175–245. Battese, G.E., Heshmati, A., and Hjalmarsson, L. (2000). “Efficiency of Labour Use in the Swedish Banking Industry: A Stochastic Frontier Approach,” Empirical Economics, 25, 623–40. BCBS (Basel Committee on Banking Supervision) (2010a). “Basel III: A Global Regulatory Framework for More Resilient Banks and Banking Systems,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel. BCBS (2010b). “Basel III: International Framework for Liquidity Risk Measurement, Standards and Monitoring,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel (revised June 2011). BCBS (2013). “Basel III: The Liquidity Coverage Ratio and Liquidity Risk Monitoring Tools,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel. BCBS (2014). “Basel III: The Net Stable Funding Ratio,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel. BCBS (2017). “Basel III: Finalising Post-Crisis Reforms,” Basel Committee on Banking Supervision, Bank for International Settlements, Basel. Beccalli, E., Anoli, M., and Borello, G. (2015). “Are European Banks Too Big? Evidence on Economies of Scale,” Journal of Banking & Finance, 58, 232–46. Beck, T. (2012). “Why the Rush? Short-term Crisis Resolution and Long-term Bank Stability,” in T.  Beck (ed.), Banking Union for Europe: Risks and Challenges (London: Centre for Economic Policy Research), 35–42. Beck, T., De Jonghe, O.G., and Schepens, G. (2013). “Bank Competition and Stability: CrossCountry Heterogeneity,” Journal of Financial Intermediation, 22, 218–44. Beltratti, A. and Stulz, R.M. (2012). “The Credit Crisis Around the Globe: Why Did Some Banks Perform Better?” Journal of Financial Economics, 105, 1–17. Berger, A.N. and Bouwman, C.H.S. (2013). “Bank Liquidity Creation,” The Review of Financial Studies, 22, 3779–837. Berger, A.N. and Humphrey, D.B. (1997). “Efficiency of Financial Institutions: International Survey and Directions for Further Research,” European Journal of Operational Research, 98, 175–212. Berger, A.N., Klapper, L.F., and Turk-Ariss, R. (2009). “Bank Competition and Financial Stability,” Journal of Financial Services Research, 35, 99–118. Boyd, J.H. and De Nicolo, G. (2005). “The Theory of Bank Risk Taking and Competition Revisited,” Journal of Finance, 60, 1329–43. British Bankers Association (2012). Annual Abstract of Statistics, 29 (London: British Bankers Association). Britton, K., Dawkes, L., Debbage, S., and Idris, T. (2016). “Ring-fencing: What Is It and How Will It Affect Banks and Their Customers?” Bank of England Quarterly Bulletin, Q4, 164–72. Brown, C.O. and Dinç, I.S. (2011). “Too Many to Fail? Evidence of Regulatory Forbearance When the Banking Sector is Weak,” Review of Financial Studies, 24, 1378–405.

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

1028   Banking Systems Around the World Brownlees, C. and Engle, R.F. (2017). “SRISK: A Conditional Capital Shortfall Measure of Systemic Risk,” Review of Financial Studies, 30, 48–79. Campos, N., Coricelli, F., and Moretti, L. (2014). “Economic Growth and Political Integration: Estimating the Benefits from Membership in the European Union Using the Synthetic Counterfactuals Method,” IZA Institute of Labor Economics Discussion Paper No. 8162, April, IZA, Bonn. Campos, N., Coricelli, F. and Moretti, L. (2016). “Further Results. Deep Integration and Economic Growth. Counterfactual Evidence from Europe,” mimeo. Canhoto, A. and Dermine, J. (2003). “A Note on Banking Efficiency in Portugal, New vs. Old Banks,” Journal of Banking & Finance, 27, 2087–98. Casu, B. and Girardone, C. (2010). “Integration and Efficiency Convergence in EU Banking Markets,” Omega, 38, 260–7. Casu, B., Girardone, C., Ferrari, A., and Wilson, J.O.S. (2016). “Integration, Productivity and Technological Spillovers: Evidence for Eurozone Banking Industries,” European Journal of Operational Research, 255, 971–83. Casu, B., Girardone, C., and Molyneux, P. (2004). Productivity Change in European Banking: A Comparison of Parametric and Non-Parametric Approaches, Journal of Banking & Finance, 28, 2521–40. Celerier, C., Kick, T., and Ongena, S. (2018). “Taxing Bank Leverage: The Effects on Bank Capital Structure, Credit Supply and Risk-Taking,” mimeo. Chiaramonte, L. and Casu, B. (2017). “Capital and Liquidity Ratios and Financial Distress. Evidence from the European Banking Industry,” British Accounting Review, 49, 138–61. Chronopoulos, D.K., Sobiech, A.L., and Wilson, J.O.S. (2017). “Future Issues in Bank Taxation,” UK Financial Conduct Authority Future Horizons Expert Paper, April, available at: https:// fca.org.uk/publication/research/future-issues-bank-taxation.pdf. Correa, R. and Sapriza, H. (2014). “Sovereign Debt Crises,” in A.N.Berger, P. Molyneux, and J.O.S. Wilson (eds.), The Oxford Handbook of Banking, 2nd edn (Oxford: Oxford University Press), 737–55. Correa, R., Sapriza, H., and Zlate, A. (2016). “Liquidity Shocks, Dollar Funding Costs, and the Bank Lending Channel During the European Sovereign Crisis,” Federal Reserve Bank of Boston Risk and Policy Analysis Unit Working Paper No. 16-04. Cutura, J. (2018). “Debt Holder Monitoring and Implicit Guarantees: Did the BRRD Improve Market Discipline?” mimeo. Daetz, S.L., Subrahmanyam, M.G., Tang, D.Y., and Wang, S.Q. (2017). “Did ECB Liquidity Injections Help the Real Economy?” Working Paper, available at: https://ssrn.com/ abstract=2915800. De Jonghe, O., Diepstraten, M., and Schepens, G. (2015). “Banks’ Size, Scope and Systemic Risk: What Role for Conflicts of Interest?” Journal of Banking & Finance, 61, S3–S13. de Larosière Report (2009). “High-Level Expert Group on Financial Supervision in the EU,” 25 February, European Union, Brussels. De Pooter, M., Martin, R.F., and Pruitt, S. (2018). “The Liquidity Effects of Official Bond Market Intervention,” Journal of Financial and Quantitative Analysis, 53, 243–68. Degl’Innocenti, M., Kourtzidis, S.A., Sevic, Z., and Tzeremes, N.G. (2017). “Bank Productivity Growth and Convergence in the European Union During the Financial Crisis,” Journal of Banking & Finance, 75, 184–99. Delis, M.D. and Staikouras, P.K. (2011). “Supervisory Effectiveness and Bank Risk,” Review of Finance, 15(3), 511–43.

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Banking in Europe   1029 Demirgüç-Kunt, A., Detragiache, E., and Merrouche, O. (2013). “Bank Capital: Lessons from the Financial Crisis,” Journal of Money, Credit and Banking, 45, 1147–64. Demirgüç-Kunt, A. and Huizinga, H. (2013). “Are Banks Too-Big-To-Fail or Too-Big-ToSave? International Evidence from Equity Prices and CDS Spreads,” Journal of Banking & Finance, 37, 875–94. Dermine, J. (2006). “European Banking Integration: Don’t Put the Cart before the Horse,” Financial Markets, Institutions and Instruments, 15, 57–106. Dermine, J. (2013). “Banking Regulations after the Global Financial Crisis, Good Intentions and Unintended Evil,” European Financial Management, 19, 658–74. DeYoung, R. and Torna, G. (2013). “Nontraditional Banking Activities and Bank Failures During the Financial Crisis,” Journal of Financial Intermediation, 22, 397–421. Díaz, B., García-Ramos, R., and García Olalla, M. (2017). “Shareholder Wealth Responses to European Legislation on Bank Executive Compensation,” Journal of Economic Policy Reform, 20, 1–21. Emter, L., Schmitz, M., and Tirpák, M. (2018). “Cross-Border Banking in the EU Since the Crisis: What is Driving the Great Retrenchment?” European Central Bank Working Paper No. 2130. Engle, R., Moshirian, F., Sahgal, S., and Zhang, B. (2014). “Non-interest Income and Systemic Risk: The Role of Concentration,” Centre for International Finance and Regulation (CIFR) Research Working Paper No. 015/2014 (April). Eser, F. and Schwaab, B. (2016). “Evaluating the Impact of Unconventional Monetary Policy Measures: Empirical Evidence from the ECB’s Securities Markets Programme,” Journal of Financial Economics, 119, 147–67. EU State Aid Scoreboard (2017). Available at: http://ec.europa.eu/competition/state_aid/ scoreboard/index_en.html#tables. European Central Bank (2000). “EU Banks’ Income Structure,” Banking Supervision Committee, April, ECB, Frankfurt. European Central Bank (2007). “Financial Integration in Europe,” March, ECB, Frankfurt. European Central Bank (2008). “Financial Integration in Europe,” April, ECB, Frankfurt. European Central Bank (2009). “Financial Integration in Europe,” April, ECB, Frankfurt. European Central Bank (2010a). “Financial Integration in Europe,” April, ECB, Frankfurt. European Central Bank (2010b). “EU Banking Structures,” September, ECB, Frankfurt. European Central Bank (2011). “Financial Stability Review,” June, ECB, Frankfurt. European Central Bank (2015). “Financial Integration in Europe,” April, ECB, Frankfurt. European Central Bank (2017a). “Financial Integration in Europe,” May, ECB, Frankfurt. European Central Bank (2017b). “Report of Financial Structures,” October, ECB, Frankfurt. European Central Bank (2017c). “Financial Stability Review,” May, ECB, Frankfurt. European Council (2012). “Report by the President of the European Council, Herman Van Rompuy, Towards a Genuine Economic and Monetary Union,” June, European Council, Brussels. European Economy (2009). “Economic Crisis in Europe: Causes, Consequences and Responses,” European Economy, 2, European Commission, Brussels. Financial Services Authority (FSA). (2009). Reforming Remuneration Practices in Financial Services (London: Financial Services Authority). Fonteyne, W., Bossu, W., Cortavarria-Checkley, L., Giustiniani, A., Gullo, A., Hardy, D., and Kerr, S. (2010). “Crisis Management and Resolution for a European Banking System,” IMF Working Paper No. 10/70.

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1030   Banking Systems Around the World Galema, R. and Koetter, M. (2016). “European Bank Efficiency and Performance: The Effects of Supranational versus National Bank Supervision,” in T. Beck and B. Casu (eds.), The Palgrave Handbook of European Banking, Chapter 11 (London: Palgrave Macmillan, 257–92). Gambacorta, L. and van Rixtel, A. (2013). “Structural Bank Regulation Initiatives: Approaches and Implications,” Bank for International Settlements (BIS) Working Paper No. 412S. Garcia-de Andoain, C., Heider, F., Hoerova, M., and Manganelli, S. (2016). “Lending-of-LastResort Is as Lending-of-Last-Resort Does: Central Bank Liquidity Provision and Interbank Market Functioning in the Euro Area,” Journal of Financial Intermediation, 28, 32–47. Goddard, J., Liu, H., Molyneux, P., and Wilson, J.O.S. (2013). “Do Bank Profits Converge?” European Financial Management, 19, 345–65. Goddard, J., Molyneux, P., and Wilson, J.O.S. (2001). European Banking: Efficiency, Technology and Growth (Chichester: John Wiley and Sons). Goddard, J., Molyneux, P., and Wilson, J.O.S. (2004a). “Dynamics of Growth and Profitability in Banking,” Journal of Money, Credit and Banking, 36, 1069–90. Goddard, J., Molyneux, P., and Wilson, J.O.S. (2004b). “The Profitability of European Banks: A Cross-Sectional and Dynamic Panel Analysis,” Manchester School, 72, 363–81. Goddard, J., Molyneux, P., and Wilson, J.O.S. (2009). “The Financial Crisis in Europe: Evolution, Policy Responses and Lessons for the Future,” Journal of Financial Regulation and Compliance, 17, 362–80. Goddard, J., Molyneux, P., and Wilson, J.O.S. (2010). “Banking in the European Union,” in A.N. Berger, P. Molyneux, and J.O.S Wilson (eds.), Oxford Handbook of Banking (Oxford: Oxford University Press), 807–43. Goddard, J., Molyneux, P., and Wilson, J.O.S. (2014). “Banking in the European Union: Deregulation, Crisis and Renewal,” in A.N. Berger, P. Molyneux, and J.O.S. Wilson (eds.), Oxford Handbook of Banking, 2nd edn (Oxford: Oxford University Press), 849–72. Goddard, J., Molyneux, P., Wilson, J.O.S., and Tavakoli, M. (2007). “European Banking: An Overview,” Journal of Banking & Finance, 31, 1911–36. Gropp, R., Mosk, T.C., Ongena, S., and Wix, C. (2019). “Bank Response to Higher Capital Requirements: Evidence from a Quasi-Natural Experiment,” Review of Financial Studies, 32, 266–99. Gros, D. (2012). “The Single European Market in Banking in Decline: ECB to the Rescue?” in T. Beck (ed.), Banking Union for Europe: Risks and Challenges (London: Centre for Economic Policy Research), 49–54. Haldane, A. (2013). “Have We Solved ‘Too Big To Fail’?” VOX-EU, Centre for European Policy Research Portal, 17 January. Honohan, P. (2017). “Management and Resolution of Banking Crises: Lessons from Recent European Experience,” Peterson Institute for International Economics Policy Brief 17-1, January, Peterson Institute for International Economics, Washington, DC. Inanoglu, H., Jacobs, M., Liu, J., and Sickles, R.C. (2016). “Analyzing Bank Efficiency: Are ‘Too-Big-To-Fail’ Banks Efficient?” in E. Haven, P. Molyneux, J.O.S. Wilson, S. Fedotov, and M.  Duygun (eds.), The Handbook of Post Crisis Financial Modeling (Frankfurt: Springer International), 110–46. Jiménez, G., López, J.A., and Saurina, J. (2013). “How Does Competition Impact Bank Risk Taking?” Journal of Financial Stability, 9, 185–95. Kleymenova, A. and Tuna, A.I. (2017). “Regulation of Compensation (June 21, 2017),” Chicago Booth Research Paper No. 16-07, available at SSRN: https://ssrn.com/abstract=2755621 or http://dx.doi.org/10.2139/ssrn.2755621.

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Banking in Europe   1031 Koskela, E. and Stenbacka, R. (2000). “Is There a Tradeoff between Bank Competition and Financial Fragility?” Journal of Banking & Finance, 24, 1853–73. Lane, P. (2012). “The European Sovereign Debt Crisis,” Journal of Economic Perspectives, 26, 49–68. Leroy, A. and Lucotte, Y. (2017). “Is there a Competition–Stability Trade-off in European Banking?” Journal of International Financial Markets, Institutions and Money, 46, 199–215. Liikanen, E. (2012). “High-level Expert Group on Reforming the Structure of the EU Banking Sector,” Brussels, October 2, available at: https://ec.europa.eu/info/system/files/liikanenreport-02102012_en.pdf. Liu, H., Molyneux, P., and Wilson, J.O.S. (2013). “Competition and Stability in European Banking: A Regional Analysis,” Manchester School, 81, 176–201. Lozano-Vivas, A. (1998). “Efficiency and Technical Change for Spanish Banks,” Applied Financial Economics, 8, 289–300. Mariathasan, M. and Merrouche, O. (2014). “The Manipulation of Basel Risk-Weights,” Journal of Financial Intermediation, 23, 300–21. Marquez, L.B., Correa, R., and Sapriza, H. (2013). “International Evidence on Government Support and Risk Taking in the Banking Sector,” International Monetary Fund Working Paper No. WP/13/94. Martinez-Miera, D. and Repullo, R. (2010). “Does Competition Reduce the Risk of Bank Failure?” Review of Financial Studies, 23, 3638–64. Matousek, R., Rughoo, A., Sarantis, N., and Assaf, A.G. (2015). “Bank Performance and Convergence during the Financial Crisis: Evidence from the ‘Old’ European Union and Eurozone,” Journal of Banking & Finance, 52, 208–16. Maudos, J. (2017). “Income Structure, Profitability and Risk in the European Banking Sector: The Impact of the Crisis,” Research in International Business and Finance, 39, 85–101. Molyneux, P., Schaeck, K., and Zhou, T.M. (2014). “Too Systemically Important to Fail in Banking—Evidence from Bank Mergers and Acquisitions,” Journal of International Money and Finance, 49, 258–82. O’Hara, M. and Shaw, W. (1990). “Deposit Insurance and Wealth Effects: The Value of Being ‘Too Big to Fail’,” Journal of Finance, 45, 1587–600. Philippon, T. and Salord, A. (2017). “Bail-ins and Bank Resolution in Europe: A Progress Report,” Geneva Reports on the World Economy Special Report 4, International Center for Monetary and Banking Studies and CEPR, Geneva, International Center for Monetary and Banking Studies. Pisani-Ferry, J. and Sapir, A. (2010). “Banking Crisis Management in the EU: An Early Assessment,” Economic Policy, 25(62), 341–73. Saghi-Zedek, N. (2016). “Product Diversification and Bank Performance: Does Ownership Structure Matter?” Journal of Banking & Finance, 71, October, 154–67. Sapir, A. and Woolff, G. (2013). “The Neglected Side of Banking Union: Reshaping Europe’s Financial System,” Note Presented at the Informal ECOFIN, Vilnius, September. Schaeck, K. and Cihák, M. (2012). “Banking Competition and Capital Ratios,” European Financial Management, 18, 836–66. Schaeck, K. and Cihák, M. (2014). “Competition, Efficiency, and Stability in Banking,” European Financial Management, 43, 215–41. Schoenmaker, D. (2013). “An Integrated Financial Framework for the Banking Union: Don’t  Forget Macro-Prudential Supervision,” European Economy Economic Papers No. 495, April.

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1032   Banking Systems Around the World Stern, G.H. and Feldman, R. (2004). Too Big To Fail: The Hazards of Bank Bailouts (Washington: Brookings Institution Press). Stern, G.H. and Feldman, R. (2009). “Addressing TBTF by Shrinking Financial Institutions: An Initial Assessment,” The Region, June, 8–13, available at: https://www.minneapolisfed.org/ publications/the-region/addressing-tbtf-by-shrinking-institutions-an-initial-assessment. Stolz, S.H. and Wedow, M. (2010). “Extraordinary Measures in Extraordinary Times—Public Measures in Support of the Financial Sector in the EU and the United States,” European Central Bank Occasional Paper Series No. 117, July. Strahan, P.E. (2013). “Too Big to Fail: Causes, Consequences, and Policy Responses,” Annual Review of Financial Economics, 5, 43–61. Tarullo, D.K. (2012). “Financial Stability Regulation,” Speech at the Distinguished Jurist Lecture, University of Pennsylvania Law School, October 10, Philadelphia, Pennsylvania. Tsionas, E.G., Assaf, A.G. and Matousek, R. (2015). “Dynamic Technical and Allocative Efficiencies in European Banking,” Journal of Banking & Finance, 52, 130–9. Turk-Ariss, R. (2010). “On the Implications of Market Power in Banking: Evidence from Developing Countries,” Journal of Banking & Finance, 34, 765–75. Uhde, A. and Heimeshoff, U. (2009). “Consolidation in Banking and Financial Stability in Europe: Empirical Evidence,” Journal of Banking & Finance, 33, 1299–311. US Government Accountability Office (2011). Modified Prompt Corrective Action Framework Would Improve Effectiveness (Washington, DC: Government Accountability Office). Vallascas, F. and Hagendorff, J. (2013). “The Risk Sensitivity of Capital Requirements: Evidence from an International Sample of Large Banks,” Review of Finance, 17, 1947–88. Van Rompuy, H. (2012). “Towards a Genuine Economic and Monetary Union,” 5 December, European Commission, Brussels. Véron, N. (2013). “A Realistic Bridge Toward European Banking Union,” Bruegel Policy Contribution No. 9. Véron, N. and Woolff, G.B. (2013). “From Supervision to Resolution: Next Steps on the Road to European Banking Union,” Bruegel Policy Contribution No. 4. Vickers, J. (2011). Independent Commission on Banking, Final Report (London: The Stationery Office). Weill, L. (2009). “Convergence in Banking Efficiency across European Countries,” Journal of International Financial Markets, Institutions & Money, 19, 818–33. World Bank (2017). “Understanding Bank Recovery and Resolution in the EU: A Guidebook to the BRRD,” Financial Sector Advisory Center FinSAC, The World Bank, Finance and Markets, April, Washington, DC. Wyplosz, C. (2012). “Banking Union as a Crisis-Management Tool,” in T. Beck (ed.), Banking Union for Europe: Risks and Challenges (London: Centre for Economic Policy Research), 17–22.

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chapter 33

Ba n k i ng i n Ja pa n A Post-global Financial Crisis Perspective Hirofumi Uchida and Gregory F. Udell

33.1 Introduction This chapter focuses on the structure, performance, and some of the defining ­characteristics of the Japanese banking industry. There are a number of reasons why an analysis of the banking industry in Japan may be of particular interest. First, it is an essential part of one of world’s largest economies. Second, like some other developed economies such as Germany, Japan has historically been a banking-oriented financial system. Third, the banking industry has some very interesting idiosyncratic features related to the nature of the Japanese corporate environment such as its “main bank system.” Fourth, like other countries, the Japanese banking system has been in a period of significant transition, some of which is idiosyncratic to Japan, such as the banking crisis of the 1990s. In section 36.2 we provide an overview of the Japanese banking system. Then in section 36.3 we turn to some specific topics on banking in Japan, including the Japanese main bank system, lending technologies in Japan, the Japanese banking crisis, and banking in post-crisis Japan. Section 36.4 concludes.1

1  For a more comprehensive analysis of corporate finance and the Japanese banking industry see Hoshi and Patrick (2000) and Hoshi and Kashyap (2001). For an analysis of the Japanese economy see Flath (2000). And for a comprehensive evaluation of economic policies related to the recent recession with respect to Japan, see Ito, Patrick, and Weinstein (2005).

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1034   Banking Systems Around the World

33.2  Overview of the Japanese Banking System In this section we provide an overview of the banking industry in Japan including discussions of its market structure, efficiency, permissible activities, and regulation.

33.2.1  The Importance of Banking and Intermediated Finance in Japan The importance of banking and intermediated finance in Japan can be seen in Table 33.1. This breakdown of Japanese financial assets shows that of the 8,150 trillion yen of financial assets, 47 percent are held by Japanese financial institutions. Depository financial institutions are, by far, the largest component, holding 23 percent of the country’s financial assets, virtually all of which can be loosely classified as “banks”—the main focus of this chapter. The largest segment of the banking industry is domestically licensed banks (58 percent of banking assets). The remainder consists of foreign banks (2 percent), “financial” (banking) institutions for agriculture, forestry and fisheries (15 percent), and “financial” (banking) institutions for small businesses (25 percent). We can also see the importance of the banking system to the Japanese corporate, government, and household sectors. Table 33.2 shows the composition of financial assets and claims by financial instruments for each of these sectors. In the corporate sector, loans by private financial institutions and shareholders’ equity (i.e., “shares”) were the largest categories. At the end of March 2017, they comprise respectively 18.6 percent and 50.0 percent of firms’ total financing. The corresponding figures were 23.2 percent and 25.1 percent at the end of March 2012, indicating a reduced reliance on bank loans and an increased reliance on equity, although this may reflect higher stock prices given that equity is shown at market value. Other forms of relatively less important debt include commercial paper (0.1 percent) and corporate bonds (i.e., “industrial securities”) (2.8 percent). By way of comparison, in the US, domestic bank loans comprise 8.5 percent of corporate liabilities with commercial paper providing 0.8 percent and corporate bonds providing 19.7 percent (Q4 2017 US Flow of Funds Accounts). As is often the case in developed economies, the government sector is the largest debtor sector in Japan. Not surprisingly this sector is heavily dependent on bonds and bills for its financing (e.g., “financing bills,” “central government securities and FILP bonds,” and “local government securities”: 82.8 percent). Many of these bonds and bills are held by the banking sectors with only a relatively small amount of this owned directly by the public (i.e., “households”). On the consumer side, of the 1,808 trillion yen of financial assets held by households, 51.6 percent is invested in demand (“transferable”) and time and savings deposits.

Table 33.1  Financial Assets in Japan by Holder Financial institutions

38,955,550 (47%) Central bank Depository corporations

5,112,329 (6%) 19,138,092 (23%)

Banks

18,942,240 (23%) Domestically licensed banks Foreign banks in Japan Financial institutions for agriculture, forestry, and fisheries Financial institutions for small businesses

10,978,071 (58% among “Banks”) 431,422 (2% among “Banks”) 2,872,858 (15% among “Banks”) 4,659,889 (25% among “Banks”) 195,852 (0%)

1,882,381

(2%)

6,370,071

(8%)

Of which MMF and MRF Insurance and pension funds

120,945

Insurance

4,812,656 (6%) Life insurance Non-life insurance Mutual aid insurance

3,747,743 461,297 603,616

Pension funds Other financial intermediaries Non-banks Finance companies

1,557,415 (2%) 5,129,397

(6%) 808,890 (1%) 623,444 (continued)

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Collectively managed trusts Securities investment trusts

Financial institutions

38,955,550 (47%) Structured-financing special purpose companies and trusts

185,446

Public financial institutions

2,521,371

(3%)

Fiscal Loan Fund Government financial institutions

1,301,411 1,219,960

Financial dealers and brokers

1,799,136

Financial auxiliaries (financial institutions other than intermediaries)

719,657

(1%)

Of which: Financial holding companies Public captive financial institutions

586,440 603,623

Non-financial corporations General government Households Private non-profit institutions serving households Overseas

12,032,515 (15%)

Total

81,489,185 (100%)

5,615,428 (7%) 18,079,776 (22%) 554,587 (1%) 6,251,329 (8%)

Source: Flow of Funds Account (the Bank of Japan) (100 million yen, March 31, 2017).

(2%)

(1%)

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Table 33.1  Continued

Table 33.2  Assets and Liabilities of the Japanese Corporate, Government, and Household Sectors Private non-financial corporations Assets Currency and deposits Currency Government deposits Transferable deposits Time and savings deposits Certificates of deposits Foreign currency deposits

Call loans and bills Loans by private financial institutions

Liabilities

Assets

Households

Liabilities

Assets

Liabilities

2,553,308

(22.3%)

935,815

(16.7%)

9,324,761

(51.6%)

80,705

(0.7%)

(4.5%)

(14.1%) (5.1%) (1.5%) (0.9%)

(0.0%) (3.9%) (5.6%) (2.6%) (2.3%) (2.4%)

818,866

1,613,108 584,484 174,458 100,553

7 217,507 311,841 146,332 126,565 133,563

3,919,457 4,526,611 279 59,548

(21.7%) (25.0%) (0.0%) (0.3%)

574,986

(5.0%) 4,040,361

274,490 (24.4%) 243,683

(4.9%) (4.3%)

4,059

(0.0%)

64

(0.0%)

1,321

(0.0%) 3,089,416

Housing loans Consumer credit Loans to companies and governments Loans by public financial institutions

(18.6%)

1,572,965

(12.4%)

2,951,627

(93.1%)

638,982

(5.0%)

2,515,140

(79.4%)

1,755,095 328,246 431,799

(55.4%) (10.4%) (13.6%)

3,089,416

(18.6%)

638,982

(5.0%)

338,580

(2.0%)

903,257

(7.1%)

Of which: Housing loans Loans by the non-financial sector Installment credit (not included in consumer credit) Repurchase agreements and securities lending transactions Debt securities

556,006

(4.9%)

17,659

(0.2%)

277,419

(2.4%)

Treasury discount bills Central government securities and FILP bonds

85,356

(0.7%)

424,970 187,395

668,741

(2.6%) (1.1%)

243,374

(4.3%)

27,990

(0.2%)

245

(0.0%)

2,736

(0.0%)

(14.9%) 10,518,824

(82.8%)

(4.0%) 836,098 29

(0.0%)

1,152,132

(9.1%)

518,565

(9.2%)

8,632,541

(68.0%)

4,059

(0.0%)

245,446

(1.4%)

125,263

(0.7%)

385,861

(12.2%)

225,038

(7.1%)

49,618 1,008

(1.6%) (0.0%)

(continued)

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Deposits with the Fiscal Loan Fund Loans

General Government

Table 33.2  Continued Assets Local government securities Public corporation securities Bank debentures Industrial securities External securities issued by residents Commercial paper Trust beneficiary rights Structured-financing instruments Equity and investment fund shares Equity Investment trust beneficiary certificates Insurance, pension and standardized guarantees Financial derivatives and employee stock options Forward-type instruments Option-type instruments Employee stock options Deposits money Trade credits and foreign trade credits Accounts receivable/payable Outward direct investment Outward investment in securities Other external claims and debts Others Total (Difference between financial assets and liabilities)

General Government

Liabilities

Assets

Households

Liabilities

Assets

8,003 30,739 4,240 19,743

(0.1%) (0.3%) (0.0%) (0.2%)

122,353 109,142 5,227 76,604 35 6 4,087 50

(2.2%) (1.9%) (0.1%) (1.4%) (0.0%) (0.0%) (0.1%) (0.0%)

726,802 377

(5.7%) (0.0%)

20,737 46,430 62,171

(0.2%) (0.4%) (0.5%)

6,972

(0.1%)

3,602,984

(31.4%)

8,418,151

3,470,607 132,377

(30.3%) (1.2%)

8,299,564 118,587

(50.7%) 1,183,607 (50.0%) (0.7%)

(21.1%)

144,056

(21.0%) (0.0%)

144,056

22,481

(0.2%)

287,473

(1.7%)

28,117

(0.2%)

48,943

(0.3%)

56

(0.0%)

1,773

(0.0%)

25,187 2,930

(0.2%) (0.0%)

42,770 3,861 2,312

(0.3%) (0.0%) (0.0%)

56

(0.0%)

1,773

(0.0%)

366,430 2,228,206 143,824 1,160,913 337,612 10,439 154,653

(3.2%) (19.4%) (1.3%) (10.1%) (2.9%) (0.1%) (1.3%)

412,793 1,976,925 304,124

(2.5%) (11.9%) (1.8%)

42,687 6,361 183,289

(0.8%) (0.1%) (3.3%)

46,294 179,295 92,274

(0.4%) (1.4%) (0.7%)

1,457 428,815

(0.0%) (2.6%)

1,761,995 118,959 28,388

(31.4%) (2.1%) (0.5%)

22,040 122,464

(0.2%) (1.0%)

2,192

(0.0%)

467,782 177,015 21,752

(2.8%) (1.1%) (0.1%)

1,181,998 1,609

11,461,372 (100.0%) 16,587,783 (100.0%) 5,615,428 −5,126,411

(debtor)

Source: Flow of Funds Account (the Bank of Japan) (100 million yen, March 31, 2017).

Liabilities

7,061 6,058 275 70,175

(0.0%) (0.0%) (0.0%) (0.4%)

36,614

(0.2%)

(1.1%)

2,814,355

(15.6%)

(1.1%)

1,829,182 985,173

(10.1%) (5.4%)

5,183,100

(28.7%)

8,110

(0.0%)

5,798 2,312

(0.0%) (0.0%)

163,161 32,509 66,487

(0.9%) (0.2%) (0.4%)

219,514

(1.2%)

18,274

(0.1%)

(100.0%) 12,699,985 (100.0%) 18,079,776 (100.0%) −7,084,557

(debtor)

8,140

(0.3%)

2,571 5,569

(0.0%) (0.0%)

64,296 50,255

(2.0%) (1.6%)

95,251

(3.0%)

3,169,569 (100.0%) 14,910,207

(creditor)

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Private non-financial corporations

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Banking in Japan   1039 The next biggest category of consumer assets is insurance and pension assets (28.7 percent) followed by equity investments (“equity”) (10.1 percent) and investment trusts including mutual funds (“investment trust beneficiary certificates”) (5.4 percent). The biggest component of consumer debt is housing loans from either private or public financial institutions (55.4 percent). Overall, these data indicate that Japan is still predominantly a bank-intermediated financial system compared to market-oriented systems such as the UK and the US. It has been suggested that high growth in the post-war period may have been facilitated by the banking-oriented nature of Japan’s financial system, and some have further argued that this type of financial system with its emphasis on financial intermediation may be a good model for developing economies (Aoki and Patrick, 1994). However, it should also be noted that Japan suffered a banking crisis that began in the 1990s, the cause of which has been linked to the banking system. While Japan can still be categorized as having a banking-oriented financial system, the dependence on banking appears to be diminishing. Specifically, the proportion of financial assets held in banks has been on a general downward trend throughout the 1990s, the 2000s, and the 2010s (see Figure 33.1).2

33.2.2  Segmentation in the Japanese Banking Market Since World War II the Japanese financial industry had been segmented by the nature of the services provided by each type of financial institution. The origin of this regulatory segmentation dates back to the crisis-mode wartime system. Its purpose was to limit competition in order to promote banking profitability, thereby enhancing the safety and soundness of the financial system. Although financial liberalization in the 1980s and 1990s blurred the divide between different types of financial institutions, there still remain some boundaries (see Hoshi and Kashyap, 2001, chapter 4). Today commercial banks and commercial banking are defined under the 1981 Banking Law. Ordinary banks (futsuu ginko) are the most common type under the law, but there are other financial institutions and public banks that engage in commercial banking. The law also permits banks to engage in activities other than lending, deposit-taking or payments/settlement services, including investing in bonds and stocks (with some restrictions). As we will see in section 33.3.1, bank equity ownership gives banks an important role in corporate governance not only as a creditor but also as a stockholder.3 In the case of certain activities such as factoring and leasing, banks must engage in them indirectly through affiliates. With this background in mind we now turn to a description of the various types of bank in Japan.4 2  Note that the spike in 2008 is due to the inclusion of Japan Post Bank in “Banks.” 3  In May 2017, the Banking Law was revised to relax ordinary banks’ equity holding in order to promote FinTech. 4  Liu and Wilson (2010, 2012) respectively compare banks’ profitability and risk, and examine their determinants across bank types (city banks, regional banks, second-regional banks, Shinkin banks, and credit cooperatives).

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1040   Banking Systems Around the World 100% 90% 80% 70% 60% 50% 40% 30% 20% 10%

1980.3 1981.3 1982.3 1983.3 1984.3 1985.3 1986.3 1987.3 1988.3 1989.3 1990.3 1991.3 1992.3 1993.3 1994.3 1995.3 1996.3 1997.3 1998.3 1999.3 2000.3 2001.3 2002.3 2003.3 2004.3 2005.3 2006.3 2007.3 2008.3 2009.3 2010.3 2011.3 2012.3 2013.3 2014.3 2015.3 2016.3 2017.3

0%

Overseas

Nonfinancial corporations

General government

Financial Institutions (other than banks)

Households

Banks

Private nonprofit institutions serving households

Figure 33.1  Composition of Financial Assets in Japan by Holder. Source: Flow of Funds Account (the Bank of Japan) (March 31, 2017).

33.2.2.1  City Banks City banks—often referred to as mega banks—are a type of ordinary bank. Although there are now only five city banks in Japan (Mitsui-Sumitomo (SMBC), MitsubishiTokyo-UFJ (MUFG), Mizuho, Resona, and Saitama Resona), they are the largest single category (see Table 33.3).5 City banks grew quite rapidly in absolute and relative importance during the 1980s (see Figure 33.2). Four of these (excluding Saitama Resona) are 5  Saitama Resona Bank is often classified differently because of its regional orientation in Saitama prefecture. Both Saitama Resona Bank and Resona Bank are affiliated with the same holding company (Resona Holdings).

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Banking in Japan   1041 universal banks offering nationwide branch banking and three (excluding Resona and Saitama Resona) have extensive foreign bank networks.

33.2.2.2  Regional Banks and Second Regional Banks Comprising the second largest category—the regional banks—are sixty-four regionally oriented medium-sized banks (all substantially smaller than the city banks) (Table 33.3). The second (-tier) regional banks also operate regionally but tend to be smaller in size. Historically these were established as mutual (Sogo) banks whose purpose was to provide 2,500,000

2,000,000

(million yen)

1,500,000

1,000,000

500,000

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

0

City banks (domestic lending branches only)

Foreign banks

Regional banks (domestic branches only)

Shinkin banks

2nd regional banks (domestic branches only)

Credit cooperatives

Trust banks (domestic branches only)

Labor banks

Long term credit banks (domestic branches only)

Agricultural cooperatives

Foreign branches of above banks

Figure 33.2  Loans Outstanding of Private Banks. Source: Financial Institutions Accounts (the Bank of Japan).

# of banks

Assets

5

5,386,766

Regional banks

64

Second regional banks

41

Trust banks Foreign banks

private banks

City banksx

Japan Post Bank

Loans/ assets

Loans/ Deposits

1,905,295

3,433,657

0.35

0.55

3,104,493

1,925,353

2,543,180

0.62

0.76

FSA

747,335

507,988

657,873

0.68

0.77

FSA

16

1,004,000*

462,268*

494,925*

0.46

*0.93

*FSA

53

463,480

73,135

82,870

0.16

0.88

FSA

1

2,095,688

40,641

1,794,347

0.02

0.02

FSA

supervisory authority FSA (Financial Services Agency)

12

329,621

148,940

247,134

0.45

0.60

FSA

Shinkin banks

264

1,512,273

691,675

1,379,128

0.46

0.50

FSA

Credit cooperatives

151

223,179

106,382

199,392

0.48

0.53

FSA

Agricultural cooperatives

679

1,177,958

216,836

982,529

0.18

0.22

Ministry of Agriculture, Forestry and Fishery

1

263,202

96,730

0

0.37

NA

Ministry of Land, Infrastructure and Transport

Other banks under the Banking Act

#

Japan Housing Finance Agency Government financial institutions

Deposits

Loans

Development Bank of Japan

1

164,226

132,102

0

0.80

NA

Ministry of Finance

Shoko Chukin Bank

1

127,789

93,568

51,090

0.73

1.83

Ministry of Economy, Trade, and Industry

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Table 33.3  Descriptive Statistics for Different Bank Types in Japan

JapanFinance Corporation

1

69,966

69,219

0

0.99

NA

Ministry of Health, Labor and Welfare and Ministry of Finance

Agriculture, Forestry, Fisheries and Food Business Unit (formerly Agriculture Forestry and Fisheries Finance Corporation)

1

27,334

26,480

0

0.97

NA

Ministry of Agriculture, Forestry and Fisheries

Small and Medium Enterprise (SME) Unit (formerly Japan Finance Corporation for Small and Medium Enterprises)

1

53,667

55,376

0

1.03

NA

Ministry of Economy, Trade, and Industry

Japan Bank for International Cooperation+

1

185,717

143,091

0

0.77

NA

Ministry of Finance

Notes: Deposits do not include CDs (certificates of deposits) and financial bonds issued by some banks (similar to time-deposits). x Mizuho Bank, Bank of Tokyo-Mitsubishi UFJ, Sumitomo Mitsui Banking Corporation, Resona Bank, Saitama Resona Bank. * These figures are for four trust banks that are full members of the Japanese Bankers Association. # Aozora Bank, AEON Bank, Shinhan Bank Japan, Jibun Bank, Japan Net Bank, Shinginko Tokyo, Shinsei Bank, SBI Sumishin Net Bank, Seven Bank, Sony Bank, Daiwa Next Bank, and Rakuten Bank. The Resolution and Collection Bank is excluded because it is not an ordinary commercial bank. Sources and dates: [# of banks for private banks]: FSA, the Japanese Bankers Association, National Shinkin Banks Financial Statements, National Central Society of Credit Cooperatives, and Norinchukin Research Institute, as of March 31, 2017. [Balance sheet figures]: The Bank of Japan, the Japanese Bankers Association, National Shinkin Banks Financial Statements, National Central Society of Credit Cooperatives, Norinchukin Research Institute, and respective banks, as of March 31, 2017. [Unit (for assets, loans, and deposits)]: 100 million yen.

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Micro Business and Individual Unit (formerly National Life Finance Corporation)

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1044   Banking Systems Around the World financing to small to medium-sized enterprises (SMEs). While they are no longer restricted to this sector, they still tend to focus on SMEs. As a group, the second regional banks are considerably smaller than city banks and regional banks but they still play an important role in providing SME financing. Economists have often grouped regional and second regional banks together because both categories tend to focus on local and retail banking.

33.2.2.3  Trust Banks Under the 1943 Act on Provision of Trust Business by Financial Institutions, special types of banks, called trust banks, are allowed to offer trust services. They are, nevertheless, commercial banks under the Banking Law with respect to their provision of normal banking services. These banks offer money trusts (kinsen shintaku) which are essentially a form of medium- to long-term time deposit. From an asset perspective, these money trusts enable these banks to provide long-term corporate funding by making long-term commercial loans and investing in bonds and equities. This role was especially important given that the domestic post-war Japanese corporate bond market had been undeveloped.

33.2.2.4  Long-term Credit Banks Historically, long-term credit banks also played an important role in providing longterm corporate funding in the post-war Japanese financial system. They no longer exist in their original form, however. They were initially designed to complement ordinary banks which were (supposed to be) restricted to short-term lending. Long-term credit banks could issue bonds that were historically more attractive to investors than time deposits because of, among other things, deposit rate ceilings. These banks disappeared as a distinct group due to their financial distress or their consolidation (e.g., merger) during the Japanese banking crisis. Their function as providers of long-term corporate finance has been partly replaced by the emergence of a domestic Japanese corporate bond market and increased access to the Eurobond and other international bond markets.

33.2.2.5  Foreign Banks There are a large number of foreign banks that have branch offices or agencies in Japan. These branches require a banking license, and are regulated in the same manner as domestic banks under the Banking Law. Overall, focusing primarily on providing foreign exchange-related services, they play only a minor role in Japanese financial intermediation, as indicated in Table 33.3, and Figure 33.2.

33.2.2.6  Shinkin Banks and Credit Cooperatives Shinkin banks (Shin-you Kinko) and credit cooperatives (Shin-you Kumiai) are both cooperatives that specialize in providing commercial banking services to member SMEs and individuals. They are not legally “banks” because they operate under a special set of laws, but they engage in the same activities as other banks, although they are restricted

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Banking in Japan   1045 to lending to their member firms and restricted geographically. Financial deregulation in the 1980s expanded their product scope to include, for example, lending to nonmembers and offering mutual funds.

33.2.2.7  Other Financial Institutions Providing Commercial Banking Services As shown in Table 33.3, there are also a number of other financial institutions that provide commercial banking services. Other banks under the Banking Law include two former long-term credit banks (see section 33.2.2.4); Internet banks established by non-financial companies; a resolution bank to manage, collect, and dispose of the assets of failed financial institutions; and, recently established banks which do not fit into the classifications above. There are also additional cooperative banks beyond Shinkin banks and credit cooperatives: labor banks, agricultural cooperatives, fishery cooperatives, and forestry cooperatives. Among these, the agricultural cooperatives are quite numerous (commonly called collectively as JA Bank (Japan Agriculture Bank). Like Shinkin banks and credit cooperatives, these banks are becoming similar to banks that operate under the Banking Law, due to deregulation.

33.2.2.8  Public Banks As in some other countries, postal savings have played a historically important role in Japan. Postal savings had long been provided by the government (via the Ministry of Posts and Telecommunications). Funds collected through postal savings flowed to the Ministry of Finance which, in turn, allocated the funds to government financial institutions and other official accounts through the Fiscal Investment Loan Program (FILP) (see, e.g., Cargill and Yoshino, 2000). In the January 2001 reform, the Postal Services Agency assumed the operation of the three postal businesses (postal savings as well as postal insurance and postal mail services), and in April 2001 stopped sending its funds to the Ministry of Finance and started to allocate the funds at its own discretion. In 2003, the three businesses were further transferred to Japan Post, a state-owned company. Finally, in October 2007 the operation of the postal savings business was succeeded by a newly established private bank, the Japan Post Bank. All the equity of the Japan Post Bank was owned by a government holding company (the Japan Post Holdings). Initially, the equity was to be sold in the market in a stepwise manner ending in 2017, but this deadline was changed to “as soon as possible.” Although the Japan Post Bank was first listed on the Tokyo Stock Exchange in November 2015, whether it becomes a fully private bank is still a contentious political issue.6 Although postal savings in the past had tax and institutional advantages, today they are the same as deposits provided by other private banks—making the Japan Post Bank 6  See Sawada (2013) for the effect of the privatization in 2007 on other private banks.

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1046   Banking Systems Around the World effectively the single largest depository institution in Japan (see Table 33.3). Due to historical inertia, most of the assets of the Japan Post Bank are now invested in very low-risk instruments, making it effectively similar to a narrow (100 percent reserve) bank, although there is some interest in expanding its asset composition into such categories as housing and corporate loans.7 There are also a number of other government financial institutions. Some are not technically banks because they do not raise funds through deposits (Table 33.3). These institutions had been users of the FILP funds raised through postal savings (and related sources). Now they raise funds themselves by issuing special government guaranteed bonds. They were also consolidated and some are in the process of privatization. The Japan Housing Finance Agency (formerly the Government Housing Loan Corporation) had historically provided housing loans but now it only securitizes housing loans originated by private banks. The Development Bank of Japan is a public bank that has been providing long-term funds to corporations. It played an important role in the post-war development of Japan. There are also some institutions that focus on SME lending: the Shoko Chukin Bank and the Japan Finance Corporation (JFC). The latter was established in 2008 as a successor to the National Life Finance Corporation and the Japan Finance Corporation for Small and Medium Enterprises (formerly the Japan Finance Corporation for Small Business).8 The JFC also absorbed the Agriculture Forestry and Fisheries Finance Corporation and temporarily absorbed the Japan Bank for International Cooperation (JBIC). However, the JBIC, which provides support for the Japanese government’s foreign economic policy initiatives and economic cooperation programs, was again made an independent institution on April 1, 2012.

33.2.3  Market Structure and Competition of the Japanese Banking Industry On the deposit side of the banking market the segmentation described above is not an issue because there is little, if any, product differentiation—even between bank deposits and postal savings. However, the lending market is more complicated. On the one hand, financial deregulation has likely promoted the integration of the markets of different bank types. On the other hand, different types of bank are likely to have different comparative advantages with respect to different borrower types. Moreover, geographical segmentation may still be important, particularly for certain types of lending, such as relationship loans that likely have a spatial dimension. Thus, two types of segmentation 7  The government allowed the Japan Post Bank to provide non-collateralized loans to its account holders in June 2017. 8  For the role of these government financial institutions in supporting SMEs, see Fukanuma, Nemoto, and Watanabe (2006). Watanabe and Sekino (2016) find that the Japan Finance Corporation for Small and Medium Enterprises (currently a unit of the JFC) contributed to mitigating the credit crunch due to the Banking Crisis at the end of the 1990s.

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Banking in Japan   1047 are likely to exist: spatial segmentation and bank-type segmentation. Defining the scope of lending markets in Japan is an important empirical question. Few empirical studies have investigated Japanese market segmentation. A rare exception is Kano and Tsutsui (2003), who find that the lending market for Shinkin banks is segmented by prefecture (probably due to geographical restrictions on their operating areas), whereas prefectural segmentation is only weakly confirmed for regional banks. However, they do not investigate segmentation by bank type, which remains unexplored. Segmentation by prefecture was also found by Ishikawa and Tsutsui (2013).9 Whether or not markets are segmented by type or by region, banks can compete via branching. Historical restrictions on branch banking were relaxed in a stepwise manner from the 1980s through the 1990s, and now banks are virtually unconstrained in opening branch offices. Also, banks are now able to provide banking services through their agents, such as other banks, insurance companies, securities companies, and nonfinancial companies. Table 33.4 shows the number of branch offices for the four major types of banks. City banks have many branches in their nationwide operations (except for Resona and Saitama Resona, both of which have a regional orientation). Typically, there are one or two regional banks and one or two second regional banks in a prefecture (there are fortyseven prefectures in Japan). These banks typically have branch offices in and around their own prefecture and in large cities such as Tokyo and Osaka. How competitive is the Japanese banking market? Again there is a scarcity of research. Pooling city and regional banks, Molyneux, Thornton, and Lloyd-Williams (1996) find that Japanese banks were uncompetitive in 1986 and 1988. Another study, using a sample of city and regional banks from 1974 to 2000, estimates the degree of competition by bank type using a marginal price (Lerner index) approach (Uchida and Tsutsui, 2005). They find that competition had improved throughout the sample period, especially in the 1970s and in the first half of the 1980s when financial deregulation began. They also find that city banks had been facing more competitive pressure than regional banks.10

33.2.4  The Efficiency of Japanese Banks Most of the studies on the efficiency of Japanese banks focus on ordinary banks (plus long-term credit banks and trust banks).11 On balance, they find evidence of economies of scale, at least for the average bank. Some studies found evidence of scale economies until the early 1990s regardless of bank size (Fukuyama, 1993; McKillop, Glass, and 9  Uchino (2014) examines the impact of market rates on deposit rates and finds evidence suggestive of regional segmentation in deposit markets. 10  Gunji and Miura (2017) report an increase in the competitiveness of regional banks for the period from 1989 to 2009 using a different methodology. Kondo and Harimaya (2014) find that prefectures with larger population and GDP attract more entry by regional banks headquartered outside the relevant prefectures. 11  Fukuyama (1996) examines the efficiency of Shinkin banks, and Fukuyama, Guerra, and Weber (1999) investigate the efficiency of credit cooperatives.

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1048   Banking Systems Around the World Morikawa, 1996), although one study found evidence of diseconomies (Tadesse, 2006). Fukuyama (1993) finds that regional banks are scale inefficient, second regional banks are more efficient than regional banks, and city banks are close to efficient, exhibiting constant returns to scale. However, subsequent studies do not uniformly find evidence of scale economies in later periods. Altunbas et al. (2000) find during the 1993–6 period scale economies for the smallest banks in their sample only (i.e., banks with assets of 1–2 trillion yen of assets or less), but find scale diseconomies for large banks. Drake and Hall (2003) find similar results in 1996, but the optimal bank size in their study is larger than found by Altunbas et al. (2000). Whether the disappearance of universal scale economies after the 1990s is due to an underlying environmental change or due to methodological improvements is an open question. Drake and Hall (2003) also find that, in comparing bank types, ordinary banks are scale inefficient, whereas long-term credit banks and trust banks are scale efficient. However, the efficiency results for long-term credit banks and trust banks may suffer from a lack of appropriate controls for the difference between these banks and ordinary banks. Studies based on data envelopment analysis investigate pure technical inefficiency, or adequate/excessive use of inputs. Fukuyama (1993) finds pure technical inefficiency for ordinary banks with the magnitude being the greatest for regional banks. Drake and Hall (2003) find that the magnitude of pure technical inefficiency is greater than that of scale inefficiency—that is, banks can reduce cost more by adopting a technology requiring fewer inputs than by increasing the scale of their operation. Drake and Hall (2003) also show that, in terms of pure technical inefficiency, regional banks, and next second regional banks are inefficient, while city banks are almost efficient, and trust and long-term credit banks are efficient. They also report that the larger the bank size, the smaller the pure technical inefficiency becomes.12 Studies of scope economies are few and their results are not consistent.13 Tachibanaki, Mitsui, and Kitagawa (1991) find cost complementarity between lending and securities investment for city, regional, long-term credit, and trust banks. However, McKillop, Glass, and Morikawa (1996) find no global economy of scope for city banks among lending, liquid asset holdings, and securities investments. Rather, they find cost anticomplementarity between lending and holding liquid assets and between lending and securities investment, and cost complementarity between holding liquid assets and securities investment. In a study of regional banks, Harimaya (2008) finds cost anti-complementarity between lending and securities investment, and between lending and trust businesses, but cost complementarity between securities investment and trust businesses. He also finds that, although scale economies are observed on average, product-specific scale diseconomies are found for banks’ trust business, casting doubt on the prospect of banks increasing 12  Glass et al. (2014) investigate the efficiency of Shinkin banks and credit cooperatives. 13  As Berger, Hunter, and Timme (1993) point out, the measurement of the economies of scope is methodologically challenging.

Table 33.4  Four Main Types of Bank in Japan # of branches

5 City banks total

64 Regional banks total Saitama Resona Bank Hokkaido Bank Aomori Bank Michinoku Bank Akita Bank Hokuto Bank Shonai Bank Yamagata Bank Bank of Iwate Tohoku Bank 77 Bank Toho Bank Gunma Bank Ashikaga Bank Joyo Bank Tsukuba

Total

Domestic

Foreign

# of employees

Total

2,835

2,683

152

97,601

41 Second regional banks total

558 824 975

516 752 937

42 72 38

24,957 31,694 27,904

North Pacific Bank Kirayaka Bank KitaNippon Bank

347 131

347 131

– –

9,788 3,258

7,488

7,471

17

130,944

131 142 101 96 96 83 87 81 108 57 142 115 151 152 179 147

131 142 101 96 96 83 87 81 108 57 142 115 150 152 179 147

– – – – – – – – – – – – 1 – – –

3,258 2,291 1,320 1,296 1,400 935 928 1,335 1,472 618 2,774 2,159 3,177 2,876 3,668 1,656

Sendai Bank Fukushima Bank Daito Bank Towa Bank Tochigi Bank Keiyo Bank HigashiNippon Bank Tokyo Star Bank Kanagawa Bank Taiko Bank Nagano Bank First Bank of Toyama Fukuho Bank Shizuoka Chuo Bank Aichi Bank Bank of Nagoya Chukyo Bank Daisan Bank Kansai Urban Banking Corporation Taisho Bank

Domestic Foreign # of employees

3,049

3,048

39

44,790

171 117 80

171 117 80

– – –

3,455 1,007 900

73 54 62 91

73 54 62 91

1 2 3 4

687 535 579 1,560

92 119 85 33 34 70 54 66 38 46 105 113 86 98 155 27

92 119 85 33 34 70 54 66 38 46 105 112 86 98 155 27

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

1,663 2,119 1,428 1,680 382 854 689 728 504 465 1,651 1,948 1,213 1,400 2,632 338 (continued)

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Mizuho Bank Bank of TokyoMitsubishi UFJ Sumitomo Mitsui Banking Corporation Resona Bank Resona Bank

# of branches

Table 33.4  Continued # of branches

Total

Domestic

Foreign

# of employees

2,835

2,683

152

97,601

Musashino Bank Chiba Bank Chiba Kogyo Bank Tokyo Tomin Bank Bank of Yokohama Daishi Bank Hokuetsu Bank Yamanashi Chuo Bank Hachijuni Bank Hokuriku Bank Toyama Bank Hokkoku Bank Fukui Bank Shizuoka Bank Suruga Bank Shimizu Bank Ogaki Kyoritsu Bank Juroku Bank Mie Bank Hyakugo Bank

96 184 73 78 208 121 84 91 152 186 39 104 96 203 122 79 149 160 75 135

96 181 73 78 207 121 84 91 151 186 39 103 96 200 122 79 149 160 75 135

– 3 – – 1 – – – 1 – – 1 – 3 – – – – – –

2,285 4,357 1,337 1,540 4,694 2,341 1,486 1,685 3,178 2,779 337 1,787 1,385 2,884 1,624 1,000 3,073 3,291 1,286 2,480

Shiga Bank Bank of Kyoto Kinki Osaka Bank Senshu Ikeda Bank Nanto Bank

119 172 118 141 136

118 172 118 141 136

1 – – – –

2,147 3,428 2,208 2,686 2,615

5 City banks total

Total 41 Second regional banks total

Domestic Foreign # of employees

3,049

3,048

39

44,790

Minato Bank Shimane Bank Tomato Bank Momiji Bank Saikyo Bank Tokushima Bank Kagawa Bank Ehime Bank Bank of Kochi Fukuoka Chuo Bank Saga Kyoei Bank Bank of Nagasaki Kumamoto Family Bank Howa Bank Miyazaki Taiyo Bank MinamiNippon Bank Okinawa Kaiho Bank Yachiyo Bank

106 34 60 114 64 81 87 103 71 41 34 23 70 42 52 64 49 85

106 34 60 114 64 81 87 103 71 41 34 23 70 42 52 64 49 85

21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38

2,294 400 866 1,422 781 952 1,031 1,364 903 518 376 259 1,025 493 653 668 719 1,649

6 Trust banks total

273

264

43

22,082

Mitsubishi UFJ Trust and Banking Mizuho Trust & Banking Sumitomo Trust & Banking Nomura Trust and Banking

62 57 153 1

58 57 148 1

40 41 42 43

7,471 3,769 10,385 457

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# of branches

111

111

–

2,451

Other banks

308

299

89

24,289

Tajima Bank Tottori Bank Sanin Godo Bank Chugoku Bank Hiroshima Bank Yamaguchi Bank Awa Bank

72 66 134 161 167 135 99

72 66 134 160 167 132 99

– – – 1 – 3 –

713 719 1,995 3,179 3,381 1,820 1,312

Shinsei Bank Aozora Bank

273 35

264 35

44 45

22,082 2,207

Total

13,700 13,521

179

299,462

Hyakujushi Bank Iyo Bank

124 152

124 150

– 2

2,327 2,927

(Cf) Japan Post Bank

19,875 19,875

–

12,965

Shikoku Bank Bank of Fukuoka Chikuho Bank Bank of Saga Eighteenth Bank Shinwa Bank Higo Bank Oita Bank Miyazaki Bank Kagoshima Bank Bank of the Ryukyus Bank of Okinawa NishiNippon City Bank Kitakyushu Bank

105 170 44 103 100 88 122 95 96 124 75 65 186 36

105 170 44 103 100 88 122 95 96 124 75 65 186 36

– – – – – – – – – – – – – –

1,374 3,835 657 1,500 1,385 1,379 2,236 1,692 1,465 2,192 1,258 1,124 3,723 482

Note: Only the full members of the Japanese Bankers Association are included. Source: Japanese Bankers Association and Japan Post Bank homepage. (as of March 31, 2017).

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Kiyo Bank

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1052   Banking Systems Around the World their profitability by focusing on fee businesses. Interestingly, a recent study suggested that results might vary depending on modeling methodologies (Drake, Hall, and Simper, 2009). Thus, on balance, it is still unclear whether there are scope economies in banking.14,15

33.2.5  Commercial versus Universal Banking in Japan Historically Japan’s regulation of universal banking has mostly mirrored regulation in the US. Like the Glass–Steagall Act in the US, Article 65 of the 1948 Securities and Exchange Law in Japan separated investment banking from commercial banking. As in the US, there was a sequential dismantling of this separation, which began in the 1980s when city, long-term, trust, and regional banks were allowed to underwrite and deal in public bonds. It peaked in the 1990s when as a part of a “big bang” financial system liberalization (like the UK and the US), corporate underwriting by banks through affiliates and financial holding companies were allowed (see Horiuchi, 2000; Royama, 2000). Investment banking and trust activities, however, must still be conducted in affiliate organizations that are separate from the banking entity. As of March 31, 2017, there were twenty bank financial holding companies including those of the five city banks and the Japan Post Bank. There have been some studies that have examined issues related to universal banking in Japan, including the conflict of interest issue and relationship building across commercial and investment banking services. The results are mixed. Hamao and Hoshi (2000) show that the new-issue corporate bond yield spread does not depend on whether the underwriter is a bank affiliate. However, Takaoka and McKenzie (2004) find that underwriting commissions are smaller when the lead underwriter is a bank-owned securities company. They also find that, after the entry of bank-affiliates, underwriting commissions and yield spreads decreased. Takaoka and McKenzie (2004) further find that commissions and spreads do not vary depending on the strength of the bank–issuer relationship, but Yasuda (2007), using a more elaborate methodology, finds that the bank–issuer relationship does have a beneficial effect.16

14  Subsequent work on bank efficiency includes: Yamori and Harimaya (2010) on the efficiency of trust banks after deregulation; Montgomery, Harimaya, and Takahashi (2014) on the effect of bank mergers; Harimaya and Kondo (2016) on the effect of branch expansion; and Yamori, Harimaya, and Tomimura (2017) on the effect of outside directors. 15  Assaf, Barros, and Matousek (2011) analyze the productivity and efficiency of Shinkin banks from 2000 to 2006 using the bootstrap and Bayesian approaches. 16  Other studies on commercial and investment banking services include Kang and Liu (2007), Kutsuna, Smith, and Smith (2007), and Suzuki and Yamada (2012). Sue and Uchida (2016) compare equity holdings by banks and by bank-affiliated venture capital firms.

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Banking in Japan   1053

33.2.6  Regulation of the Japanese Banking System Before the banking crisis in Japan, the Ministry of Finance (MoF) played a dominant role in the prudential supervision of most of the banking system. In 1998, bank regulatory responsibility was shifted to the new Financial Supervisory Agency, which was reorganized as the Financial Services Agency (FSA) in 2000. As can be seen in Table 33.3, the FSA supervises and charters most of the banking system including, most importantly, the ordinary banks and financial holding companies. Some of the other private banking institutions are supervised by various ministries of the government as are all of the government financial institutions.17 As the central bank, the Bank of Japan (BoJ) also has the ability to monitor its customer banks (so-called “on-site examinations”) in order to discharge its responsibilities in determining and executing monetary policy and in providing liquidity to the banking system, including its role as lender of last resort. The deposit insurance ­system in Japan was established in 1971 and is provided by the Deposit Insurance Corporation.

33.3  Selected Topics in Japanese Banking 33.3.1  The Main Bank System and Relationship Banking The main bank system in Japan can be more precisely defined as a “system of corporate financing and governance involving an informal set of practices, institutional arrangements, and behaviours among industrial and commercial firms, banks of various types, other financial institutions, and the regulatory authorities. At its core there is the relationship between the main bank and the firm” (Aoki, Patrick, and Sheard, 1994, p. 3). Originally set up in war-time Japan, based on zaibatsus to help coordinate wartime production, these industrial groups allegedly became a driver of economic growth during the post-war period when they became known as keiretsu (see Teranishi, 1994; Hoshi and Kashyap, 2001). This relationship has many dimensions including reciprocal shareholdings, the supply of management resources and directors, and the provision of a broad array of financial services. Also important is the relationship between a firm’s main bank, the firm’s other financiers (see Sheard, 1994b), and the relationships among the regulatory authorities and all of these actors. The financial institutions and the firms tied together under this system are referred to as the “financial keiretsu” (horizontal keiretsu). This can be distinguished

17  For a more extensive discussion of the FSA and bank regulation including financial stability, see IMF (2012).

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1054   Banking Systems Around the World from the concept of a “corporate keiretsu” (vertical keiretsu) that mainly focuses on ties through vertical relationships among suppliers and sellers (see Aoki and Patrick, 1994). Before the early empirical studies on relationship banking in the US (e.g., Petersen and Rajan, 1994; Berger and Udell, 1995) and later in Europe (e.g., Angelini, DiSalvo, and Ferri, 1998), the practitioners and academics in Japan had focused primarily on the role of Japan’s main bank system. As we shall see in section 33.3.1.1, these earlier main bankfocused studies share much of their theoretical foundation with the newer literature on relationship lending. However, two distinctions need to be made between the newer literature on relationship lending and the study of the role of the main bank in the financial keiretsu. First, the main bank literature has a corporate governance component which is lacking in the newer relationship lending literature. Second, the main bank literature focuses, for the most part, on large companies while most of the newer relationship lending literature focuses on SMEs. These distinctions are important because corporate governance issues are much less relevant in the SME sector where there is usually no separation of ownership and management. It is important to note that there have been some studies on SME lending in Japan, conducted in the spirit of the newer literature on relationship lending that focus on the relationship between SMEs and their main banks.

33.3.1.1  Traditional Main Bank Studies Numerous academic studies since the 1980s have examined the role of main banks in financial keiretsus. The early focus of these studies was on risk-sharing among keiretsu members (e.g., Nakatani, 1984; Osano and Tsutsui, 1985). The literature then gradually shifted to the role of banks as providers of corporate governance (see Aoki, 1994). Some studies emphasize a special corporate governance role of the main bank in periods of firm distress (Sheard, 1994a; Osano, 1998). Other studies emphasize a contingent governance role for the main bank: the main bank plays a minimal role in normal times but in financial distress the bank assumes managerial control (e.g., Berglöf and Perotti, 1994). To a certain extent, the Japanese main bank system in terms of corporate governance can be viewed as similar to Germany’s historical Hausbank system, each standing in contrast to markets-oriented economies such as the UK and the US where the market for corporate control and shareholder activism play a more important role (Prowse, 1995). Empirically, the issue of the very definition of “the main bank” is challenging. A common approach is to follow the definition used by data providers, such as (1) keiretsu affiliation in Keiretsu no Kenkyu (Studies on Keiretsu) data, (2) a first-listed bank in Quarterly Corporate Report (Japan Company Handbook), and (3) an affiliation in Dodwell Marketing Consultants’ Industrial Groupings in Japan. Alternatively, the main bank is defined as a bank that (4) has a director on the borrower’s board, (5) is the largest lender, (6) is the largest shareholder, or (7) is both (5) and (6) (plus other characteristics). Empirical studies here can also be broadly classified based on their focus on the role of the main bank. Some emphasize the role of the main bank in mitigating liquidity constraints (e.g., Hoshi, Kashyap, and Scharfstein,  1990a, 1990b, 1991; Ogawa and

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Banking in Japan   1055 Suzuki, 2000).18 Others investigate managerial intervention by main banks. Kaplan and Minton (1994), Kang and Shivdasani (1995, 1997), and Morck and Nakamura (1999) find that during the late 1980s banks assigned new board members in a timely and effective manner. Shin and Kolari (2004) found that main banks played a unique role in information production specific to the 1995–7 period during the banking crisis.19 However, to some extent the tone of the research on main banks may reflect the timing of the studies themselves and the changing view of the Japanese economy from the more positive pre-crisis perspective to the more critical post-crisis perspective. Other later studies find that firms with a main bank exhibit weaker performance (e.g., Weinstein and Yafeh, 1998; Hanazaki and Horiuchi, 2000; Wu and Xu, 2005), suggesting that main banks extract excessive rents from their borrowers. Kang and Shivdasani (1999) and Kang and Stulz (2000) find similar results for bank- (though not necessarily main bank-) dependent firms. Some authors even argue that the main bank system and the importance of keiretsus is a “myth” and that many of the empirical results in this literature cannot be reproduced (Miwa and Ramseyer, 2002, 2005). One interpretation of these seemingly conflicting results is that the benefits from the main bank system (e.g., liquidity provision) may come at the cost of extracted rents. Interestingly, Weinstein and Yafeh (1998) find (in effect) evidence of a tradeoff where a main bank relationship may mitigate financing constraints even though it reduces firm performance. Moreover, the possibility of such a tradeoff between the benefits and costs of a main bank relationship had already been noted in a much earlier study (Nakatani, 1984). It is important to add here that recently there has been a fundamental change in corporate governance in Japan—a change that has been associated with a dismantling of keiretsu ties (Aoki, Jackson, and Miyajima, 2007). This suggests that for large businesses the main bank relationship may be significantly less important in the future. However, empirical evidence suggests that the main bank relationship is still important for large businesses, at least until 2008, with respect to the lack of changes in banks identified as the firm’s main bank and with respect to the provision of financial services (Hirota, 2009). Also, it seems unlikely that this trend has altered the importance of the main bank relationship for SMEs that continue to depend on banks for external finance.20

33.3.1.2  SME Relationship Lending Relatively recently there has been growing interest in research that examines relationship lending in the context of Japanese SMEs. Increased data availability has spawned 18  Although the methodology in the Hoshi, Kashyap, and Scharfstein papers has been criticized (Kaplan and Zingales, 1997; Hayashi, 2000), similar findings have been reported in a subsequent study using an improved methodology (Hori, Saito, and Ando, 2006). 19  See Gao (2008), Inoue, Kato, and Bremer (2008), and Kang et al. (2011) for more recent empirical studies on the role of main banks. 20  Kobayashi and Osano (2011) and Wu and Yao (2012) provide a more current theoretical assessment of the main bank system.

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1056   Banking Systems Around the World new empirical work on SME financing constraints including research on the impact of bank–borrower relationships and the benefits of soft information production. This coincides with increased practitioner and policy interest in SME financing and the FSA’s adoption of measures that are intended to promote relationship banking between SMEs and smaller banks (the Action Program concerning Enhancement of Relationship Banking Functions (2003 and 2004), and its successor program Ensuring Further Promotion of Regionally-based Relationship Banking (2005 and 2006)). Findings in the academic literature on SME lending practices in Japan are interesting from an international perspective. Kano et al. (2011) find that the lower loan interest rate and enhanced credit availability that are associated with long-term banking relationships occur only when hard information is unavailable for the borrower and the bank is small and faces stiff competition. However, the lending relationship in this sample is quite long (32.2 years on average) compared with that in other countries. Uchida, Udell, and Watanabe (2008) find that the mode of relationship building in Japan is somewhat different from that in the US as reported in Berger et al. (2005). Findings in Uchida, Udell, and Yamori (2012) also suggest that the role of the loan officer in Japan may be different than in the US.21

33.3.2  Lending Technologies in Japan Recently, the literature on business lending, especially small business lending, classifies types of lending as different lending technologies with relationship lending (discussed above) being one of the technologies (Berger and Udell, 2002, 2006). There are some interesting aspects of Japanese business lending from the lending technology viewpoint.22 In this subsection, we will discuss three of these: the role of collateral, business credit scoring, and government credit guarantee programs.

33.3.2.1  The Role of Collateral in Business Lending in Japan Collateral is one of the most powerful contracting tools used by bankers to mitigate information-based problems associated with business lending and is a vital component of many SME lending technologies. Lending against real estate, for example, is quite common globally in SME lending. Japan is no exception (see Ono et al., 2015). In fact, the role of collateral historically appears to have been of particular importance in Japan where banks practiced the so-called “collateral principle” under which they routinely underwrote business loans based almost entirely on real estate—real estate owned by the business and/or the entrepreneur. Interestingly, however, analyses from the post crisis period (mid-2000s) suggests that the collateral principle is no longer a dominant SME loan underwriting technology (see Uchida, Udell, and Yamori, 2008; Uchida, 2011).

21  Hattori, Shintani, and Uchida (2015) compare production of soft information by loan officers and branch managers. 22  See Uchida (2011) for the different use of various lending technologies by banks in Japan.

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Banking in Japan   1057 Whether or not the use of collateral is associated with borrower risk has been extensively studied in the literature, particularly in the US (see John, Lynch, and Puri, 2003). Evidence from one study on Japan suggests that there is a positive association, and that collateral’s use mitigates ex post moral hazard (Ono, Sakai, and Uesugi, 2012), but another study shows that ex ante borrower risk does not change the likelihood of pledging collateral (Ono and Uesugi, 2009). Another interesting finding in Japan (perhaps related to the collateral principle) is that stronger banking relations appear to be associated with an increased likelihood of pledging collateral (e.g., Ono and Uesugi, 2009; Kano et al., 2011). Relatively recently the requisite legal and commercial infrastructure to allow lending against movable assets (i.e., account receivables and inventory) was introduced in Japan (see Ono et al., 2015, section 4.1). As a result, commercial banks in Japan have begun offering SME lending technology known as asset-based lending (ABL), a type of collateral lending against receivables and inventory associated with intense monitoring. ABL had been confined almost entirely to common law countries such as Australia, Canada, New Zealand, the UK, and the US and is generally associated with a riskier class of borrowers (Carey, Post, and Sharpe, 1998; Udell, 2004). Some research suggests that ABL is still in the development stage in Japan (Kinjo, 2013).

33.3.2.2  Small Business Credit Scoring in Japan Japanese banks started to adopt in the early 2000s another lending technology originally introduced in the US in the mid-1990s—small business credit scoring (SBCS), and its volume rapidly increased to more than 2 trillion yen by 2005 (BoJ, 2007). Its introduction was also facilitated by a government policy initiative mentioned earlier to promote relationship banking by smaller banks (the Action Program Concerning Enhancement of Relationship Banking Functions 2003 and 2004). SBCS was promoted under this program as a form of lending that does not depend on collateral. However, due to the huge loan losses in SBCS loans, particularly those extended by Shinginko Tokyo (a bank established by the Tokyo Metropolitan Government to focus on SME lending), banks decreased the volume of their SBCS lending in the late 2000s (Hasumi and Hirata, 2013). Even earlier, the BoJ (2007) already identified the inadequacy of the informational infrastructure in Japan (e.g., the inability to link firm data with the owners’ personal credit history) as a potential source of high SBCS loan losses. In addition, the BoJ identified problems with the scoring model as it was applied to relatively large borrowers where the fit was generically poor. Hasumi and Hirata (2013) conclude that adverse selection problems, exacerbated by financial statement window-dressing (from which SBCS inputs were drawn), were the main causes of the huge losses.23

33.3.2.3  Government Guarantee Programs in Japanese Business Lending Governments in both developed and developing economies have directly or indirectly provided substantial amounts of funding to SMEs to address a “funding gap” 23  Ono, Hasumi, and Hirata (2014) investigate the ex post performance of SBCS borrowers with special attention to relationship vs. non-relationship lenders.

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1058   Banking Systems Around the World (e.g., Cressy, 2000, 2002). Evidence suggests that this funding gap is exacerbated by macro shocks that affect the banking system (e.g., Jiménez et al., 2012; Popov and Udell, 2012). In addition to direct lending by government financial institutions (see section 33.2.2.8), Japan has long implemented massive government loan guarantee programs for small business. Multiple credit guarantee corporations (CGCs) around the country, which are public institutions established based on the Credit Guarantee Corporation Law, provide guarantees on loans to SMEs, and the Japan Finance Corporation’s Small and Medium Enterprise Unit provides insurance on the guaranteed liabilities associated with the loans. The outstanding amount of liabilities guaranteed by the credit guarantee corporations was 23.9 trillion yen at the end of March 2017.24 Historically, the most important feature of these guarantee programs was the assumption of all risk (by CGCs) stemming from a 100 percent guarantee. To mitigate the screening and monitoring problems that arose from the 100 percent guarantee, a “Responsibility-Sharing System” was implemented in 2007 that reduced in principle the guarantee coverage to 80 percent. However, there have been some significant exceptions in the form of “special” 100 percent guarantee programs, including guarantee programs to respond to the Global Financial Crisis (the “Emergency (Safety-Net) Credit Guarantee Program,” from 2008), and to the Great Tohoku Earthquake (the “Great East Japan Earthquake Recovery Emergency Guarantee,” from 2011). Collectively, the credit guarantee programs in Japan provide a unique opportunity to study this type of government intervention and the potential moral hazard and adverse selection problems they might invite. Some evidence on the “Special Credit Guarantee Program for Financial Stability” implemented in 1998–2001 suggests that the benefits were significant and that many firms—specifically low-risk firms—actually became more efficient (Uesugi, Sakai, and Yamashiro, 2010). Other evidence on the same program suggests that it might have had bigger spillover effects on the supply of funds to non-users (Wilcox and Yasuda, 2008). Yet another study focusing on the “Emergency (Safety-Net) Credit Guarantee Program” calls for a more nuanced view. Ono, Uesugi, and Yasuda (2013) find that, while this program improved credit availability for borrowing firms, it also encouraged a portfolio substitution by the borrower’s main banks away from nonguaranteed loans to guaranteed loans. They also find deteriorating ex post performance of firms obtaining guaranteed loans from their main bank as compared with those obtaining non-guaranteed loans.

33.3.3  The Japanese Banking Crisis The banking crisis in Japan became a public policy issue in the middle of the 1990s, escalated dramatically shortly thereafter, and then continued perhaps as late as the 24  For more information about the credit guarantee system in Japan, see National Federation of Credit Guarantee Corporations (2017).

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Banking in Japan   1059 mid-2000s.25 We offer a brief overview of the crisis and its causes and its effects on bank behavior.

33.3.3.1  Brief Review of the Crisis The visible beginning of the crisis is associated with the failures of two credit cooperatives in 1994. The enormity of the banking crisis was revealed in stages.26 Ultimately there were 171 bank failures in Japan from 1994 through 2003 involving one city bank, two long-term credit banks, one regional bank, twelve second regional banks, twentythree Shinkin banks, and 132 credit cooperatives (Nikkin, 2005). The regulatory response can best be described as one of catching up with rapidly unfolding events. In particular, the regulatory policies and infrastructure in place at the beginning of the crisis were simply not capable of handling a crisis of this magnitude. New policies and infrastructure were created to address the problem—but with a significant lag. A limited number of bank failures prior to 1994 were resolved in a conventional manner using arranged mergers. However, the crisis moved to a more visibly serious stage in late 1994 with the failures of Tokyo Kyowa and Anzen, the two urban credit cooperatives. They were too large to be resolved by an arranged merger, and the deposit insurance fund was insufficient to cover the unprecedented losses. Concern about contagion effects persuaded regulators to avoid a payoff resolution in which depositors would take a haircut. The ultimate “hand-made” (Nakaso, 2001, p. 7) nature of the resolution of these two failures involved the establishment of a new successor bank capitalized by funds from the deposit insurance agency, the BoJ, and private financial institutions including those that had no relationship with the two cooperatives. In the following year a number of other banks failed, including a much larger urban cooperative. In addition, a group of real estate finance companies, the jusen, failed. Initially founded by commercial banks to augment their residential mortgage lending, the jusen had shifted their focus to financing real estate developers. Because of the collective size of these institutions, the resolution could not be handled without the use of taxpayer funding. Additional emergency measures were also undertaken at this time including the creation of the Resolution and Collection Bank, and the temporary implementation of a 100 percent deposit insurance guarantee.27 Following several other bank failures the financial crisis escalated in 1997 as it became apparent that problem loans were threatening the viability of Japan’s largest banks. Nippon Credit Bank, one of the three long-term credit banks, was bailed out, two security 25  Our reading of the literature suggests that there is no agreement on exactly when the crisis began and when it ended. As described below, the first bank failures, though small, began occurring in the early 1990s but then escalated dramatically later in the decade. Bank capital and non-performing loans, however, did not appear to stabilize until the mid-2000s. 26  The following discussion of the stages of the banking crisis is based on Nakaso (2001). 27  Even before this temporary measure, deposits had been implicitly 100% guaranteed under the convoy system (Hoshi, 2002). See Hoshi (2002) for a discussion of the “convoy” system in use until the early stages of the crisis in which the MoF protected and kept alive all financial institutions, including the most inefficient.

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1060   Banking Systems Around the World firms failed, and major bank failures began occurring on a regular basis in the fall, including that of Hokkaido Takushoku Bank (a city bank) and some second regional banks. Belatedly, in 1997 the government implemented emergency and permanent measures to cope with the crisis. These measures resulted in capital injections into twenty-one large banks in 1998. Nevertheless, problems in the banking system continued to mount in 1998 including the failure of two of the long-term credit banks—the Nippon Credit Bank (bailed out earlier) and the Long Term Credit Bank of Japan, each being resolved by temporary nationalization. Early in 1998, legislation was passed that provided for a further injection of $230 billion of public funds, part of which was allocated to the Deposit Insurance Corporation and the remainder was allocated to direct capital injections. Later in 1998, the Diet (Parliament) passed two pieces of legislation that significantly expanded the regulatory infrastructure to handle the disposition of failed banks and to inject capital into viable banks. Also, available funds were doubled from the original $230 billion. Additionally, in June 1998 the responsibility for the prudential supervision of banks was shifted from the Ministry of Finance to the Financial Supervisory Agency, which later reorganized as the Financial Services Agency in 2000. On October 2002, the Financial Services Agency officially announced the Program for Financial Revival: Revival of the Japanese Economy through Resolving NonPerforming Loans Problems of Major Banks. The agency declared its intent to reduce the non-performing loans (NPLs) ratio of major banks by around 50 percent. Following these actions and others including the sporadic capital injections as described above, the crisis subsided and indeed the NPL ratio decreased by more than half.28 No major bank failure has occurred since the failure and nationalization of Ashikaga Bank (a regional bank) in 2003.29 In hindsight, the resolution of the crisis saw the government and bank regulators deploy a variety of tools that had been used (or would be used) elsewhere in the world. These included establishing a bridge bank for segregating non-performing loans, and temporarily nationalizing large banks. Ultimately these measures were associated with the injection of massive amounts of government funding to back up the 100 percent deposit insurance coverage.30

33.3.3.2  Causes of the Crisis Cargill (2000) argues that there were five underlying causes of the crisis: a rigid financial regime, the failure of the BoJ’s monetary policy, a slow and indecisive regulatory 28  For smaller banks, the FSA took a less drastic and indirect approach to revitalize their customers (SMEs and regional economies). Specifically, the FSA adopted the two action programs indicated in section 36.3.1.2 to promote relationship banking. Although the causality is unclear, it turned out that the NPL ratio of regional banks ultimately decreased to less than 4 percent by 2007 (from FSA’s webpage, Status of Non-Performing Loans). 29  Resona Bank was also nationalized in 2003. 30  Studies on policy responses to the crisis include Hoshi and Patrick (2000), Hoshi and Kashyap (2001), Spiegel and Yamori (2003), and Montgomery and Shimizutani (2009).

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Banking in Japan   1061 response to emerging problems, a lack of public and political support to deal with troubled financial institutions with public funds, and the intransigence of financial institutions in accepting criticism of management policies. Hoshi (2001) and Hoshi and Kashyap (2001) make a related argument that the slow and incomplete deregulation of the financial system in the 1980s was also a key causal factor, because it precipitated the flight of good borrowers from the bank loan market to the capital markets, forcing banks to lend to borrowers with whom they were unfamiliar. Ueda (2000) also points out that excessive lending to unfamiliar borrowers in the real estate and related industries, as a consequence of the financial deregulation, might have contributed to the increase in non-performing loans.31 Ueda (2000) also speculates that rising land prices decreased the perceived risk in real estate lending, prompting more lending ex ante. He also finds evidence that the big drop in land prices ex post was an important determinant of deteriorating nonperforming loans.32 The “collateral principle” discussed above might also have exacerbated this pathology. Ogawa et al. (1996) and Ogawa and Suzuki (2000) find that large firms with more real estate were less financially constrained than those with less real estate. Anecdotal evidence indicates that euphoric lending practices driven by the formation of the asset price bubble ultimately led to problem loans in the banking system. This is partly consistent with the lazy bank hypothesis (Manove, Padilla, and Pagano, 2001). Irrational herding behavior may also have occurred (Uchida and Nakagawa,  2007; Nakagawa and Uchida, 2011).33,34 Kashyap (2002), however, argues that the loan problems that were ultimately revealed in the later stages of the crisis were simply too large to be entirely attributable to euphoric or reckless lending during the formation of the bubble. Further, Ono et al. (2018) find that the increase in the amount of loans was far smaller than the increase in land prices, which is at least quantitatively inconsistent with the euphoric or herding scenarios. These arguments notwithstanding, the evidence seems clear that the initial cause of problems in the banking sector was a pricing bubble in real estate that burst around 1990 (Hoshi and Kashyap, 2010).

33.3.3.3  The Effects of the Crisis Did the banking crisis lead to a credit crunch? The BoJ concluded so, noting in the minutes of their Monetary Policy Meeting (January 16, 1998) that the “prospects for a more restrictive lending attitude of financial institutions and its possible effects were discussed in detail.” Also, a quarterly survey on business expectations conducted by the BoJ, the 31  He also finds evidence of inefficient (lax) bank management and the safety net-driven moral hazard problem as factors driving poor loan performance. 32  Consistent with this evidence, Gan (2007) finds that banks with greater real estate exposure reduce more loans after the burst of the real estate bubble. 33  “Reckless lending,” more broadly defined, could include the practice of evergreening (the lending behavior of banks designed to keep zombie firms alive) as we will discuss in section 36.3.3.3. 34  Horiuchi and Shimizu (2001) find that practice in Japan, known as amakudari—hiring retired government officials as board members—may also have been a factor leading to non-performing loans although another study using a more elaborate methodology did not find this association (Konishi and Yasuda, 2004).

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1062   Banking Systems Around the World TANKAN survey, showed a significant shift in the perception of credit tightening by corporate Japan beginning in late 1997 (see Figure 33.4 below).35 A number of research papers have shown that bank capital deterioration and the decline in the health of the banking industry reduced bank lending (Ito and Sasaki, 2002), firm capital expenditures, and firm performance (Gibson, 1997; Fukuda, Kasuya, and Nakajima, 2005b; Hosono and Masuda, 2005; Miyajima and Yafeh, 2007), and increased the likelihood of the bankruptcy of borrowers (Fukuda, Kasuya, and Akashi, 2009).36 Woo (2003) and Watanabe (2007) find that the negative impact of the capital crunch was the greatest in fiscal year 1997, when the MoF became stricter on bank asset valuation.37

33.3.4  Banking in Post-Crisis Japan 33.3.4.1  Japanese Banks and the Global Financial Crisis Soon after the persistent adverse effect from the banking crisis subsided in Japan, the turmoil in the US subprime residential mortgage market beginning in early 2007 triggered an unprecedented worldwide financial crisis. The effect of the Global Financial Crisis spread to the Japanese economy after the failure of Lehman Brothers in September 2008. For the most part, however, the effect was minimal and Japan was not significantly affected by the Global Financial Crisis in ways that were comparable to Europe and the US (see IMF, 2012, p. 7). As shown in Figure 33.3, which shows the decomposition of profits and losses for ordinary banks, the adverse effect was only short-lived. There were several reasons for this. First, residential mortgages underwritten in Japan are all prime mortgages. Second, securitization is relatively undeveloped in Japan. When we compare the amount of residential mortgages (housing loans) underwritten and the amount of residential mortgage-backed securities (RMBS) issued from fiscal years 2004 to 2016, even at its peak in fiscal 2006, the volume of RMBS issued is just onefourth of the volume of residential mortgages underwritten.38 Third, Japan did not experience a real estate bubble during this period, and Japanese banks did not purchase significant amounts of US subprime mortgage-backed securities.39 Finally, the crisis 35  See Hoshi and Kashyap (2010) for a more detailed discussion of both the January 1998 meeting and the TANKAN survey. 36  Also, there are studies on the impact of bank failures on borrower performances, for example, Yamori and Murakami (1999), Brewer et al. (2003), Hori (2005), Fukuda and Koibuchi (2006), and Minamihashi (2011). Giannetti and Simonov (2013) examine the effect of bank bailout on the banks’ supply of credit and the performance of their borrowers. 37  Some studies also found that the introduction of Basel capital standards may have reduced bank lending (Hall, 1993; Konishi and Yasuda, 2004). 38  Data on the amount of residential mortgages (housing loans) underwritten and the amount of RMBS issued are respectively available from Japan Housing Finance Agency and Japan Securities Dealers Association. 39  The Bank of Japan’s Financial System Report (Bank of Japan, 2008, p. 2) notes that “(w)hile Japanese banks’ losses stemming from the US subprime mortgage problem increased as the problem became

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Banking in Japan   1063 was not propagated through capital-impaired foreign banks as in Europe (e.g., Popov and Udell, 2012) because Japanese banking is dominated by domestic banks.40 Interestingly, there are a number of parallels between the Japanese crisis in the 1990s and the financial crisis in the US, including the root cause—the bursting of a real estate bubble. Other similarities include the failure of investment banks and other non-banking financial institutions and the “hand made”/ad hoc nature of the regulatory response.41 For a more complete comparison of the Japanese banking crisis and the current financial crisis in the US, see Udell (2009), Hoshi and Kashyap (2010) and Allen, Chakraborty, and Watanabe (2011).42,43

33.3.4.2  Lost-decades and banking problems As in many developed countries, the Japanese economy has suffered from long-standing deflation that continued through and after the Global Financial Crisis, and in Japan, the period from the 1990s is often called “the lost-decades.” Possible causal factors include two that could be attributable to the banking sector: the credit crunch and evergreening loans. The former predicts that capital regulation contributes to a decrease in lending by under-capitalized banks. The latter, however, predicts an increase in lending, because banks might renew/roll over problem loans to make them appear performing, which could prop up economically unviable firms (“zombies”) who should otherwise be liquidated. As explained at the end of the previous subsection (section 33.3.3.3), there is strong evidence indicating a credit crunch and its adverse effects on the real economy. However, the effects do not seem to be prolonged. While the diffusion index of the lending attitude of Japanese financial institutions (Figure 33.4) sharply declined during the banking crisis (consistent with a nationwide crunch), it is generally good in other periods with the exception of the decline due to the Global Financial Crisis around 2009.44,45 This positive more serious, such losses seem to have been contained within their current profit levels and capital strength, since Japanese banks’ related exposures were mainly in the form of investments in structured credit products.” 40  Japanese banks did not suffer material damage from the European sovereign debt crisis (2009–) due to small exposure. 41  Imai (2009) find evidence suggesting that the political pressure mattered on the declaration of insolvency of regional financial institutions. 42  See Harada et al. (2015) for Japan’s financial regulatory responses after the Global Financial Crisis. 43  The Global Financial Crisis has also spawned much policy discussion on how to offset fiscal deficits caused by bank bailouts. Banerji et al. (2017) exploit a natural experiment, the 2000 “Tokyo bank tax,” to assess the unintended consequences of taxing banks as a solution. They find that the unexpected imposition of the Tokyo bank tax increased net interest margins, net interest, and fee margins, and reduced the credit supply of affected banks. 44  A study that is related and suggestive in this regard is Ishikawa and Tsutsui (2013), which uses prefectural panel data to try to identify whether the credit contraction in the 1990s was supply- or demand-driven. 45  As noted earlier, the government provided support during the Global Financial Crisis with special credit guarantee programs (section 36.3.2.3.) and increased loan supply by public banks (Shoko Chukin Bank and the JFC, see section 36.2.2.8). After the Global Financial Crisis, the Government also enacted temporary law, the 2009 Debt Moratorium Law, to obligate banks to make the “utmost effort” to reschedule loans for SMEs and eased the regulatory standard for non-performing loans (Imai, 2019).

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1064   Banking Systems Around the World 20

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Figure 33.3  Profits and Losses for Ordinary Banks. Source: Japanese Bankers Association.

lending attitude is at least partly due to massive monetary easing by the BoJ.46 Also, the exit rate of firms due to bankruptcy is low after the Global Financial Crisis, and even after the Great Tohoku Earthquake (March 2011), financial shocks from distressed banks did not increase this rate (Uchida et al., 2015).47 46  The easing was further strengthened when newly appointed Governor Kuroda at the Bank of Japan introduced quantitative and qualitative easing in April 2013. This aggressive monetary policy is one of the three components, or “arrows” of the so-called “Abenomics” (a policy package named after the prime minister), together with flexible fiscal policy and a growth strategy (see Ito et al., 2018). 47  Hosono et al. (2016) find that the financial shocks from damaged banks decreased firm investment after the Great Hanshin Earthquake (January 1995).

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Banking in Japan   1065 60 50 40 30 20

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Figure 33.4  Diffusion Index for Lending Attitude of Financial Institutions. Source: TANKAN Judgement Survey (the BoJ).

Hayashi and Prescott (2002) provide evidence showing that the stagnation of the Japanese economy in the 1990s was not due to a breakdown of the financial system, but rather due to low productivity growth (measured as total factor productivity (TFP)) in the real economy. Motonishi and Yoshikawa (1999) also report that tighter lending attitudes in banks did not constrain corporate investments by large firms, although small firms were constrained by tighter lending behavior. Regarding evergreening, Peek and Rosengren (2005) provide evidence consistent with evergreening in the form of increased lending by banks with low capital ratios to distressed firms in keiretsu.48 Further, Caballero, Hoshi, and Kashyap (2008) find evidence suggesting that the presence of zombie firms in an industry reduces investment and employment growth of non-zombie firms in the same industry, and increases the 48  Watanabe (2010) finds evidence suggesting that a large loss of bank capital in 2007 due to the regulators’ toughened stance led to the banks’ evergreening.

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1066   Banking Systems Around the World disparity in the productivity between zombies and non-zombies. However, later studies using an improved identification of zombie firms report a decrease in the number of zombie firms (Fukuda and Nakamura, 2011). Also, no evidence of zombie firms has been found for smaller firms (Fukuda, Kasuya, and Nakajima, 2005a; Sakai, Uesugi, and Watanabe, 2010). On balance, although the problems due to the banking sector might have had severe temporal adverse effects, it is difficult to conclude that they were the primary causes of the prolonged stagnation of the Japanese economy. Rather, a mechanism that works in the opposite direction appears more important. Under the zero interest rate environment driven by massive quantitative easing, especially after the introduction of the negative interest rate policy by the BoJ (January 2016), banks in Japan are suffering from decreasing interest revenues (see “Fund management profit/loss” in Figure 33.3).49

33.4 Conclusion This chapter examined the structure, the performance, and some of the defining characteristics of the Japanese banking industry. In addition to this overview, we have reviewed the literature on four interesting topics: the Japanese main bank system, lending technologies in Japan, the Japanese banking crisis in the 1990s, and banking in post-crisis Japan. We conclude by pointing out the scarcity of research on Japanese banking. Even on the selected topics discussed above there remain many open questions. For example, how and to what extent are banking markets in Japan segmented? Are there economies of scale or scope in banks in Japan, and to what extent? What were, and what are, the pros and cons of the main bank system? Did the banking crisis cause the prolonged stagnation in the Japanese economy, or vice versa? What is the future of the Japanese banking industry and the keiretsu-driven ties between firms and their main banks? The banking-oriented financial system has been a critical component of Japan’s economy—an economy that has grown to one of the largest in the world. Despite the idiosyncratic nature of Japanese banking, its seems quite likely that there is much we can learn from the Japanese experience that will inform us more generally about the role of banks in the global financial system architecture. More research on the banking industry in Japan is clearly called for.

49  Using data from fiscal years 1998 to 2010, Ogawa and Imai (2014) find evidence to indicate a portfolio shift for banks in Japan from loans to Japanese government bonds due to the decreasing interest margin for loans.

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Banking in Japan   1067

Acknowledgments The authors would like to thank Allen Berger, Phil Molyneux, John Wilson, Kozo Harimaya, Hikaru Fukanuma, Hiroshi Fujiki, Takeo Hoshi, Tae Okada, Arito Ono, Kenji Fujii, Wako Watanabe, and Yoshiaki Ogura for their helpful comments.

References Allen, L., Chakraborty, S., and Watanabe, W. (2011). “Foreign Direct Investment and Regulatory Remedies for Banking Crises: Lessons from Japan,” Journal of International Business Studies, 42, 875–93. Altunbas, Y., Liu, M.-H., Molyneux, P., and Seth, R. (2000). “Efficiency and Risk in Japanese Banking,” Journal of Banking and Finance, 24, 1605–28. Angelini, P., DiSalvo, R., and Ferri, G. (1998). “Availability and Cost of Credit for Small Businesses: Customer Relationships and Credit Cooperatives,” Journal of Banking and Finance, 22, 925–54. Aoki, M. (1994). “Monitoring Characteristics of the Main Bank System: An Analytical and Developmental View,” in M. Aoki and H. T. Patrick (eds.), The Japanese Main Bank System (New York: Oxford University Press), 109–41. Aoki, M. and Patrick, H. T. (1994). The Japanese Main Bank System: Its Relevance for Developing and Transforming Economies (New York: Oxford University Press). Aoki, M., Jackson, G., and Miyajima, H. (2007). Corporate Governance in Japan (Oxford: Oxford University Press). Aoki, M., Patrick, H. T., and Sheard, P. (1994). “The Japanese Main Bank System: An Introductory Overview,” in M. Aoki and H. T. Patrick (eds.), The Japanese Main Bank System (New York: Oxford University Press), 1–50. Assaf, A. G., Barros, C. P., and Matousek, R. (2011). “Productivity and Efficiency Analysis of Shinkin Banks: Evidence from Bootstrap and Bayesian Approaches,” Journal of Banking and Finance, 35, 331–42. Banerji, S., Chronopoulos, D. K., Sobiech, A. L., and Wilson, J. O. S. (2017). “Taxation and Financial Intermediation: Evidence from a Quasi-Natural Experiment,” Working Papers in Responsible Banking & Finance, No. 18-001, University of St. Andrews. Bank of Japan (2007). Financial System Report, September 2007. Bank of Japan (2008). Financial System Report, September 2008. Berger, A. N. and Udell, G. F. (1995). “Relationship Lending and Lines of Credit in Small Firm Finance,” Journal of Business, 68, 351–81. Berger, A. N. and Udell, G. F. (2002). “Small Business Credit Availability and Relationship Lending: The Importance of Bank Organizational Structure,” Economic Journal, 112, F32–F53. Berger, A. N. and Udell, G. F. (2006). “A More Complete Conceptual Framework for SME Finance,” Journal of Banking and Finance, 30, 2945–66. Berger, A. N., Hunter, W. C., and Timme, S. G. (1993). “The Efficiency of Financial Institutions: A Review and Preview of Research Past, Present and Future,” Journal of Banking and Finance, 17, 221–49.

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

1068   Banking Systems Around the World Berger, A. N., Miller, N. H., Petersen, M. A., Rajan, P. G., and Stein, J. C. (2005). “Does Function Follow Organizational Form? Evidence from the Lending Practices of Large and Small Banks,” Journal of Financial Economics, 76, 237–69. Berglöf, E. and Perotti, E. (1994). “The Governance Structure of the Japanese Financial Keiretsu,” Journal of Financial Economics, 36, 259–84. Brewer, E., Genay, H., Hunter, W. C., and Kaufman, G. G. (2003). “The Value of Banking Relationships During a Financial Crisis: Evidence from Failures of Japanese Banks,” Journal of the Japanese International Economies, 17, 233–62. Caballero, R.  J., Hoshi, T., and Kashyap, A.  K. (2008). “Zombie Lending and Depressed Restructuring in Japan,” American Economic Review, 98, 1943–77. Carey, M., Post, M., and Sharpe, S. A. (1998). “Does Corporate Lending by Banks and Finance Companies Differ? Evidence on Specialization in Private Debt Contracting,” Journal of Finance, 53, 845–78. Cargill, T. F. (2000). “What Caused Japan’s Banking Crisis?” in T. Hoshi and H. T. Patrick (eds.), Crisis and Change in the Japanese Financial System (Amsterdam: Kluwer Academic), 37–58. Cargill, T. F. and Yoshino, N. (2000). “The Postal Savings System, Fiscal Investment and Loan Program, and Modernization of Japan’s Financial System,” in T. Hoshi and H. T. Patrick (eds.), Crisis and Change in the Japanese Financial System (Amsterdam: Kluwer Academic), 201–30. Cressy, R. C. (2000). “European Loan Guarantee Schemes: Who Has Them, Who Pays, and Who Gains?” in B. Green (ed.), Risk Behaviour and Risk Management in Business Life (Amsterdam: Kluwer Academic), 235–46. Cressy, R. C. (2002). “Funding Gaps: A Symposium,” Economic Journal, 112, F1–F16. Drake, L. and Hall, M. J. B. (2003). “Efficiency in Japanese Banking: An Empirical Analysis,” Journal of Banking and Finance, 27, 891–917. Drake, L., Hall, M. J. B., and Simper, R. (2009). “Bank Modeling Methodologies: A Comparative Non-Parametric Analysis of Efficiency in the Japanese Banking Sector,” Journal of International Financial Markets, Institutions and Money, 19, 1–15. Flath, D. (2000). The Japanese Economy (Oxford: Oxford University Press). Fukanuma, H., Nemoto, T., and Watanabe, W. (2006). “Do Governmental Financial Institutions Help Startups Grow? Evidence from Japan,” Keio University, mimeo. Fukuda, S. and Koibuchi, S. (2006). “The Impacts of ‘Shock Therapy’ under a Banking Crisis: Experiences from Three Large Bank Failures in Japan,” Japanese Economic Review, 57, 232–56. Fukuda, S. and Nakamura, J. (2011). “Why did ‘Zombie’ Firms Recover in Japan?” The World Economy, 34, 1124–37. Fukuda, S., Kasuya, M., and Akashi, K. (2009). “Impaired Bank Health and Default Risk,” Pacific-Basin Finance Journal, 17, 145–62. Fukuda, S., Kasuya, M., and Nakajima, J. (2005a). “Did ‘Evergreening Loans’ Exist for Non-Listed Companies?” Bank of Japan Working Paper Series No. 05-J-9 (in Japanese). Fukuda, S., Kasuya, M., and Nakajima, J. (2005b). “Bank Health and Investment: An Analysis of Unlisted Companies in Japan,” Bank of Japan Working Paper Series No. 05-E-5. Fukuyama, H. (1993). “Technical and Scale Efficiency of Japanese Commercial Banks: A NonParametric Approach,” Applied Economics, 25, 1101–12. Fukuyama, H. (1996). “Returns to Scale and Efficiency of Credit Associations in Japan: A Nonparametric Frontier Approach,” Japan and the World Economy, 8, 259–77. Fukuyama, H., Guerra, R., and Weber, W.  L. (1999). “Efficiency and Ownership: Evidence from Japanese Credit Cooperatives,” Journal of Economics and Business, 51, 473–87.

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

Banking in Japan   1069 Gan, J. (2007). “The Real Effects of Asset Market Bubbles: Loan- and Firm-level Evidence of a Lending Channel,” Review of Financial Studies, 20, 1941–73. Gao, W. (2008). “Banks as Lenders and Shareholders: Evidence from Japan,” Pacific-Basin Finance Journal, 16, 389–410. Giannetti, M. and Simonov, A. (2013). “On the Real Effects of Bank Bailouts: Micro Evidence from Japan,” American Economic Journal: Macroeconomics, 5, 135–67. Gibson, M. S. (1997). “More Evidence on the Link between Bank Health and Investment in Japan,” Journal of the Japanese and International Economies, 11, 296–310. Glass, J.  C., McKillop, D.  G., Quinn, B., and Wilson, J.  O.  S. (2014). “Cooperative Bank Efficiency in Japan: A Parametric Distance Function Analysis,” European Journal of Finance, 20, 291–317. Gunji, H. and Miura, K. (2017). “Competition among Regional Banks in Japan: Evidence from the Boone Indicator,” Journal of International Economic Studies (Hosei University), 31, 65–86. Hall, B. J. (1993). “How has the Basle Accord Affected Bank Portfolios?” Journal of Japanese and International Economies, 7, 408–40. Hamao, Y. and Hoshi, T. (2000). “Bank-owned Security Subsidiaries in Japan: Evidence after the 1993 Financial System Reform,” in M.  Aoki and G.  R.  Saxonhouse (eds.), Finance, Governance, and Competitiveness in Japan (Oxford: Oxford University Press), 105–17. Hanazaki, M. and Horiuchi, A. (2000). “Is Japan’s Financial System Efficient?” Oxford Review of Economic Policy, 16, 61–73. Harada, K.  H., Hoshi, T., Imai, M., Koibuchi, S., and Yasuda, A. (2015). “Japan’s Financial Regulatory Responses to the Global Financial Crisis,” Journal of Financial Economic Policy, 7, 51–67. Harimaya, K. (2008). “Impact of Nontraditional Activities on Scale and Scope Economies: A Case Study of Japanese Regional Banks,” Japan and the World Economy, 20, 175–93. Harimaya, K. and Kondo, K. (2016). “Effects of Branch Expansion on Bank Efficiency: Evidence from Japanese Regional Banks,” Managerial Finance, 42, 82–94. Hasumi, R. and Hirata, H. (2013). “Small Business Credit Scoring and Its Pitfalls: Evidence from Japan,” Journal of Small Business Management, 52, 555–68. Hattori, M., Shintani, K., and Uchida, H. (2015). “The Repository of Soft Information Within Bank Organizations,” Journal of Money, Credit and Banking, 47, 737–70. Hayashi, F. (2000). “The Main Bank System and Corporate Investment: An Empirical Reassessment,” in M.  Aoki and G.  R.  Saxonhouse (eds.), Finance, Governance, and Competitiveness in Japan (Oxford: Oxford University Press), 81–98. Hayashi, F. and Prescott, E. C. (2002). “The 1990s in Japan: A Lost Decade,” Review of Economic Dynamics, 5, 206–35. Hirota, S. (2009). “Main Bank Relationships in Japan: From Monitoring to Risk Hedging,” RIETI Discussion Paper Series, 09-J-023 (in Japanese). Hori, K., Saito, M., and Ando, K. (2006). “What Caused Fixed Investment to Stagnate during the 1990s in Japan? Evidence from Panel Data of Listed Companies,” Japanese Economic Review, 57, 283–306. Hori, M. (2005). “Does Bank Liquidation Affect Client–Firm Performance? Evidence from a Bank Failure in Japan,” Economics Letters, 88, 415–20. Horiuchi, A. (2000). “The Big Bang: Idea and Reality,” in T. Hoshi and H. T. Patrick (eds.), Crisis and Change in the Japanese Financial System (Amsterdam: Kluwer Academic), 233–52.

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

1070   Banking Systems Around the World Horiuchi, A. and Shimizu, K. (2001). “Did Amakudari Undermine the Effectiveness of Regulator Monitoring in Japan?” Journal of Banking and Finance, 25, 573–96. Hoshi, T. (2001). “What Happened to Japanese Banks?” Bank of Japan Monetary and Economic Studies, 19, 1–30. Hoshi, T. (2002). “The Convoy System for Insolvent Banks: How it Originally Worked and Why it Failed in the 1990s,” Japan and the World Economy, 14, 155–80. Hoshi, T. and Kashyap, A. (2001). Corporate Financing and Governance in Japan (Cambridge, MA: MIT Press). Hoshi, T. and Kashyap, A.  K. (2010). “Will the US Bank Recapitalization Succeed? Eight Lessons from Japan,” Journal of Financial Economics, 97, 398–417. Hoshi, T. and Patrick, H.  T. (2000). “The Japanese Financial System: An Introductory Overview,” in T. Hoshi and H. T. Patrick (eds.), Crisis and Change in the Japanese Financial System (Amsterdam: Kluwer Academic), 1–36. Hoshi, T., Kashyap, A., and Scharfstein, D. (1990a). “Bank Monitoring and Investment: Evidence from the Changing Structure of Japanese Corporate Banking Relationships,” in R. G. Hubbard (ed.), Asymmetric Information, Corporate Finance, and Investment (Chicago, IL: University of Chicago Press), 105–26. Hoshi, T., Kashyap, A., and Scharfstein, D. (1990b). “The Role of Banks in Reducing the Costs of Financial Distress in Japan,” Journal of Financial Economics, 27, 67–88. Hoshi, T., Kashyap, A., and Scharfstein, D. (1991). “Corporate Structure, Liquidity, and Investment: Evidence from Japanese Industrial Groups,” Quarterly Journal of Economics, 106, 33–60. Hosono, K. and Masuda, A. (2005). “Bank Health and Small Business Investment: Evidence from Japan,” RIETI Discussion Paper Series No. 05-E-030. Hosono, K., Miyakawa, D., Uchino, T., Hazama, M., Ono, A., Uchida, H., and Uesugi, I. (2016). “Natural Disasters, Damage to Banks, and Firm Investment,” International Economic Review, 57, 1335–70. Imai, M. (2009). “Political Influence and Declarations of Bank Insolvency in Japan,” Journal of Money, Credit, and Banking, 41, 131–58. Imai, M. (2019). “Regulatory Responses to Banking Crisis: Lessons from Japan,” Global Finance Journal, 39, 10–16. IMF (2012). “Japan: Financial Sector Stability Assessment Update,” IMF Country Report No. 12/10, August. Inoue, K., Kato, H.  K., and Bremer, M. (2008). “Corporate Restructuring in Japan: Who Monitors the Monitor?” Journal of Banking and Finance, 32, 2628–35. Ishikawa, D. and Tsutsui, Y. (2013). “Credit Crunch and its Spatial Differences in Japan’s Lost Decade: What Can We Learn From It?” Japan and the World Economy, 28, 41–52. Ito, T. and Sasaki, Y. N. (2002). “Impacts of the Basle Capital Standard on Japanese Banks’ Behavior,” Journal of the Japanese and International Economies, 16, 372–97. Ito, T., Iwata, K., McKenzie, C., and Urata, S. (2018). “Did Abenomics Succeed? Editors’ Overview,” Asian Economic Policy Review, 13, 1–22. Ito, T., Patrick, H. T., and Weinstein, D. E. (2005). Reviving Japan’s Economy: Problems and Prescriptions (Cambridge, MA: MIT Press). Jiménez, G., Ongena, S., Peydro, J., and Saurina, J. (2012). “Credit Supply and Monetary Policy: Identifying the Bank–Balance Sheet Channel with Loan Applications,” American Economic Review, 102, 2121–65.

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

Banking in Japan   1071 John, K., Lynch, A. W., and Puri, M. (2003). “Credit Ratings, Collateral and Loan Characteristics: Implications for Yield,” Journal of Business, 76, 371–409. Kang, J.-K. and Liu, W. L. (2007). “Is Universal Banking Justified? Evidence from Bank Underwriting of Corporate Bonds in Japan,” Journal of Financial Economics, 84, 142–86. Kang, J.-K. and Shivdasani, A. (1995). “Firm Performance, Corporate Governance, and Top Executive Turnover in Japan,” Journal of Financial Economics, 38, 29–58. Kang, J.-K. and Shivdasani, A. (1997). “Corporate Restructuring During Performance Declines in Japan,” Journal of Financial Economics, 46, 29–65. Kang, J.-K. and Shivdasani, A. (1999). “Alternative Mechanisms for Corporate Governance in Japan: An Analysis of Independent and Bank-Affiliated Firms,” Pacific-Basin Finance Journal, 7, 1–22. Kang, J.-K. and Stulz, R. (2000). “Do Banking Shocks Affect Borrowing Firm Performance? An Analysis of the Japanese Experience,” Journal of Business, 73, 1–23. Kang, J.-K., Kim, K.  A., Kitsabunnarat-Chatjuthamard, P., and Nishikawa, T. (2011). “The Effects of Bank Relations on Stock Repurchases: Evidence from Japan,” Journal of Financial Intermediation, 20, 94–116. Kano, M. and Tsutsui, Y. (2003). “Geographical Segmentation in Japanese Bank Loan Markets,” Regional Science and Urban Economics, 33, 157–74. Kano, M., Uchida, H., Udell, G. F., and Watanabe, W. (2011). “Information Verifiability, Bank Organization, Bank Competition and Bank–Borrower Relationships,” Journal of Banking and Finance, 35, 935–54. Kaplan, S.  N. and Minton, B. (1994). “Appointments of Outsiders to Japanese Boards: Determinants and Implications for Managers,” Journal of Financial Economics, 36, 225–57. Kaplan, S. N. and Zingales, L. (1997). “Do Investment–Cash Flow Sensitivities Provide Useful Measures of Financing Constraints?” Quarterly Journal of Economics, 112, 169–215. Kashyap, A. (2002). “Sorting out Japan’s Financial Crisis,” Federal Reserve Bank of Chicago Economic Perspectives, 26, 42–55. Kinjo, A. (2013). “Function of Collateral When Asset Class is Accounts Receivables and Inventory: A Comparative Analysis of Japanese and US Bank Inspection Manuals,” Presented at the Japan Society of Monetary Economics 2013 Spring Annual Meeting. Kobayashi, M. and Osano, H. (2011). “The New Main Bank System,” Journal of the Japanese and International Economies, 25, 336–54. Kondo, K. and Harimaya, K. (2014). “Why Do Japanese Non-Local Regional Banks Enter Other Prefectures Under the Region-based Relationship Banking Policy?” Journal of Industry, Competition and Trade, 14, 473–85. Konishi, M. and Yasuda, Y. (2004). “Factors Affecting Bank Risk Taking: Evidence from Japan,” Journal of Banking and Finance, 28, 215–32. Kutsuna, K., Smith, J. K., and Smith, R. L. (2007). “Banking Relationships and Access to Equity Capital Markets: Evidence from Japan’s Main Bank System,” Journal of Banking and Finance, 31, 335–60. Liu, H. and Wilson, J. O. S. (2010). “The Profitability of Banks in Japan,” Applied Financial Economics, 20, 1851–66. Liu, H. and Wilson, J. O. S. (2012). “Competition and Risk in Japanese Banking,” European Journal of Finance, 19, 1–18. Manove, M., Padilla, A. J., and Pagano, M. (2001). “Collateral versus Project Screening: A Model of Lazy Banks,” Rand Journal of Economics, 32, 726–44.

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

1072   Banking Systems Around the World McKillop, D. G., Glass, J. C., and Morikawa, Y. (1996). “The Composite Cost Function and Efficiency in Giant Japanese Banks,” Journal of Banking and Finance, 20, 1651–71. Minamihashi, N. (2011). “Credit Crunch Caused by Bank Failures and Self-Selection Behavior in Lending Markets,” Journal of Money, Credit, and Banking, 43, 133–61. Miwa, Y. and Ramseyer, J. M. (2002). “The Fable of the Keiretsu,” Journal of Economics & Management Strategy, 11, 169–224. Miwa, Y. and Ramseyer, J. M. (2005). “Does Relationship Banking Matter? The Myth of the Japanese Main Bank,” Journal of Empirical Legal Studies, 2, 261–302. Miyajima, H. and Yafeh, Y. (2007). “Japan’s Banking Crisis: An Event–Study Perspective,” Journal of Banking and Finance, 31, 2866–85. Molyneux, P. J., Thornton, P., and Lloyd-Williams, D. M. (1996). “Competition and Market Contestability in Japanese Commercial Banking,” Journal of Economics and Business, 48, 33–45. Montgomery, H. and Shimizutani, S. (2009). “The Effectiveness of Bank Recapitalization Policies in Japan,” Japan and the World Economy, 21, 1–25. Montgomery, H., Harimaya, K., and Takahashi, Y. (2014). “Too Big to Succeed? Banking Sector Consolidation and Efficiency,” Journal of International Financial Markets, Institutions and Money, 32, 86–106. Morck, R. and Nakamura, M. (1999). “Banks and Corporate Control in Japan,” Journal of Finance, 54, 319–39. Motonishi, T. and Yoshikawa, H. (1999). “Causes of the Long Stagnation of Japan during the 1990s: Financial or Real?” Journal of the Japanese International Economies, 13, 181–200. Nakagawa, R. and Uchida, H. (2011). “Herd Behaviour by Japanese Banks after Financial Deregulation,” Economica, 78, 618–36. Nakaso, H. (2001). “The Financial Crisis in Japan During the 1990s: How the Bank of Japan Responded and the Lessons Learnt,” BIS Papers No. 6. Nakatani, I. (1984). “The Economic Role of Financial Corporate Grouping,” in M. Aoki (ed.), The Economic Analysis of the Japanese Firm (Amsterdam: Elsevier), 227–58. National Federation of Credit Guarantee Corporations (2017). Credit Guarantee System in Japan 2017. Nikkin (2005). Nikkin Data Annual (in Japanese). Ogawa, K. and Imai, K. (2014). “Why Do Commercial Banks Hold Government Bonds? The Case of Japan,” Journal of the Japanese and International Economies, 34, 201–16. Ogawa, K. and Suzuki, K. (2000). “Demand for Bank Loans and Investment Under Borrowing Constraints: A Panel Study of Japanese Firm Data,” Journal of the Japanese and International Economies, 14, 1–21. Ogawa, K., Kitasaka, S.-I., Yamaoka, H., and Iwata, Y. (1996). “Borrowing Constraints and the Role of Land Asset in Japanese Corporate Investment Decision,” Journal of the Japanese and International Economies, 10, 122–49. Ono, A. and Uesugi, I. (2009). “Role of Collateral and Personal Guarantees in Relationship Lending: Evidence from Japan’s SME Loan Market,” Journal of Money, Credit, and Banking, 41, 935–60. Ono, A., Hasumi, R., and Hirata, H. (2014). “Differentiated Use of Small Business Credit Scoring by Relationship Lenders and Transactional Lenders: Evidence from Firm–Bank Matched Data in Japan,” Journal of Banking & Finance, 42, 371–80. Ono, A., Sakai, K., and Uesugi, I. (2012). “The Effects of Collateral on Firm Performance,” Journal of the Japanese and International Economies, 26, 84–109.

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

Banking in Japan   1073 Ono, A., Uchida, H., Kozuka,  S., and Hazama, M. (2015). “A New Look at Bank–Firm Relationships and the Use of Collateral in Japan: Evidence from Teikoku Databank Data,” in T. Watanabe, I. Uesugi, and A. Ono (eds.), The Economics of Interfirm Networks (Tokyo: Springer Japan), 191–214. Ono, A., Uchida, H., Udell, G. F., and Uesugi, I. (2018). “Lending Pro-Cyclicality and MacroPrudential Policy: Evidence from Japanese LTV Ratios,” Mizuho Research Institute, Kobe University, Indiana University, and Hitotsubashi University. Ono, A., Uesugi, I., and Yasuda, Y. (2013). “Are Lending Relationships Beneficial or Harmful for Public Credit Guarantees? Evidence from Japan’s Emergency Credit Guarantee Program,” Journal of Financial Stability, 9, 151–67. Osano, H. (1998). “Default and Renegotiation in Financial Distress in the Multiple Bank Model: An Analysis of the Main Bank System,” Japanese Economic Review, 49, 138–57. Osano, H. and Tsutsui, Y. (1985). “Implicit Contracts in the Japanese Bank Loan Market,” Journal of Financial and Quantitative Analysis, 20, 211–30. Peek, J. and Rosengren, E.  S. (2005). “Unnatural Selection: Perverse Incentives and the Misallocation of Credit in Japan,” American Economic Review, 95, 1144–66. Petersen, M.  A. and Rajan, R.  G. (1994). “The Benefits of Lending Relationships: Evidence from Small Business Data,” Journal of Finance, 49, 3–37. Popov, A. and Udell, G. F. (2012). “Cross-Border Banking, Credit Access, and the Financial Crisis,” Journal of International Economics, 87, 147–61. Prowse, S. (1995). “Corporate Governance in an International Perspective: A Survey of Corporate Control Mechanisms Among Large Firms in the USA, UK, Japan and Germany,” Financial Markets, Institutions and Instruments, 4, 1–63. Royama, S. (2000). “The Big Bang in Japanese Securities Markets,” in T. Hoshi and H. T. Patrick (eds.), Crisis and Change in the Japanese Financial System (Amsterdam: Kluwer Academic), 253–76. Sakai, K., Uesugi, I., and Watanabe, T. (2010). “Firm Age and the Evolution of Borrowing Costs: Evidence from Japanese Small Firms,” Journal of Banking and Finance, 34, 1970–81. Sawada, M. (2013). “Measuring the Effect of Postal Saving Privatization on the Japanese Banking Industry: Evidence from the 2005 General Election,” Pacific-Basin Finance Journal, 21, 967–83. Sheard, P. (1994a). “Main Banks and the Governance of Financial Distress,” in M. Aoki and H.  T.  Patrick (eds.), The Japanese Main Bank System, 188–230. New York: Oxford University Press. Sheard, P. (1994b). “Reciprocal Delegated Monitoring in the Japanese Main Bank System,” Journal of the Japanese and International Economies, 8, 1–21. Shin, G.  H. and Kolari, J.  W. (2004). “Do Some Lenders have Information Advantages? Evidence from Japanese Credit Market Data,” Journal of Banking and Finance, 28, 2331–51. Spiegel, M. M. and Yamori, N. (2003). “The Impact of Japan’s Financial Stabilization Laws on Bank Equity Values,” Journal of the Japanese and International Economies, 17, 263–82. Sun, Y. and Uchida, K. (2016). “The Role of Bank-Affiliated Venture Capital for Parent Banks in Japan: New Evidence,” Asia-Pacific Journal of Financial Studies, 45, 864–85. Suzuki, K. and Yamada, K. (2012). “Do the Use of Proceeds Disclosure and Bank Characteristics Affect Bank Underwriters’ Certification Roles?” Journal of Business Finance & Accounting, 39, 1102–30. Tachibanaki, T., Mitsui, K., and Kitagawa, H. (1991). “Economies of Scope and Shareholding of Banks in Japan,” Journal of the Japanese and International Economies, 5, 261–81.

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1074   Banking Systems Around the World Tadesse, S. (2006). “Consolidation, Scale Economies and Technological Change in Japanese Banking,” Journal of International Financial Markets, Institutions and Money, 16, 425–45. Takaoka, S. and McKenzie, C. R. (2004). “The Impact of Bank Entry in the Japanese Corporate Bond Underwriting Market,” Journal of Banking and Finance, 30, 59–83. Teranishi, J. (1994). “Loan Syndication in War-time Japanese and the Origins of the Main Bank System,” in M. Aoki and H. T. Patrick (eds.), The Japanese Main Bank System (New York: Oxford University Press), 51–88. Uchida, H. (2011). “What Do Banks Evaluate When They Screen Borrowers? Soft Information, Hard Information and Collateral,” Journal of Financial Services Research, 40, 29–48. Uchida, H. and Nakagawa, R. (2007). “Herd Behavior in the Japanese Loan Market: Evidence from Bank Panel Data,” Journal of Financial Intermediation, 16, 555–83. Uchida, H. and Tsutsui, Y. (2005). “Has Competition in the Japanese Banking Sector Improved?” Journal of Banking and Finance, 29, 419–39. Uchida, H., Miyakawa, D., Hosono, K., Ono, A., Uchino, T., and Uesugi, I. (2015). “Financial Shocks, Bankruptcy, and Natural Selection,” Japan and the World Economy, 36, 123–35. Uchida, H., Udell, G. F., and Watanabe, W. (2008). “Bank Size and Lending Relationships in Japan,” Journal of the Japanese and International Economies, 22, 242–67. Uchida, H., Udell, G. F., and Yamori, N. (2008). “How Do Japanese Banks Discipline Small- and Medium-Sized Borrowers? An Investigation of the Deployment of Lending Technologies,” International Finance Review, 9, 57–80. Uchida, H., Udell, G.  F. and Yamori, N. (2012). “Loan Officers and Relationship Lending,” Journal of Financial Intermediation, 21, 97–122. Uchino, T. (2014). “Bank Deposit Interest Rate Pass-through and Geographical Segmentation in Japanese Banking Markets,” Japan and the World Economy, 30, 37–51. Udell, G. F. (2004). Asset-Based Finance (New York: Commercial Finance Association). Udell, G. F. (2009). “Wall Street, Main Street, and a Credit Crunch: Thoughts on the Current Financial Crisis,” Business Horizons, 52, 117–25. Ueda, K. (2000). “Causes of Japan’s Banking Problems in the 1990s,” in T.  Hoshi and H. T. Patrick (eds.), Crisis and Change in the Japanese Financial System (Amsterdam: Kluwer Academic), 59–84. Uesugi, I., Sakai, K., and Yamashiro, G. M. (2010). “The Effectiveness of Public Credit Guarantees in the Japanese Loan Market,” Journal of the Japanese and International Economies, 24, 457–80. Watanabe, W. (2007). “Prudential Regulation and the ‘Credit Crunch’: Evidence from Japan,” Journal of Money, Credit and Banking, 39, 639–65. Watanabe, W. (2010). “Does a Large Loss of Bank Capital Cause Evergreening? Evidence from Japan,” Journal of the Japanese and International Economies, 24, 116–36. Watanabe, W. and Sekino, M. (2016). “Does the Policy Lending of the Government Financial Institution Mitigate the Credit Crunch? Evidence from the Loan Level Data in Japan,” Asian Finance Association (AsianFA) 2016 Conference, available at SSRN: https://ssrn.com/ abstract=2722304. Weinstein, D. E. and Yafeh, Y. (1998). “On the Costs of a Bank-Centered Financial System: Evidence from the Changing Main Bank Relations in Japan,” Journal of Finance, LIII, 635–72. Wilcox, J.  A. and Yasuda, Y. (2008). “Do Government Loan Guarantees Lower, or Raise, Banks’ Non-Guaranteed Lending?” Evidence from Japanese Banks, World Bank Workshop. Woo, D. (2003). “In Search of ‘Capital Crunch’: Supply Factors Behind the Credit Slowdown in Japan,” Journal of Money, Credit, and Banking, 35, 1019–38.

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Banking in Japan   1075 Wu, W. and Xu, L. L. (2005). “The Value Information of Financing Decisions and Corporate Governance During and After the Japanese Deregulation,” Journal of Business, 78, 243–80. Wu, X. and Yao, J. (2012). “Understanding the Rise and Decline of the Japanese Main Bank System: The Changing Effects of Bank Rent Extraction,” Journal of Banking and Finance, 36, 36–50. Yamori, N. and Harimaya, K. (2010). “Efficiency in the Japanese Trust Banking Industry: A Stochastic Distance Function Approach,” Banks and Bank Systems, 5, 86–95. Yamori, N. and Murakami, A. (1999). “Does Bank Relationship have an Economic Value? The Effect of Main Bank Failure on Client Firms,” Economics Letters, 65, 115–20. Yamori, N., Harimaya, K., and Tomimura, K. (2017). “Corporate Governance Structure and Efficiencies of Cooperative Banks,” International Journal of Finance & Economics, 22, 368–78. Yasuda, A. (2007). “Bank Relationships and Underwriter Competition: Evidence from Japan,” Journal of Financial Economics, 86, 369–404.

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chapter 34

Ba n k i ng i n A fr ica Thorsten Beck, Robert Cull, and Patricio Valenzuela

34.1 Introduction Banking in Africa has undergone dramatic changes over the past three decades.1 While the continent was dominated by government-owned banks until the 1980s and subject to restrictive regulation—including interest rate ceilings and credit quotas—financial liberalization, institutional and regulatory upgrades, and globalization have changed the face of financial systems across the region. Today, most countries have deeper and more stable financial systems, although challenges of concentration and limited competition, high costs, and limited inclusion persist. This chapter takes stock of the current state of banking systems across Sub-Saharan Africa2 and discusses recent developments including innovations that could help Africa leapfrog more traditional banking models. We use an array of different data sources to document different dimensions of the development of African banking systems, highlighting variation within the region and changes over time. We compare Africa’s banking systems to those of comparable low- and lower-middle income countries outside the region, and gauge whether there is an “Africa-specific” element to banking development. We also discuss progress in policies and institutions underpinning 1  This chapter’s findings, interpretations, and conclusions are entirely those of the authors and do not necessarily represent the views of the World Bank, its Executive Directors, or the countries they represent. 2  In the following we will use Sub-Saharan Africa and Africa interchangeably. However, the analysis in this chapter focuses almost exclusively on Sub-Saharan Africa thus excluding Northern Africa. While some of the characteristics of Sub-Saharan African financial systems extend to Northern Africa, there is a similar variation across countries in the northern part of the continent, ranging from a fairly developed system in Morocco to rather shallow financial markets in Tunisia and Egypt, to a state-dominated financial system in Algeria. Beck et al. (2011) offer a discussion of both Sub-Saharan and Northern African financial systems.

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Banking in Africa   1077 financial deepening and the results of specific innovations, including innovative branch expansion programs, mobile banking, and new financial products designed to reach out to previously unbanked population segments. We also focus on challenges in long-term finance and the recent patterns and regulatory implications of cross-border banking in the region. Overall, we will show a picture of achievements and challenges, with progress along some fronts but with other challenges persisting and new ones arising. When talking about financial systems in Africa, one has to take into account the enormous variation within the region. On the one hand, South Africa and Mauritius have relatively developed banking systems and capital markets. On the other hand, smaller and poorer countries, such as South Sudan or Sierra Leone, have shallow banking systems offering only the most rudimentary financial services, with few if any non-bank financial institutions or capital markets. In spite of the variation within the region, however, there are four specific characteristics that make banking in Africa more difficult than in other regions of the developing world, and most of those apply to many, if not all, African economies (see Honohan and Beck, 2007; Beck et al., 2011). First, the small size of many economies does not allow financial service providers to reap the benefits of scale economies. The limited demand for savings, insurance, credit, or even simple payment transactions means that large parts of the population of African economies are not commercially viable customers. The dispersion of population in many African countries means that financial service provision outside urban centers is not cost-effective. Second, large parts of the economy and a large share of all economic agents operate in the informal sector and do not have the necessary formal documentation that facilitates financial transactions, such as enterprise registration, land titles, or even formal addresses. This increases the costs and risks for financial institutions and excludes large segments of the population from formal financial services. Third, volatility increases costs and undermines risk management. At the individual level, volatility is related to informality and the consequent fluctuations in the income streams of many microenterprises and households. This means these agents are less attractive for financial institutions. At the aggregate level, volatility refers to the dependence of many African economies on commodity exports, which makes economies vulnerable to the large price swings characteristic of commodities, as well as to political and social unrest, from which Africa has suffered over the past fifty to sixty years of independence. Finally, governance problems continue to plague many private and government institutions throughout the continent and undermine not only the market-based provision of financial services, but also reform attempts and government interventions aimed at fixing market failures. These characteristics make banking in Africa more challenging and increase the need for innovative solutions. Technology can potentially reduce transaction costs and risks, thus enabling the processing of smaller transactions, and turning more households and enterprises into commercially viable clients. Innovative products and delivery channels can address the constraints discussed above. Critically, these interventions and policy reforms have to work both on the supply and demand side. In what follows we will discuss several examples of such innovative approaches to financial inclusion.

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1078   Banking Systems Around the World The recent crisis in the developed world has shed doubt on the positive impact that large, complex banks can have on economic development (Allen et al., 2014b; Arcand, Berkes, and Panizza,  2015), in contrast to extensive literature illustrating a positive finance–growth relationship (Levine, 2005). Consumer credit booms in the US and several European countries, fueled by a combination of the liquidity glut linked to the global macroeconomic imbalances, regulatory neglect and the feeling that “this time is different,” ended in the global financial crisis. If there is a lesson to be learnt for Africa’s banking systems from the crisis, it seems that the growth benefits of financial deepening can only be reaped in a stable macroeconomic environment and with the appropriate safeguards framework, both in terms of external regulation and supervision and internal bank governance. Notwithstanding the recent negative experience in countries with the deepest financial sectors, banking systems in Africa can and must play a critical role in the economic development process of the region. The remainder of this chapter is structured as follows. Section  34.2 documents ­financial development across different dimensions, in international comparison, but also illustrating variation within the region and over time. Section 34.3 discusses recent evidence on policies and interventions that can help deepen and broaden financial ­systems in Africa. Section 34.4 focuses on challenges of long-term finance in the region and presents recent patterns in cross-border banking in the region and its regulatory implications. Section 34.5 concludes and looks forward.

34.2  Stock-Taking: Where Does Africa Stand? Earlier stock-taking exercises of banking and finance in Africa suffered from a lack of data for a broad cross-section of countries in the region (Honohan and Beck, 2007). Most cross-country studies on financial development included only a few larger African financial markets and their focus was on other developing and emerging regions of the world. This situation has changed over the past decade, with data available for a large part of the region and several segments of the financial system. Relatively recent global data collection efforts on the depth, outreach, stability, and efficiency of financial systems have been much more successful in collecting data on African financial systems.3 Aggregate data have been complemented with a number of enterprise surveys, and ­surveys for some countries now have a panel dimension (i.e., firms being surveyed at several points in time).4 Similarly, household surveys focused on financial services, such 3  See Beck, Demirgüç-Kunt, and Levine (2000, 2010); Demirgüç-Kunt and Klapper (2012); Laeven and Valencia (2013). 4  For example, the World Bank’s Enterprise Surveys now offer an expansive array of economic data on 131,000 firms in 139 countries. For the case of Africa, the Enterprise Surveys team has already released survey data for forty-three Sub-Saharan African countries.

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Banking in Africa   1079 as the Finscope and Finaccess surveys in several African countries, have provided important insights into individual and household access to, and use of, formal and informal financial services, while the Global Findex dataset includes most countries in Sub-Saharan Africa. In the following, we will therefore use an array of databases and other sources to document the development and structure of banking systems across the region.

34.2.1  Aggregate Financial Development in Africa in International Comparison Africa’s banking systems are small, costly, and focused on the short-term end of the yield curve as we will illustrate in the following. However, we will also document the progress Africa’s banking systems have made over the past fifteen years. To compare banking systems in Africa to a proper benchmark, we limit our sample to low- and lower-middle-income countries in Sub-Saharan Africa and compare the median for this group to the median country across a sample of low- and lower-middle-income countries outside Africa. We thus explicitly drop several upper-middle-income African countries in our statistical comparison, although we will include them in the discussion on intra-regional variation below.5 Figure 34.1 shows that the median African country has a markedly shallower financial system than the median non-African country. We present three standard indicators of financial development: liquid liabilities to GDP, Bank Deposits to GDP and Private Credit to GDP, using data for 2015.6 While the median non-African developing country has liquid liabilities of 41 percent of GDP, the median African country has only 31 percent. Similarly, the median deposit to GDP ratio outside Africa is 40 percent, compared to 22 percent in Africa, while the median Private Credit to GDP ratio is 37 percent outside Africa, but only 17 percent inside Africa. Comparing the difference between deposit and credit ratios also indicates that African banks are less effective in intermediating society’s savings, a topic we will return to below. It is important to note that the median ratios mask wide variation across Africa. Figure 34.2 shows that even excluding the most financially developed African economies, such as Mauritius and South Africa, there is a wide range in Private Credit to GDP across the low- and lower-middle-income countries of the region, from 1.6 percent in South Sudan to 61 percent in Cape Verde. The median country is Zambia with a Private Credit to GDP ratio of 17 percent. This compares with 146 percent in South Africa and 102 percent in Mauritius.

5  The countries not included in the statistical comparison are: Botswana, Equatorial Guinea, Gabon, Mauritius, Namibia, Seychelles, and South Africa. 6  In our analyses, 2015 data are available for most countries in our sample. We employ 2014 data when 2015 data are not available.

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1080   Banking Systems Around the World 45 40 35 30 25 20 15 10 5 0

Liquid liabilities to GDP (%)

Bank deposits to GDP (%)

Non-African developing countries

Private credit by deposit money banks and other financial institutions to GDP (%)

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Figure 34.1  Aggregate Financial Development in International Comparison, 2015. Source: Global Financial Development Indicators (June 2017 version), World Bank.

While Africa’s financial systems are shallow in international comparison, there have been marked improvements over the past decade. All three standard indicators of financial development have substantially improved over the period 2000 to 2015.7 Figure 34.3 shows that the median value for Private Credit to GDP increased from 9 percent to 18 percent, with similar increases in the other two indicators of financial development. And this improvement has been broad based. If one considers the 25th, 50th, and 75th percentiles of private credit to GDP over the same period, it is evident that countries at different points of the distribution have all witnessed improvements. Despite the improvements in the domestic financial African markets, financial development gaps persist as developing countries outside Africa have also exhibited significant progress. In fact, Figure 34.3 shows that the gap between Africa and the developing world outside Africa has widened in terms of private credit, though it has remained the same for deposits to GDP and has even decreased for liquid liabilities to GDP (not shown). Africa’s banking systems are not only shallower than banking systems in non-African developing countries, they are also less inclusive (Figure 34.4). Here we present four indicators of access to, and use of, financial services. First, we present two aggregate indicators: bank accounts per 100 adults and bank branches per 100,000 adults. Both indicators are substantially lower in the median African country than in the median non-African developing country. Specifically, there are only fifteen bank accounts for every 100 adults 7  The median is computed over a balanced sample of thirty-two African countries and twenty-eight non-African developing countries, for which data were available over all sixteen years.

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South Sudan Sierra Leone Congo, Dem. Rep. Sudan Chad Malawi Guinea-Bissau Central African Republic Madagascar Guinea Gambia, The Uganda Tanzania Nigeria Niger Cameroon Zambia Ghana Burundi Lesotho Rwanda Swaziland Congo, Rep. Cote d'Ivoire Benin Angola Mali Comoros Sao Tome and Principe Burkina Faso Mozambique Senegal Kenya Togo Cape Verde

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Figure 34.2 Private Credit to GDP across Low- and Lower-middle-income African Countries, 2015. Source: Global Financial Development Indicators (June 2017 version), World Bank.

45 40 35 30

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Figure 34.3  Private Credit to GDP (%). Source: Global Financial Development Indicators (June 2017 version), World Bank.

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1082   Banking Systems Around the World 65 60 55

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Account at a formal financial institution (% age 15+), 2017

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Figure 34.4  Access to and use of Financial Services in International Comparison, 2010–17. Source: Global Financial Development Indicators (June 2017 version), World Bank.

in the median African country, while there are fifty-one outside Africa. There are four branches per 100,000 adults in Africa, while there are ten outside Africa. Second, the more limited outreach of Africa’s banking systems is also reflected in indicators of use of formal finance by enterprises and households. While in the median African country only 16 percent of firms indicate that they have a line of credit or loan from a formal financial institution, this share is 35 percent outside Africa.8 Similarly, 33 percent of adults in the median African country (excluding high-income countries) indicate that they have an account with a formal financial institution, while this share is 65 ­percent outside Africa. By 2015, Africa’s banks were, on average, less efficient, but more profitable and operated in less competitive environments. Net interest margins in the median African country stood at 5.7 percent, while they stood at 4.5 percent outside Africa. Similarly, the interest rate spread between lending and deposit rates was 7.6 percent in Africa and 7.2 percent outside. While there are many reasons that spreads and margins are higher in Africa, one important reason is higher operating costs. Specifically, overhead costs in the median African financial system stood at 5 percent of total assets, while they were 1.7 percent outside Africa. On the other hand, African banks are also more profitable than banks outside Africa. The return on assets (ROA) stood at 2.1 percent in the median 8  Unlike the previous comparisons, which are all for 2015, data for Enterprise Surveys were averaged over 2010 to 2015. Comparisons from the Global Findex Database are for 2017.

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Banking in Africa   1083 African country, while it was 1.2 percent outside Africa. We will revisit this issue below with bank-level data. The higher interest rate spreads go hand in hand with greater concentration and lower competitiveness in African banking markets. While the share of the five largest banks was 87 percent in the median African country in 2015, it was 73 percent outside Africa. Higher interest rate spreads are related to greater concentration across a sample of African countries. While there are several countries in Africa where aggregate data point to five banks making up the whole banking system (Benin, Burkina Faso, Burundi, Cameroon, Cape Verde, Madagascar, Malawi, Mali, Mauritania, and Togo), there are only a few such countries among the much larger group of non-African developing countries. Greater concentration, however, does not seem to come with lower competition: The median Lerner index, which is the markup between marginal revenue and costs, was 29 percent in the median African country in 2015, while it was 36 percent outside Africa. It is important to note that the correlation between concentration and the Lerner index of market power is relatively low within Africa, at only 0.35, in comparison with the 0.81 outside Africa. This suggests that market structure is only one, and maybe not the most important, determinant of the lack of competition within Africa, consistent with cross-country evidence (Claessens and Laeven, 2004). Africa’s banking systems have focused mostly on the short-end of the yield curve, as illustrated by the maturity structure on both the asset and liability sides of African banks’ balance sheets. Using data for the 2005–9 period, Beck et al. (2011) show that more than 80 percent of deposits are sight deposits or deposits with a maturity of less than one year and less than 2 percent of deposits have a maturity of more than ten years. There is a similar, though not as extreme, bias toward the short-end on the lending side. During the 2005–9 period, almost 60 percent of loans were for less than one year, and less than 2 percent of loans were for more than ten years. However, it is noteworthy that the maturity structure of bank loans has extended in the last decade. Figure 34.5 shows that the proportion of short-term loans has decreased, in some cases substantially, in all African countries with available data. One striking case is Guinea-Bissau that in the last decade reduced the proportion of short-term loans from 96 percent to 31 percent. The maturity distribution mentioned above is consistent with the dearth of non-bank long-term financial instruments, including the limited development of contractual savings institutions, such as insurance companies, pension funds, and mutual funds. Fewer than half of the countries in the region have stock exchanges and few of them are liquid. Another indication of the short-term nature of African banking is the dearth of mortgage finance. While mortgage depth to GDP in the median African country was below 1 percent, it was above 2 percent outside Africa (Badev et al., 2013). These aggregate numbers match with anecdotal evidence that mortgage systems in many smaller African countries comprise just a few hundred mortgages, concentrated among wealthy individuals. While shallow, Africa’s banking systems have also proven stable and resilient over the past years. The shallowness of Africa’s banking systems appears to have helped them weather the global financial crisis of 2008 better than some other regions of the world,

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1084   Banking Systems Around the World 100 90 80 70 60

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Figure 34.5  Short-term Loans as Percentage of Total Loans. Source: African Financial Sector Database 2016, African Development Bank Group.

with the impact of the crisis on Africa mostly working through real sector channels, such as lower demand for export goods, or through lower foreign direct investment. Given the limited integration with global financial markets and exposure to “toxic” assets, financial institutions across the region largely evaded the direct impact of the global financial crisis. Greater stability is also illustrated in the aggregate balance-sheet indicators of African banks. In 2015, the capital to risk-weighted asset ratio was 18 percent in the median African country, compared to 17 percent outside Africa. On the systemic level, Africa has suffered few banking crises since the bout of systemic fragility in the 1980s and 1990s (Laeven and Valencia, 2013). Notwithstanding these positive headline indicators, pockets of (hidden) fragility continue to exist, often related to political crisis and/or governance deficiencies. The shallowness of African financial markets is not surprising given the region’s low levels of economic development and the four characteristics mentioned above—small size, informality, volatility, and institutional governance problems. However, many of the non-African low- and lower-middle-income countries suffer from similar problems. Is there an Africa-specific element to financial underdevelopment? We address this issue next, before documenting in more detail specific dimensions of African banking,

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Banking in Africa   1085 including the structure and efficiency of banking systems, and enterprise and household access to financial services.

34.2.2  Benchmarking Africa’s Banking Systems As suggested by Figures 34.1 and 34.3, despite extensive economic and financial sector reforms over the last few decades, many Sub-Saharan African countries still face financial development gaps relative to other developing countries. In short, the level of financial development and credit penetration in Africa is still low compared to other parts of the developing world, but it is also low relative to what would be predicted based on underlying factors that are associated with financial development. Cross-country regressions to benchmark African financial development and inclusion based on its correlates in other low- and middle-income countries reveal a substantial gap between predicted and actual levels of African financial development and inclusion. Figure  34.6 shows that predicted 2011–15 levels of private credit/GDP tended to be higher for most African countries than their actual levels. While in a few countries the 100

MUS

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BFA MOZ BEN CIV LSO BDI GMB GHA NGA MWI CMR TZA GAB COG ZMB UGA GNQ SLE

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70

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Figure 34.6 Private Credit/GDP (%) in African Countries 2011–15, Actual vs. Predicted Values. Note: Predicted values of banking sector development, measured by credit to the private sector extended by deposit money banks/GDP, come from OLS regressions that control for a set of country-level variables including total population, population density, natural resources rents/GDP, GDP per capita, economic growth, consumer price inflation, manufacturing value added/GDP, primary school enrollment, and six different dimensions of governance (Voice and Accountability, Political Stability and Absence of Violence, Government Effectiveness, Regulatory Quality, Rule of Law and Control of Corruption). Note that negative predicted values are replaced by zero. Source: Authors’ calculations.

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1086   Banking Systems Around the World actual levels of financial development exceed predicted levels, most African countries still face underdeveloped credit markets. Specifically, the figure shows that a third of the countries have levels of private credit to GDP that exceed their predicted levels. However, Mauritius (MUS) and South Africa (ZAF) are not particularly representative of the African experience, and Liberia (LBR), Central African Republic (CAF), Chad (TCD) and South Sudan (SDN) are in the lower left-hand corner of the figure where both actual and predicted values are very low. Regarding financial inclusion, demand-side evidence from the 2017 Global Financial Inclusion Database (Global Findex) suggests that financial institutions are not providing as much credit to all segments of the African population as they do in non-African developing countries. The average share of respondents that reported having borrowed from a financial institution or used a credit card in the past year was 9 percent in Africa, compared with 16 percent in the rest of the developing world. This is also confirmed in cross-country regressions using 2017 Findex data based on the correlates of credit usage in other developing countries. Specifically, we find that the predicted share of Findex respondents that had a loan from a financial institution in the past year exceeds the actual share in almost all cases. Only Botswana, Ethiopia, Kenya, South Africa, and Tanzania exhibit higher actual than predicted levels. The case of Kenya is quite remarkable and, as we highlight later, seems to be influenced by the emergence of Equity Bank, a pioneering institution that devised a banking service strategy targeting low-income ­clients and traditionally underserved territories. Though the tools used are crude, the benchmarking regressions indicate that private credit provision in Africa, though improving somewhat, lags behind what fundamentals would predict, and that the allocation of what credit there is does not extend deeply into the population. To a much lesser extent, there is evidence of development gaps on the savings side. The smaller number of countries with gaps on the savings side suggests that Africa has been more effective in the provision of basic, rather than more sophisticated, banking services. In addition, both country- and firm-level tests indicate that the correlates of banking development in Africa differ from the rest of the world. For example, Allen et al. (2014a) show that measures of the quality of macroeconomic management (inflation and the current account balance) are not correlated with African financial development as they are in other developing countries. Measures of institutional development (such as adherence to rule of law) are positively linked to African financial development, though substantially less strongly than in other parts of the developing world. Allen et al. (2014a, 2016) also show that the most striking difference is that population density is more strongly linked to financial development in Africa than elsewhere. Population density is also more closely linked to bank branch penetration in Africa than in other developing economies, and both are more strongly linked to firm-level access to external finance in Africa than elsewhere. Presumably, bank branch penetration figures remain low in Africa because of difficulties in achieving minimum viable scale in sparsely populated, low-income areas, though below we discuss financial institutions, strategies, and technological innovations that are rising to meet that challenge.

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Banking in Africa   1087

34.2.3  Drilling Deeper—Bank- and Branch-Level Evidence While the aggregate data already give us some indication of the shallowness of African banking systems, bank- and branch-level data provide more detailed insights. Comparing a sample of 307 banks from low- and lower-middle-income countries in Africa and 720 banks from non-African developing countries shows significantly higher liquidity ratios for African banks. Specifically, the ratio of liquid assets to short-term funding and deposits is 42.9 percent for African banks, as compared with 29.3 percent for nonAfrican banks. Similarly, African banks are better capitalized, with an equity-asset ratio of 14.3 percent, compared with 13.3 percent for non-African banks. These comparisons give a picture of African banks that are well capitalized, over-liquid and provide only limited lending to the real economy, as highlighted previously by Honohan and Beck (2007) and Beck et al. (2011). As discussed above, African banks are less efficient than banks in other developing regions of the world and financial services are therefore more expensive. A lot of discussion in this context has focused on interest rate spreads and margins, that is, the difference between lending and deposit interest rates. But what drives high interest rate spreads in Africa? There are three different ways to analyze spreads and margins. The first one is a decomposition of spreads into their different components. The second is to analyze the relevant underlying bank-, industry-, and country-level traits. Finally, the third way of understanding interest rate spreads in Africa is by exploring their levels across different geographic areas within a country. Table 34.1 presents a decomposition of interest rate spreads for Uganda and shows that high operating costs are one important factor, while loan loss provisions reflecting loan losses and reserve requirements are rather minor components of the interest rate spread. The highest component of interest rate spreads, however, is the high profit ­margin, consistent with limited competition, but also a high-risk premium. Comparing domestic and foreign-owned banks, we see that domestic banks have higher spreads, due to higher lending rates, which most likely reflects a riskier loan portfolio. The spread

Table 34.1  Decomposition of Interest Rate Spreads in Uganda in 2008

Average Lending Rate Average Deposit Rate Spread Overhead Costs Loan-loss Provisions Reserve Requirements Taxes Profit Margin Source: Cull and Trandafir (2010).

All Banks

Domestic

16.72 1.97 14.75 4.66 0.72 0.22 2.51 6.65

18.44 2.31 16.13 2.74 0.38 0.26 3.34 9.42

Foreign 15.24 1.9 13.34 6.22 1.01 0.21 1.64 4.26

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1088   Banking Systems Around the World

Table 34.2  Explaining Overhead Costs in Africa Overhead costs African banks Rest of World banks Difference Of which: Contractual framework   Non-interest income   Banks size   Equity-asset ratio    Other bank characteristics Inflation Africa residual

605 451 154 12 93 18 5 −3 11 18

Source: Authors’ calculations using data from Bankscope.

decompositions indicate that domestic banks generate high profit margins from a group of borrowers that repay their loans at a higher rate than clients of foreign banks. The ­relatively high overhead costs and low profit margins for the foreign banks could be consistent with the idea that they deal with a set of “blue-chip” clients whose projects are costlier to evaluate and maintain. In addition, higher wages might add to their costs, though higher costs could also result from foreign banks’ propensity to invest more, including in IT and technology to develop new products.9 Table 34.2 uses regression analysis to relate bank-level variation in overhead costs to bank- and country-level characteristics and compares banks in Africa with banks in non-African developing countries. Since overhead costs is one of the major components of interest rate spreads, we regress overhead costs in 2011 for a cross-country sample of banks on (1) the share of non-interest income, (2) the equity–asset ratio, (3) the liquidity ratio, (4) loan growth over the previous year, (5) the log of total assets, (6) the inflation rate and (7) the Kaufmann, Kraay, and Mastruzzi indicator of Rule of Law. The results in Table 34.2 indicate the extent to which these different factors contribute to the substantially higher overhead costs of banks in Africa (6.05 percent) than in banks outside Africa (4.51 percent). Relatively high reliance by African banks on non-interest income and their smaller size can explain 93 and 18 basis points, respectively, of the difference in overhead costs. Higher inflation in African countries and less efficient contractual frameworks can explain 11 and 12 basis points, respectively. Even after accounting for these bank and country characteristics, there is still an unexplained Africa residual of 18 basis points. Allen et al. (2018) use branch-level data to better understand Equity Bank’s interest rate spreads across different geographic areas in Kenya. Their findings are consistent with a more aggressive pricing schedule by Equity Bank in areas largely ignored by its competitors, as is reflected in higher lending-deposit interest rate spreads in arid and 9  For a more detailed discussion, see Cull and Trandafir (2010) and Beck et al. (2011).

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Banking in Africa   1089 semi-arid counties. Since holding a bank account and/or a loan with Equity Bank was the only option for many customers in less-developed areas to keep their money safe and/or finance their business projects, the bank was able to combine the pursuit of financial inclusion with low interest paid on deposits and relatively high interest charged on loans in less-banked regions. As discussed earlier, the ownership structure of Africa’s banking systems has ­undergone notable changes over the past decades. Today foreign-owned banks play an increasingly important role in Sub-Saharan Africa, while government-owned banks are less prominent (Cull, Martínez Pería, and Verrier, 2018). Although foreign-owned banks have been present in Africa since the colonial era, their participation increased following the privatization wave in the 1980s and 1990s, and the reforms that liberalized the financial sectors in the 1990s and early 2000s. In particular, the median share of assets held by foreign-owned banks rose from 34 percent in 1995 to 73 percent in the latest year for which data are available for each country from 2010 to 2013. Long dominated by European banks, banks from emerging markets and—critically—from inside Africa have gained importance over the past decade. After the end of Apartheid, several South African banks, most notably Standard Bank and ABSA, started expanding throughout the continent. More recently, two West African banks—Ecobank and Bank of Africa— have begun expanding throughout Sub-Saharan Africa. Similarly, Moroccan banks have started to expand southwards. Finally, and as a consequence of the recent bank consolidation wave in Nigeria and Kenya (Beck et al., 2014), banks from those economies also started expanding throughout the rest of the continent. We will return to the topic of cross-border banking and regulatory implications in section 34.4.2.

34.2.4  Enterprise Access to Finance in International Comparison The World Bank’s Enterprise Surveys allow us to dig deeper into the international ­comparison of enterprise access to finance and distinguish between firms of different sizes. Using data from the period 2013–17, Figure 34.7 shows, as expected, that larger firms are more likely to have an account and/or a loan from a formal financial institution in both African and other developing countries. The figure also shows that the disadvantage African firms have relative to firms in other developing economies is particularly striking in terms of access to credit. Across all three size groups, enterprises within Africa are less likely to have a loan than enterprises outside Africa. On the payment/savings side, the vast majority of firms use formal accounts in both African and non-African developing countries, and the differences between firm size groups are very similar. Enterprise survey data also provide the self-reported reasons why enterprises do not have loans with formal financial institutions. Specifically, enterprises are asked for the reason why they did not apply for a loan with a formal financial institution over the past year. The share of enterprises that quote the lack of demand is substantially lower in Africa (43 percent) than in other developing countries (62 percent), suggesting that lack

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1090   Banking Systems Around the World 100 90 80 70 60 50 40 30 20 10 0

Sub-Saharan Africa Non-African developing 2013–2017 countries 2013–2017 Account

Small (5–19)

Sub-Saharan Africa 2013–2017

Medium (20–99)

Non-African developing countries 2013–2017 Loan

Large (100+)

Figure 34.7 Use of Formal Account and Loan Services across Firm Size Groups in International Comparison, 2013–17. Source: Authors’ calculations based on World Bank’s Enterprise Surveys.

of demand is a less important factor in the African context. High interest rates were also mentioned as a reason for not applying for loans (14 percent in Africa vs. 10 percent in other developing countries), which could indicate that the return on investment projects is too low. On the other hand, and as noted by many observers of African finance, the high cost of credit might impede the use of bank finance. Interest rate spreads and thus lending rates are notably higher in Africa than in non-African developing countries. Those high costs of credit can be explained not only by the lack of competition described above, but also by monetary and socio-political instability resulting in a highrisk premium. The importance of monetary and socio-political stability can be appreciated when considering that the share of non-applicants due to high interest rates is especially high in unstable countries such as the Democratic Republic of the Congo (DRC) and Zimbabwe. Even more striking than the differences based on the perceptions of high interest rates is the difference in the share of respondents, indicating that application procedures are the reason for not applying: 16 percent of non-applicant enterprises in Africa as opposed to 7 percent in other developing countries. Collateral requirements also seem to be a greater impediment in Africa than in other regions of the developing world (9 percent vs. 4 percent), as is the need for bribes (4 percent vs. 2 percent). These data point to a large array of barriers both on the macroeconomic but also the bank-specific levels for enterprises in Africa to access formal sources of external finance.

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Banking in Africa   1091 The financing of small and medium-sized enterprises thus continues to pose a s­ ignificant challenge, and not only for African financial systems. However, it is important to distinguish between segments within this group of enterprises that have different financing needs and profiles. A large share of the enterprises in Africa is comprised of informal microenterprises whose establishment often stems from the lack of alternative economic opportunities. Not being able to produce formal financial accounts or formal guarantees, it is hard to see this segment of the enterprise population becoming bankable over the medium to long term, at least not for credit services.10 They seem a natural target group for microcredit institutions and rely more heavily than other enterprises on informal finance providers. A second segment is medium-sized enterprises, often well-established and export-oriented companies. In most cases they have access to bank finance, but struggle to get access to equity finance, including through financial markets. Finally, there are small formal enterprises, some of which might have high growth potential. These firms—often also referred to as the missing middle—are usually too big to be serviced by microfinance institutions, but not formal or established enough for banks. It is especially this last segment that seems to be affected by shallow financial markets. This is also illustrated in Figure 34.7, where there is a larger difference in the use of formal loans between small and medium-sized enterprises in Africa (13 percent vs. 23 percent) than outside Africa (27 percent vs. 35 percent).

34.2.5  Household Access to Finance in International Comparison Figure 34.8 shows a significant increase in the share of households with a bank account in the median country in Sub-Saharan Africa, between 2011 and 2017, increasing from 17 percent in 2011 to 22 percent in 2014 to 41 percent in 2017. This graph shows the median value across the six regions of the developing world (as classified by the World Bank) as well as high-income countries. There has been a general increase in financial inclusion across most regions, as measured by this variable, though there is substantial variation in the extent to which inclusion has increased. The one dimension on which Sub-Saharan Africa stands out is the share of the population with a mobile phone-based account (only data for 2014 and 2017 are available), where the median is significantly higher than in other regions, a topic which we will return to below. In spite of the progress in financial inclusion across the region, there is still a wide variation in account penetration across Sub-Saharan Africa, which ranges from over 80 percent in Mauritius, Kenya, and Namibia to below 10 percent in South Sudan. While this variation partly reflects the variation in income levels, this is certainly not the only factor as Kenya, for example, is the African country with the second highest account penetration in the region, ahead of South Africa with 69 percent. 10  That said, for those with mobile phones, alternative scoring based on usage of digital platforms offers one potential route to better credit access.

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1092   Banking Systems Around the World 120

Account penetration

100 80 60 40 20 0

South Asia

Europe & Middle East & Sub-Saharan Latin America High income East Asia & Central Asia North Africa Africa & Caribbean Pacific median 2011

median 2014

median 2017

Figure 34.8  Account Penetration across Regions, 2011, 2014, and 2017. Source: Global Findex.

Table 34.3 shows account penetration across the three Findex waves for the countries for which data are available for all three years (2011, 2014, and 2017). As can be seen, ­several countries in Sub-Saharan Africa saw dramatic increases in account penetration (led by Kenya with a 39 percentage point increase over the six years and Gabon, Senegal, Togo, and Uganda with increases well above 30 percentage points). In short, while most countries saw an improvement in financial inclusion, as measured by account penetration, progress has been very uneven. The large increase in account penetration in several African countries can be linked to the rise of mobile money accounts, with 73 percent of the population in Kenya having a mobile money account in 2017 and over 40 percent in Namibia, Gabon, Zimbabwe, and Uganda. On the other extreme are countries with repressed financial systems, such as Ethiopia (less than 1 percent), countries in West Africa (Mauritania, Nigeria, Congo, Niger) or countries with very high levels of account penetration (and thus no need for mobile money accounts), such as Mauritius. The Global Findex survey not only allows an aggregate picture of the share of households using formal financial services, but also a more detailed look into which population segments have access to formal financial services. Figure 34.9 shows account penetration across male versus female, the richest 60 percent versus the poorest 40 ­percent and people in and outside the labor force. The gender gap dropped between 2011 and 2014 though it again increased between 2014 and 2017, with males being 40 percent more likely to have a formal financial account than females. It is important to note, however, that these are unconditional comparisons. Using more detailed financial sector surveys for a number of Eastern and Southern African countries, Aterido, Beck, and Iacovone (2013) show that when key observable characteristics of individuals are taken into account, the gender gap disappears. The lower use of formal financial services by women

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Banking in Africa   1093

Table 34.3  Account Penetration over Time and across Countries Country

Account Penetration 2011

Account Penetration 2014

Account Penetration 2017

39.2 10.46 30.26 13.35 7.24 14.81 8.96 10.05 3.7 18.95 29.43 3.69 42.34 5.52 16.54 8.21 17.46 80.12 1.52 29.67 32.76 5.82 15.34 53.65 6.9 17.26 10.19 20.46 21.36 39.65

29.32 16.62 51.96 14.36 7.11 12.18 12.43 17.07 17.48 33.01 40.51 6.96 74.66 8.55 18.09 20.08 22.87 82.21 6.71 44.44 42.12 15.42 15.58 70.32 15.27 39.78 18.25 44.45 35.64 32.39

n.a. 38.49 51.03 43.16 n.a. 34.59 21.76 26.09 25.83 58.6 57.72 23.49 81.57 17.87 33.71 35.42 20.87 89.84 15.52 39.67 50.02 42.34 19.81 69.22 n.a. 46.75 45.29 59.2 45.86 55.29

Angola Benin Botswana Burkina Faso Burundi Cameroon Chad Congo Congo, Dem. Republic Gabon Ghana Guinea Kenya Madagascar Malawi Mali Mauritania Mauritius Niger Nigeria Rwanda Senegal Sierra Leone South Africa Sudan Tanzania Togo Uganda Zambia Zimbabwe Source: Global Findex (2017).

may therefore be explained by gender gaps on other dimensions related to the use of financial services, such as their lower level of income and education, and by their ­household and employment status. On the other hand, the gap between the poorest 40 percent and richest 60 percent closed between 2011 and 2017; while in 2011 the former were only 36 percent as likely as the latter to have a formal financial account, they were 65 percent as likely in 2017. Similarly, those outside the labor force were 28 percent as likely to have a formal financial account as those in the labor force in 2011. By 2017, they were 60 percent as likely. Figure 34.10 shows the same gaps for mobile money account penetration. Men are

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1094   Banking Systems Around the World Panel A: Gender gap 50

Gender gap

40 30 20 10 0

2011

2014 Male

2017 Female

Panel B: Income gap 50 Income gap 40 30 20 10 0

2011

2014 Poorest 40%

2017 Richest 60%

Panel C: Labor force gap 60

Labor force gap

50 40 30 20 10 0 2011

2014 In labor force

Out of labor force

Figure 34.9  Gaps in Account Penetration in Sub-Saharan Africa.

2017

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Banking in Africa   1095 Panel A: Gender gap 30

Gender gap

20

10

0

2014

2017 Male

Female

Panel B: Income gap 30 Income gap 20

10

0

2014

2017 Poorest 40%

Richest 60%

Panel B: Income gap 30

Labor force gap

20

10

0

2014 In labor force

2017 Out of labor force

Figure 34.10  Gaps in Mobile Money Account Penetration in Sub-Saharan Africa.

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1096   Banking Systems Around the World only 25 percent more likely than women to have a mobile money account, the poorest 40 percent half as likely as the richest 60 percent, and people outside the labor force 55 percent as likely as people in the labor force. This suggests that especially the gender gap can be closed through technology. The Global Findex data also allow us to explore the reasons why households do not have accounts with formal financial institutions. In the median African country, 73 percent of respondents without an account with a formal financial institution cite lack of money as a reason, 27 percent cite high costs, and 28 percent report lack of the necessary documentation as an impediment; 25 percent point to geographic barriers, while 15 percent cite lack of trust in financial institutions. Finally, 6 percent report religious reasons for not having a formal bank account,11 while 10 percent point to someone else in the family having an account.

34.3  Overcoming Barriers to Financial Inclusion: Branch Expansion, Field Experiments, and Technology Africa has made substantial progress over the past decade, not only in financial depth and inclusion, but also in underlying macroeconomic stability, with few countries presenting double-digit inflation rates. Similarly, there has been some underlying institutional progress, including in creditor rights, contract enforcement and credit information sharing. Specifically, the average cost of property registration dropped from 13 percent to 7.8 percent of property value between 2004 and 2017, while creditor rights increased from an average of 4.2 to an average of 5.2 (on a ten-point scale) over the same period. While in 2004, fewer than half of the countries had a public or private credit registry, in 2017 more than 80 percent of countries in the region had one. The average cost of contract enforcement decreased from 56 percent of the average claim in 2004 to 47 percent in 2017.12 While macroeconomic management and institutional development have thus shown a certain degree of improvement, the benchmarking exercise discussed in section 34.2.2 suggests that these are necessary and not sufficient conditions for financial deepening in Sub-Saharan Africa and that other barriers, including geographic disadvantages, hold back the further deepening of African banking systems. Financial innovation, that is, new delivery channels, new players, and new products, can help overcome these barriers, especially geographic barriers. Africa has seen substantial innovation on this front 11  This might be related to the Sharia prohibition of interest payment. The share that cite religious regions as an impediment to having a bank account is typically higher in countries with a significant Muslim population. 12  These numbers are based on data from the Doing Business database (http://www.doingbusiness.org.)

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Banking in Africa   1097 over the past decade, as reported by Beck et al. (2011). Much of it comes from different financial institutions, banks, NGOs, and MFIs, both domestic and foreign-owned, often with support from donors. In many countries, regulators have reacted flexibly, opening space for innovation within existing regulatory frameworks or adjusting them where necessary. In this section, we report on different forms of financial innovation, summarizing research findings on the recent branch expansion by some banks into more sparsely populated areas and the potential for banks to use agent networks to further extend their reach. Agents are typically owners of small retail businesses who are trained by a formal financial institution (most often a bank or a microfinance institution) to collect deposits and process payments, including payments on small-scale loans (Lyman, Ivatury, and Staschen, 2006; Siedek, 2008; Flaming, McKay, and Pickens, 2011). We also summarize results from recent field experiments in Africa that are beginning to shed light on the types of financial services that could benefit underserved market segments and overcome impediments to their uptake. Finally, we explore the role that technological innovation could play in bridging some of the geographic and informational divides that currently characterize the African financial landscape.

34.3.1  Bank Branching Kenya represents a good example of an African country that has experienced a significant bank branch expansion in recent years. According to the World Bank’s Global Financial Development Dataset, the total number of bank branches in Kenya increased from 2.98 per 100,000 adults in 2004 to 5.85 in 2015, while the number of ATMs increased from 2.49 per 100,000 adults to 10.16 in the same period. While many Kenyan banks, including some state- and foreign-owned ones, expanded their branch footprints during this period, the expansion strategy of one private domestic bank in particular, Equity Bank, stood out for its potential impact on outreach to under-served market segments. This institution has played a key role in fostering financial inclusion in Kenya and in neighboring countries in East Africa while remaining profitable in the process. In the period 2006–16 its client base grew from 1 million to 11 million people, making Equity Bank the largest bank in Africa in terms of customers. As part of its expansion strategy, Equity Bank emphasized that local languages be spoken in its branches, an important consideration since 30–40 percent of the people in central Kenya do not speak English or Swahili. At the same time, according to the Financial Times’ 2014 ranking of the world’s Top 1,000 banks, Equity Bank generated the highest rate of return in Africa with a return on assets of 6.8 percent and a return on capital of 54.9 percent. Allen et al. (2018) use the case of Equity Bank to explore the relationship between bank branch expansion, financial inclusion and bank profitability. Using instrumental variables and difference-in-differences techniques, the paper finds that the presence of Equity Bank branches has a positive and significant impact on households’ use of

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1098   Banking Systems Around the World bank accounts and bank credit.13 Across estimation techniques, Equity’s presence was associated with a 4 to 9 percentage point increase in the probability of having a bank account. Similar regressions confirm that Equity’s presence was associated with an increase in borrowing, although loan use increased less dramatically, from 2.9 percent of respondents in 2006 to 4.4 percent in 2009. Additionally, the study finds that the impact of Equity Bank’s expansion into underserved territories was particularly strong for Kenyans who are less educated, do not own their own home, and live in less-developed areas. In all, Equity Bank’s experience in Kenya and those of a handful of banks in other developing countries suggest that it might be possible to generate sustainable profits with a business model focused on the provision of financial services to population segments that are typically ignored by commercial banks.14 At the same time, the number of studies is small (and most are not from African countries) making it hard to identify the factors that lead to the successful adaptation of those strategies. As noted above, another potential method for promoting financial inclusion in sparsely populated areas is agent banking.15 For example, a review of the Latin American experience suggests that agents have been effective in reaching the unbanked (Alliance for Financial Inclusion, 2012). In Kenya, Equity Bank has also moved forcefully into agent banking, expanding its number of agents from under 1,000 in early 2011 to over 6,000 by the end of 2012. By that point, agents accounted for over 30 percent of Equity Bank’s total transactions. Rigorous studies of the effects of agent banking in Africa are beginning to emerge. For example, Finca DRC’s over 500 agents handle over 65 percent of the transactions of one of the largest microfinance institutions in the DRC, and regression analysis of agent activity indicates that they have been successful in reaching the urban poor (Cull et al., 2018). Access to agents also holds the potential to influence clients’ financial behavior. A recent field experiment in Senegal shows that individuals encouraged to open a no-frills account with an agent subsequently performed more transactions than those encouraged to open the same account at a branch, and their account balances also increased suggesting that access to agents made it easier for them to save (Buri et al., 2018). In short, there are encouraging signs that agents of African banks and MFIs can reduce transactions costs enabling poorer clients to become more financially active, though 13  For similar studies, see Bruhn and Love (2014) on the extension of Banco Azteca in Mexico; Burgess and Pande (2005) on an exogenous change in branching restrictions in India to identify the effects of increased branch penetration on poverty reduction; and Brown, Guinn, and Kirschenmann (2016) who document substantial gains in financial inclusion associated with the expansion of a major microfinance provider (ProCredit) in Albania, Bulgaria, Macedonia, and Serbia. 14  Allen et al. (2018) provide detailed evidence of how Equity Bank’s business model is profitable both at the bank and branch level since it allowed the bank to pursue an aggressive loan pricing schedule, reduce delinquency rates, and secure inexpensive funding in the form of retail deposits. 15  Anecdotal evidence suggests that agent banking allows overcoming not only geographic but also socio-cultural barriers that might prevent low-income population segments from entering formal bank offices.

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Banking in Africa   1099 early results indicate that this is through cash-in/cash-out transactions and, to a lesser extent, savings rather than credit.

34.3.2  Assessing Tailored Product Interventions with Randomized Field Experiments Although the number of field experiments based on randomized controlled trials (RCTs) in Africa involving financial services is low, patterns are beginning to emerge that point to key impediments to broader financial inclusion. On the savings side, commitment devices that enable users to guard accumulated funds from outside demands (often from relatives and friends) have led to increased investment and more rapid growth of firms. For example, Dupas and Robinson (2013) show that female shopkeepers in Kenya were much more likely to take up non-interest-bearing bank accounts that were subject to high withdrawal fees (and thus less attractive than standard interest-bearing accounts) than male business owners, and investment in those female-owned businesses was nearly double that of female business owners in the control group. Brune et al. (2011) document changes in the production methods of tobacco farmers in Malawi who were offered a “commitment” savings account that allowed the account holders to freeze their funds until a specified date (typically just prior to the planting season, thus preserving funds for purchases of farm inputs). Deposit and withdrawal activity spiked just prior to the planting season, land under cultivation increased by 9.8 percent, agricultural input use in that planting by 26.2 percent, crop output in the subsequent harvest by 22 percent, and household expenditures in the months immediately after harvest by 17.4 percent (all relative to the mean for the control group). Another study from Western Kenya shows how a commitment savings device enabled farmers to increase their use of fertilizer (Duflo, Kremer, and Robinson, 2011). Recent experimental evidence indicates that access to finance by the poor should be combined with complementary policies. Using data from a field experiment in Uganda and Malawi, Dupas et al. (2016) show that interventions merely focused on expanding access to finance to the poor, like one–time bank account opening subsidies, are unlikely to broaden financial access. Finally, there is also recent evidence that suggests that access to savings products influences interpersonal financial relationships. Dupas, Keats, and Robinson (2019) study the effect of accounts on financial linkages in rural Kenya, documenting that households that were randomly offered a bank account became less financially reliant on grown children and siblings living outside their village, and more supportive of neighbors and friends within their village. There is less evidence from experiments involving African credit products than for savings products. But some evidence from micro-credit experiments in Africa suggests that beneficial effects are harder to identify than for savings. For example, Tarozzi, Desai, and Johnson (2015) use data from an RCT conducted in rural Ethiopia to study the impact of access to microcredit on income from agriculture, animal husbandry, non-farm self-employment, labor supply, schooling, and indicators of women’s empowerment.

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1100   Banking Systems Around the World The study does not find clear evidence of widespread improvement in socioeconomic indicators in treated areas.16 Another key impediment to broader extension of credit in Africa is the lack of reliable methods for personal identification. Individuals who lack collateral and credit histories, which characterizes a large share of the African population, struggle to overcome informational asymmetries that make it almost impossible to access credit from formal sources. Establishing collateral and credit registries could help, but these can only function if people can be accurately identified. A field experiment among paprika farmers in Malawi tested whether biometric identification methods can improve the functioning of credit markets in a country where identity theft is common (Giné et al., 2013). Applicants for agricultural input loans from a state-owned bank were randomly assigned to a treatment group in which a fingerprint was collected from each member as part of the loan application, or to a control group in which no fingerprint was taken. Both treatment and control groups attended a training session on the importance of a credit history in ensuring future access to credit. For the sub-group of farmers identified as having high ex-ante default risk, fingerprinting led to a 40 percent increase in repayment rates.17 As in other parts of the developing world, microinsurance products could offer benefits in Africa, especially in agricultural areas. For example, rainfall insurance, which pays a set amount when rainfall falls below (or surpasses) a predetermined threshold, could be useful to African farmers.18 In Ghana, Karlan et al. (2014) find that rainfall insurance counters farmers’ risk aversion and improves decision-making, though effects were largest when insurance was combined with subsidized capital. Farmers that received both increased their spending on agricultural chemical inputs by 47 percent, expanded their land under cultivation by 22 percent, and were less likely to report that their households suffered from hunger. But in another experiment in Malawi, Giné and Yang (2009) find that take-up rates for an agricultural loan product were somewhat lower when the loan was coupled with an insurance policy (priced at an actuarially fair rate) that paid off in the event of poor rainfall. In part, the reluctance to purchase the insurance product may have stemmed from farmers’ belief that they only faced limited liability for their loans in the event of severe weather problems (and thus they already had a form of implicit insurance). In both experiments, the take-up rate for insurance products was puzzlingly low, suggesting a weak match between the insurance products and farmers’ needs and/or farmers not fully understanding how these products could benefit them. More research in the insurance area is clearly warranted. 16  See Roodman (2012) and Bauchet et al. (2011) for summaries of evidence from earlier randomized evaluations of microfinance. In their review of early microfinance studies in Africa, Van Rooyen, Stewart, and De Wet (2012) find that microcredit and microsavings interventions have mixed effects on household income and accumulation of assets. In part, this could stem from the uneven quality of the studies they review. 17 Moreover, a rough cost–benefit analysis suggests that the benefits from improved repayment greatly outweighed the cost of equipment and fingerprint collection. 18  Because farmers’ behavior does not influence payments, rainfall insurance eliminates moral hazard problems and could therefore be a viable product for financial services providers.

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Banking in Africa   1101

34.3.3  Technological Innovation Mobile money transfer (“m-transfer”) systems facilitate financial transactions via mobile phones, allowing users to deposit and withdraw cash from an account that is accessible by mobile handset. Users can store value in the account and transfer value between users via text messages, menu commands, and personal identification numbers (Aker and Mbiti, 2010). M-transfer arrangements therefore enable users to make payments and transfer funds at relatively low cost across much wider geographic areas than is possible using localized informal payment solutions. Aker et al. (2011) report that, from 2005 to 2010, m-transfer systems were established in 80 developing countries in Africa, Asia, and Latin America. The World Bank Global Findex dataset revealed that, by 2011, 67 and 60 percent of the  adult population in Kenya used mobile telephones to receive and send money, respectively. In 2017, 73 percent of Kenyans had a mobile money account, and 72 percent had used a mobile phone or the Internet to access an account within the past year. As reported in Table 34.4, mobile banking has also taken off as a means of accessing accounts and performing financial transactions in other African countries such as Gabon, Ghana, Namibia, Tanzania, Uganda, and Zimbabwe. In each of those countries at least 35 percent of the adult population were active users of mobile or Internet banking options in 2017 (Table 34.4, column 2). As noted in Allen et al. (2014a), the penetration of mobile telephones to receive and send money has been deeper in Sub-Saharan Africa than in the rest of the developing world. That trend has continued and the range of banking services used via mobile telephones has expanded. Mobile banking spread quickly in Kenya thanks, in part, to the fact that the operator of M-Pesa (M is for mobile, “pesa” is Swahili for “money”), Kenyan mobile network operator Safaricom, controlled two-thirds of the telecoms market in Kenya. M-Pesa, the mobile payments wallet launched in 2007 by Safaricom, had 15 million registered users by early 2012, a network of 35,000 cash-in/cash-out agents, and a transaction volume of $665 million per month (Mark, 2012; Rotman, Ferrand, and Rasmussen, 2012). At the same time, M-Pesa was rarely used for storing value for any significant period (most transactions were of the cash-in, immediate cash-out variety) and the vast majority of M-Pesa transactions were undertaken by relatively affluent Kenyans, though there were some indications of less intensive use by poorer population segments.19 Recent empirical evidence suggests that this innovation has paid off, not only in terms of financial inclusion, but also in terms of increased consumption. M-Pesa use has brought about a substantial decline in the costs of sending transfers and a substantial increase in their volume (especially remittances), a greater likelihood of being formally banked, and decreased use of informal savings mechanisms (Jack and Suri, 2011; Mbiti and Weil, 2016). 19  One potential explanation for limited time savings is that balances stored in an M-Pesa account accrued no interest (though that could change as M-Pesa teams up with banking partners to link M-Pesa accounts to mainstream bank accounts).

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1102   Banking Systems Around the World

Table 34.4  Mobile Phone use in Financial Transactions in Africa by Country, 2017

Country Benin Botswana Burkina Faso Cameroon Central African Republic Chad Congo Congo, Dem. Republic Cote d’Ivoire Ethiopia Gabon Ghana Guinea Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda Senegal Sierra Leone South Africa South Sudan Tanzania Togo Uganda Zambia Zimbabwe

Mobile money account (% age 15+)

Used mobile phone or Internet to access an account (% age 15+)

Used mobile phone or Internet to access a financial institution account (% age 15+)

18 24 33 15 n.a.

19 25 29 16 2

27 32 24 22 16

15 6 16

13 6 17

15 8 29

34 0 44 39 14 73 28 21 12 20 24 4 6 22 43 9 6 31 32 11 19 n.a. 39 21 51 28 49

33 0 44 35 11 72 26 21 11 20 24 3 15 22 46 8 8 29 29 10 21 1 37 21 47 26 46

21 1 32 28 15 57 27 16 17 27 22 8 16 30 42 16 18 13 27 23 25 6 31 16 27 35 38

Source: Global Findex (2017).

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Banking in Africa   1103 In partnership with the Commercial Bank of Africa (CBA), Safaricom also began offering a mobile product called M-Shwari to offer an array of financial services including interest-earning savings and credit. New loans can be applied for (and granted) almost instantaneously. Loan amounts start small and M-Shwari uses the prospect of larger future loans to incentivize loan repayment. Early indications are that take-up rates for M-Shwari loans are substantially higher than for microfinance loans. Like microcredit, M-Shwari loans appear to be used as a tool to smooth consumption and better manage the financial lives of clients, though there are also indications that some clients use them for educational expenses (Bharadwaj, Jack, and Suri, 2017). Jack and Suri (2014) have shown that, by reducing the costs of transfers within social networks in Kenya, households have been able to smooth consumption in the face of economic shocks. Specifically, they find that shocks reduce the consumption of nonM-Pesa users by 7 percent, while shocks have no significant effect on the consumption of households with an M-PESA user. Both the volume and diversity of remittance senders also increase after a shock and the average distance from senders to receivers of remittances increases substantially (Jack and Suri, 2014), suggesting that M-Pesa has enabled households to expand or make fuller use of their social networks at lower cost. Finally, Jack, Ray, and Suri (2013) find that the purposes of remittances differ between users and non-users of M-Pesa. Users are more likely to receive remittances via M-Pesa for credit or in response to an emergency, while the fraction of total M-Pesa transactions for regular support declines. The patterns suggest that M-Pesa enables households to more easily draw on their social networks for support in trying circumstances.20 M-Pesa also had positive effects on firms’ access to trade credit and thus growth, as shown by Beck et al. (2018). Specifically, by providing a safer payment method, enterprises increase their access to, and lower the cost of, supplier credit, with positive repercussions for sales growth. M-transfer systems have also facilitated spatial risk sharing within an economy as illustrated by Blumenstock, Eagle, and Fafchamps (2011) who show that the Lake Kivu earthquake in 2008 in Rwanda caused individuals living outside the affected area to transfer a large and significant volume of airtime to people living close to the earthquake’s epicenter. They also show that the transfers were consistent with reciprocal risk sharing rather than charity or altruistic motivations, suggesting that mobile payment services facilitate informal interpersonal insurance mechanisms, although it seems again that wealthier segments of the population benefited most. Another example comes from Niger, where an m-transfer system is providing a more cost-effective means of implementing a cash transfer program. While Bold, Porteous, and Rotman (2012) argue that electronic payment methods for social cash transfers work best when piggy-backing upon existing payments infrastructure, the experience in Niger suggests that electronic cash transfer via an m-system could also work where more traditional payments infrastructure is lacking.21 20  Suri and Jack (2016) provide analysis that M-Pesa increased per capita consumption levels and lifted an astounding 194,000 households, or 2 percent of Kenyan households, out of poverty. 21  In Niger, there is less than one bank per 100,000 residents.

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1104   Banking Systems Around the World An experiment comparing traditional cash transfers with transfers via an m-system called Zap was undertaken in ninety-six “food-deficit” villages in Niger, meaning they had produced less than half of their consumption needs during the 2009 harvest (Aker et al., 2011). Zap substantially reduced the cost of distributing and obtaining the cash transfers, and households used their transfers to purchase a more diverse set of goods, increased the diversity of their diets, depleted fewer assets, and grew a wider variety of crops (including marginal crops typically grown by women). The authors speculate that lower costs, in particular the time savings to recipients of electronic transfers, and greater privacy in receiving those transfers (reducing obligations to share money within social networks) is driving the changes in household outcomes associated with Zap usage. The experimental results for Africa thus far suggest that financial products that can reach the poor at low cost (both to providers and to the poor themselves), and that incorporate elements that enable borrowers/savers to protect funds to meet financial goals, hold promise for expanding financial inclusion.

34.4  Beyond Financial Inclusion: New Challenges While we have documented achievements in deepening and broadening African financial systems, challenges remain. In this section, we point to two specific areas where future research could support policy formulation.

34.4.1  The Long-Term Finance Challenge The first of these challenges refers to the short-term nature of finance across the region, as illustrated not only in the balance-sheet structures of banks, but also in the limited development of contractual savings institutions and financial markets. While financial inclusion has dominated the recent policy debate and research agenda, the need for long-term finance by households, enterprises, and government is enormous. The cost of addressing Africa’s physical infrastructure needs is estimated at $93 billion per year, roughly 15 percent of Africa’s gross domestic product (GDP) (Foster and BriceñoGarmendia,  2010). Demand for housing, especially in urban areas, continues to rise across the continent as Africa rapidly urbanizes. And firms continue to lack the necessary resources for long-term investment. While expanding access to formal financial services continues to be a challenge, there has been less progress in developing long-term finance on the continent, at least as indicated by the limited data that are available. Most of bank finance is short-term (both on the deposit and loan side) and non-bank finance, both intermediated and

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Banking in Africa   1105 market-based, is not developed. Given the overall development of financial systems, including shallow banking systems, this is not surprising; as shown by Beck et al. (2008) and De la Torre, Feyen, and Ize (2013), non-bank segments arise at a much later stage of economic development. Long-term finance is critical for long-term development of modern societies. Wellfunctioning intermediaries and capital markets that allow investors and savers easy access to their funding while enabling long-term investment are at the core of financial sector development. Beyond this general statement, one can also consider specific ­beneficiaries of long-term finance and projects that rely on long-term funding streams. Take the example of infrastructure: Given high resource needs and long-time horizons between the start of construction, its completion and the revenue phase, appropriate funding structures are needed. As private–public partnerships in infrastructure gain in importance, corresponding financing structures are needed that match maturity and risk structures of assets with funding. More generally, for governments, better access to long-term funding instruments can reduce the procyclicality of government consumption and its costs, as well as allow for more efficient investment decisions. In the case of households, access to long-term savings instruments allows consumption smoothing over the life cycle and provides savings and insurance products for retirement. On the funding side it allows large investment, prominently into housing, but also into human capital, independent of current income but as a function of future expected income streams. Finally, for firms, availability of long-term finance allows a better maturity matching of assets and liabilities and reduces the dependence of investment decisions on cash flow availability (Love, 2003) as well as greater investment in R&D activities, as shown by Aghion et al. (2010). Public capital markets, especially stock exchanges, have often been seen as quintessential elements of long-term finance provision in an economy. There were, therefore, intensive efforts by donors and local governments to establish such markets across ­Sub-Saharan Africa in the 1980s, though unfortunately those met with limited success. Albuquerque de Sousa et al. (2016) show that this can be mainly explained by the small size of financial systems across the region, limited banking sector development (another precondition for capital market development) and limited domestic savings. By 2018, half of the region’s countries had a stock market, but with very low liquidity.22 Development of bond markets is even more rudimentary, with few if any non-financial companies in most countries being able to issue bonds. While recent reforms in several countries in Sub-Saharan Africa have created private pension systems that are rapidly accumulating assets under management, the pension fund industry only intermediates a fraction of those assets into productive long-term investments (reverse maturity transformation). Mortgage finance is very limited (Badev 22  This is illustrated by the following statement by a market practitioner, “an entire year’s worth of trading in the frontier African stock markets is done before lunch on the New York Stock Exchange” (quoted in Christy, 1998). It should be noted that some countries are served by regional stock exchanges.

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1106   Banking Systems Around the World et al., 2013) as discussed above, which is again in line with global experience where it is mostly high-income countries where one sees a significant role for mortgage finance. Addressing the long-term finance gap first requires addressing a data gap. While data availability on access to finance has improved enormously across the globe and especially in Africa, driven partly by global data collection efforts, such as the World Bank’s Global Findex and the IMF’s Financial Access Survey, and partly by country-specific efforts, such as the FinScope and FinAccess surveys, very limited data is available on the depth, efficiency, and accessibility of long-term financial markets, though there are currently attempts at increasing the availability of indicators of long-term finance.

34.4.2  Cross-Border Banking and Regulatory Challenges As discussed above, foreign banking has had a long tradition in Africa, first in colonial times, and emerging again in the 1980s. What has been the effect of the increase in ­foreign bank ownership on the development, efficiency, stability, and outreach of African banking?23 Foreign bank entry seems to have several advantages that are ­specific to Africa: international banks can help foster governance; they can bring in much-needed technology and experience that should translate into increased efficiency in financial intermediation; and they can help exploit scale economies in small host countries. Nonetheless, especially in Africa, with its many small, risky, and opaque enterprises, the downsides of foreign bank entry also can become obvious, even more so in countries in which foreign banks have captured almost 100 percent of  the banking market. Specifically, the greater reliance of foreign banks on hard information about borrowers as opposed to soft information can have negative repercussions for riskier and more opaque borrowers if foreign banks crowd out domestic banks. The absence of a sound contractual and informational framework reduces the feasibility of small business lending further and thus the positive effect of foreign bank entry (Claessens and van Horen, 2014). Finally, the small size of many financial ­markets in Sub-Saharan Africa may make foreign banks reluctant to incur the fixed costs of introducing new products and technologies. While there is limited quantitative evidence across the region, country-specific analysis points to an overall positive effect of private bank ownership and foreign bank entry. Beck, Cull, and Jerome (2005) show for Nigeria that the privatization of stateowned banks led to performance improvements, although those authors also found that ­ etrimental to maintaining a substantial minority government ownership share was d privatized banks’ performance. In Uganda, Uganda Commercial Bank (UCB), the largest government-owned bank—and also the largest bank in the system—was successfully privatized in the second attempt to the South African Standard Bank. Although an agreement not to close any branches was in place for two years following the sale of 23  For a general overview of the literature on the effects of foreign bank entry, see Cull, Martínez Pería, and Verrier (2018).

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Banking in Africa   1107 UCB, Standard Bank kept all branches in place and even opened new ones. It introduced new products and even increased agricultural lending (Clarke, Cull, and Fuchs, 2009). In Tanzania, the National Bank of Commerce was privatized after splitting it into a commercial bank that assumed most of the original bank’s assets and liabilities, and the National Microfinance Bank that assumed most of the branch network and the mandate to foster access to financial services. The new National Bank of Commerce’s profitability and portfolio quality improved, although credit growth was initially slow. Although finding a buyer for the National Microfinance Bank proved difficult, profitability eventually improved, and lending grew, while the share of non-performing loans remained low (Cull and Spreng, 2011). Ultimately, Rabobank took management control of NMB. On a global level, World Bank (2018) shows that post-crisis entry by foreign bank subsidiaries was driven largely by banks headquartered in developing countries, and that they tended to enter neighboring countries, thus contributing to greater regionalism in international banking. The so-called South–South entry trend was especially pronounced in the African context. Understanding the channels through which cross-­ border banking can help deepen financial systems and foster real integration, and the channels through which cross-border banks can threaten financial stability, is critical. Claessens and van Horen (2014) confirm this conjecture on the aggregate level; any positive effect of cross-border banking on a host country’s financial development is lower the more distant the parent banks’ headquarters are. Beck (2015) shows that it is critical to distinguish between different groups of foreign banks. Specifically, he presents tentative evidence of a positive relationship between the share of foreign banks from the region, or other emerging markets, and firms’ access to finance, and of a negative relationship between the share of foreign banks from Europe or the US and entrepreneurial finance. While cross-border banking brings many benefits for host economies, regional financial integration also entails new potential sources of risks. New channels of contagion will develop— indeed, they are already developing—as national banking systems and financial markets become increasingly interwoven, allowing for the transmission of shocks across borders. These new potential risks underscore the importance—both for banks and their supervisors—of having in place adequate provisions for risk management and mitigation. They also call for a greater commitment and adherence to common “rules-of-the-game,” as embodied in internationally accepted standards and practices, to foster greater confidence in the financial sectors on the continent. Given the serious repercussions both for financial stability and financial deepening associated with bank fragility, particularly when it concerns larger pan-African banking groups, both the banks and the authorities have a mutual interest in upgrading bank oversight and cross-border supervisory cooperation. In this context, the optimal design of cross-­border cooperation between regulators and supervisors to minimize risks from cross-border banking, while maximizing its benefits, is important (Beck et al., 2014; Beck and Wagner, 2016). There is a broader issue on regulatory reform beyond cross-border cooperation. African countries have made enormous upgrades to their regulatory and supervisory

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1108   Banking Systems Around the World frameworks over the past decades. It is important to keep in mind, however, that recent regulatory reform processes were driven and dominated by the global financial crisis and the fragility concerns of economies with developed, if not sophisticated, financial markets. Africa’s fragility concerns are different and its reform capacity lower. Some of the suggested or implemented reforms seem irrelevant for almost all African countries (such as centralizing over-the-counter trades) or might have substantially worse effects in the context of shallow financial markets than in sophisticated markets increasingly dominated by high frequency trading (such as securities trading taxes). Kasakende, Bagyenda, and Brownbridge (2012) esteem the proposed Basel III reforms as not sufficient in the African context, and call for additional regulatory tools, including the possibility of imposing restrictions on banks’ asset exposures and regulations on loan concentration and foreign exchange exposure. More generally, in the context of regulatory reform, an approach of best fit would be more appropriate than a best practice approach that blindly adopts international standards. Prioritizing regulatory reforms according to risks and opportunity costs for financial deepening and inclusion is therefore critical.

34.5 Conclusion While Africa’s banking systems are shallow, they have made substantial progress over the past decade, a trend that can only be partially captured in aggregate data. Decades of regulatory upgrades have borne fruit in the form of more stable banking systems and substantially less fragility. Financial innovation has helped broaden the share of the population with access to basic formal financial services, and technology has helped African financial systems leapfrog traditional delivery channels. While observers often focus on the mobile money revolution, there are many forms of financial innovation, including new products, new providers and new delivery channels. However, for innovative approaches to financial service delivery to be adopted, a competitive environment and a flexible regulatory approach are needed. While we have documented achievements in deepening and broadening financial systems, long-term finance remains a challenge. The dominance of banks and their focus on short-term transactions has prevented the financial system from playing a stronger role in funding the infrastructure Africa needs so urgently, the housing needs that the ongoing urbanization and population growth require, and the long-term investment by firms. While cross-border banking has been a hallmark of African banking for many decades, the recent shift from North–South to South–South banking has created new opportunities but also new challenges. It has created new opportunities in terms of financial innovation and competition, but it has created new challenges in terms of the need for more cross-border regulatory and supervisory cooperation. This need for cross-border cooperation arises amid a more general discussion on regulatory standards in lowincome countries.

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Banking in Africa   1109 While many of the implemented and planned reforms follow either in the footsteps of other developing countries or have been identified by regulators and analysts as helpful, there is an important political economy aspect to financial sector reform. Politicians primarily maximize private interests, whether the interests of their voters or special interest groups. Short-term election cycles undermine the focus on long-term financial development objectives; objectives that maintain the dominant position of elites undermine the incentives of these elites to undertake reforms that can open up financial systems and, thus, dilute the dominant position of the elites. Path dependence in political structures and the underlying socioeconomic distribution of resources and power make the adoption of growth-enhancing policies, such as financial sector policies, difficult or impossible if the policies threaten to reduce the relative dominance of the incumbent elites. On the other hand, the financial sector is critical for an open, competitive, and contestable economy because it provides the necessary resources for new entrants and can thus support economic transformation. Better understanding the political constraints in financial sector reforms and identifying windows of opportunity are therefore important. Focusing on the creation of broader groups with a stake in further financial deepening can help develop a dynamic process of financial sector reforms. As discussed in this chapter, research into banking in Africa has expanded rapidly over the past years, using increasingly micro-level data, including credit registry data, thus following a trend from other regions of the world. Close cooperation between researchers, central banks but also commercial banks and MFIs can help produce critical insights into which practices and policies work to deepen, broaden, and lengthen banking in Africa. There is an exciting and policy-relevant research agenda going forward.

References Aghion, P., Angeletos, G.-M., Banerjee, A., and Manova, K. (2010). “Volatility and Growth: Credit Constraints and the Composition of Investment,” Journal of Monetary Economics, 57(3), 246–65. Aker, J.C. and Mbiti, I.M. (2010). “Mobile Phones and Economic Development in Africa,” Journal of Economic Perspectives, 24, 207–32. Aker, J.C., Boumnijel, R., McClelland, A., and Tierney, N. (2011). “Zap It To Me: The Short-Term Impacts of a Mobile Cash Transfer Program,” Center for Global Development Working Paper No. 268. Albuquerque de Sousa, J.A., Beck, T., van Bergeijk, P.A.G., and van Dijk, M.A. (2016). “Nascent Markets: Understanding the Success and Failure of New Stock Markets,” mimeo, available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2870392. Allen, F., Carletti, E., Cull, R., Qian, J., Senbet, L., and Valenzuela, P. (2014a). “The African Financial Development and Financial Inclusion Gaps,” Journal of African Economies, 23, 614–42. Allen, F., Carletti, E., Cull, R., Qian, J., Senbet, L., and Valenzuela, P. (2016). “Resolving the African Financial Development Gap: Cross-Country Comparisons and a Within-Country Study of Kenya,” in S.  Edwards, S.  Johnson, and D.  Weil (eds.), African Successes: Modernization and Development, Vol. III (Cambridge, MA; Chicago, IL: NBER; University of Chicago Press), 13–62.

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1110   Banking Systems Around the World Allen, F., Carletti, E., Cull, R., Qian, J., Senbet, L., and Valenzuela, P. (2018). “Improving Access to Banking: Evidence from Kenya,” CEA Working Paper No. 298. Allen, F., Carletti, E., Qian, J., and Valenzuela, P. (2014b). Does Finance Accelerate or Retard Growth? Theory and Evidence Towards a Better Global Economy: Policy Implications for Citizens Worldwide in the 21st Century (Oxford: Oxford University Press). Alliance for Financial Inclusion (2012). “Agent Banking in Latin America,” AFI Discussion Paper, March, Kuala Lumpur, Malaysia. Arcand, J.L., Berkes, E., and Panizza, U. (2015). “Too Much Finance?” Journal of Economic Growth, 20(2), 105–48. Aterido, R., Beck, T., and Iacovone, L. (2013). “Access to Finance in Sub-Saharan Africa: Is there a Gender Gap?” World Development, 47, 102–20. Badev, A., Beck, T., Vado, L., and Walley, S. (2013). “Housing Finance across Countries: New Data and Analysis,” The World Bank Policy Research Working Paper No. 6756. Bauchet, J., Marshall, C., Starita, L., Thomas, J., and Yalouris, A. (2011). “Latest Findings from Randomized Evaluations of Microfinance,” Access to Finance FORUM, CGAP and its Partners’ Reports, No. 2. Beck, T. (2015).“Cross-Border Banking and Financial Deepening: The African Experience”, Journal of African Economies, 24, i32–i45. Beck, T. and Wagner, W. (2016). “Supranational Supervision: How Much and for Whom?” International Journal of Central Banking, 12(2), 221–68. Beck, T., Cull, R., and Jerome, A. (2005). “Bank Privatization and Performance: Empirical Evidence from Nigeria,” Journal of Banking and Finance, 29(8–9), 2355–79. Beck, T., Demirgüç-Kunt, A., and Levine, R. (2000). “A New Database on Financial Development and Structure,” World Bank Economic Review, 14(3), 597–605. Beck, T., Demirgüç-Kunt, A., and Levine, R. (2010). “Financial Institutions and Markets Across Countries and Over Time: The Updated Financial Development and Structure Database,” World Bank Economic Review, 24(1), 77–92. Beck, T., Feyen, E.H.B., Ize, A., and Moizeszowicz, F. (2008). “Benchmarking Financial  Development,” Policy Research Working Paper No. 4638, World Bank, Washington, DC. Beck, T., Fuchs, M., Singer, D., and Witte, M. (2014). Making Cross-Border Banking Work for Africa (Bonn and Eschborn: GIZ). Beck, T., Munzele Maimbo, S., Faye, I., and Triki, T. (2011). Financing Africa: Through the Crisis and Beyond (Washington, DC: The World Bank). Beck, T., Pamuk, H., Ramrattan, R., and Uras, B.R. (2018). “Payment Instruments, Finance and Development,” Journal of Development Economics, 133(C), 162–86. Bharadwaj, P., Jack, W., and Suri, T. (2017). “The Impacts of Digital Credit: The Case of M-Shwari in Kenya,” MIT Sloan Working Paper. Blumenstock, J., Eagle, N., and Fafchamps, M. (2011.) “Risk and Reciprocity Over the Mobile Phone Network: Evidence from Rwanda,” CSAE Working Paper No. 2011-19. Bold, C., Porteous, D., and Rotman, S. (2012). “Social Cash Transfers and Financial Inclusion: Evidence from Four Countries,” CGAP Focus Note No. 77. Brown, M., Guinn, B., and Kirschenmann, K. (2016). “Microfinance Banks and Financial Inclusion,” Review of Finance, 20(3), 907–46. Bruhn, M. and Love, I. (2014). “The Real Impact of Improved Access to Finance: Evidence from Mexico,” Journal of Finance, 69(3), 1347–76. Brune, L., Giné, X., Goldberg, J., and Yang, D. (2011). “Commitments to Save: A Field Experiment in Rural Malawi,” World Bank Policy Research Working Paper No. 5748.

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Banking in Africa   1111 Burgess, R. and Pande, R. (2005). “Can Rural Banks Reduce Poverty? Evidence from the Indian Social Banking Experiment,” American Economic Review, 95(3), 780–95. Buri, S., Cull, R., Giné, X., Harten, S., and Heitmann, S. (2018). “Banking with Agents: Experimental Evidence from Senegal,” World Bank Policy Research Working Paper No. 8417. Christy, J.H. (1998). “Bright Spots on the Dark Continent,” Forbes, October 5, available at: http://www.forbes.com/global/1998/1005/0113068a.html. Claessens, S. and Laeven, L. (2004). “What Drives Bank Competition? Some International Evidence,” Journal of Money, Credit, and Banking, 36(3, Part 2), 563–83. Claessens, S. and van Horen, N. (2014). “Foreign Banks: Trends and Impact,” Journal of Money, Credit and Banking, 46(9), 295–326. Clarke, G.R.G., Cull, R., and Fuchs, M. (2009). “Bank Privatization in Sub-Saharan Africa: The Case of Uganda Commercial Bank,” World Development, 37(9), 1506–21. Cull, R. and Spreng, C.P. (2011). “Pursuing Efficiency While Maintaining Outreach: Bank Privatization in Tanzania,” Journal of Development Economics, 94(2), 254–61. Cull, R. and Trandafir, M. (2010). “Credit Market Segmentation in Uganda,” World Bank, mimeo. Cull, R., Giné, X., Harten, S., Heitmann, S., and Rusu, A. (2018). “Agent Banking in a Highly Under-Developed Financial Sector: Evidence from the Democratic Republic of Congo,” World Development, 107, 54–74. Cull, R., Martínez Pería, M.S., and Verrier, J. (2018). “Bank Ownership and Economic Development,” in T. Beck and R. Levine (eds.), Handbook of Finance and Development (Amsterdam: Elsevier). De la Torre, A., Feyen, E.H.B., and Ize, A. (2013). “Financial Development: Structure and Dynamics,” World Bank Economic Review, 27(3), 514–41. Demirgüç-Kunt, A. and Klapper, L. (2012). “Measuring Financial Inclusion: The Global Financial Inclusion Index,” World Bank Policy Research Working Paper No. 6025. Duflo, E., Kremer, M., and Robinson, J. (2011). “Nudging Farmers to Use Fertilizer: Theory and Experimental Evidence from Kenya,” American Economic Review, 101(6), 2350–90. Dupas, P. and Robinson, J. (2013). “Savings Constraints and Microenterprise Development: Evidence from a Field Experiment in Kenya,” American Economic Journal: Applied Economics, 5(1), 163–92. Dupas, P., Karlan, D., Robinson, J., and Ubfal, D. (2016). “Banking the Unbanked? Evidence from Three Countries,” NBER Working Paper No. 22463. Dupas, P., Keats, A., and Robinson, J. (2019). “The Effect of Savings Accounts on Interpersonal Financial Relationships: Evidence from a Field Experiment in Rural Kenya,” The Economic Journal, 129(617), 273–310. Flaming, M., McKay, C., and Pickens, M. (2011). “Agent Management Toolkit: Building a Viable Network of Branchless Banking Agents,” Consultative Group to Assist the Poor (CGAP) Technical Guide, CGAP, Washington, DC. Foster, V. and Briceño-Garmendia, C. (2010). Africa’s Infrastructure: A Time for Transformation (Washington, DC: World Bank). Giné, X. and Yang, D. (2009). “Insurance, Credit, and Technology Adoption: Field Experimental Evidence from Malawi with D.  Yang,” Journal of Development Economics, 89(1), 1–11. Giné, X., Goldberg, J., Sankaranarayanan, S., Sheerin, P., and Yang, D. (2013). “Use of Biometric Technology in Developing Countries,” in R.  Cull, A.  Demirgüç-Kunt, and J.  Morduch (eds.), Banking the World: Empirical Foundations of Financial Inclusion (Cambridge, MA: MIT Press), 429–46.

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1112   Banking Systems Around the World Honohan, P. and Beck, T. (2007). Making Finance Work for Africa (Washington, DC: World Bank). Jack, W. and Suri, T. (2011). “The Economics of M-Pesa,” MIT Sloan Working Paper. Jack, W. and Suri, T. (2014). “Risk Sharing and Transactions Costs: Evidence from Kenya’s Mobile Money Revolution,” American Economic Review, 104(1), 183–223. Jack, W., Ray, A., and Suri, T. (2013). “Money Management by Households and Firms in Kenya,” American Economic Review: Papers and Proceedings, 103(3), 1–8. Karlan, D., Osei, R., Osei-Akoto, I., and Udry, C. (2014). “Agricultural Decisions after Relaxing Credit and Risk Constraints,” Quarterly Journal of Economics, 129(2), 597–652. Kasakende, L., Bagyenda, J., and Brownbridge, M. (2012). “Basel III and the Global Reform of Financial Regulation: How Should Africa Respond? A Bank Regulator’s Perspective,” Bank of Uganda mimeo, Kampala, Uganda. Laeven, L. and Valencia, F. (2013). “Systemic Banking Crises Database: An Update,” IMF Economic Review, 61(2), 225–70. Levine, R. (2005). “Finance and Growth: Theory and Evidence,” in P. Aghion and S.N. Durlauf (eds.), Handbook of Economic Growth (Amsterdam: Elsevier), 865–934. Love, I. (2003). “Financial Development and Financing Constraints: International Evidence from the Structural Investment Model,” Review of Financial Studies, Society for Financial Studies, 16(3, July), 765–91. Lyman, T., Ivatury, G., and Staschen, S. (2006). “Use of Agents in Branchless for the Poor: Rewards, Risks, and Regulation,” Consultative Group to Assist the Poor (CGAP), Focus Note No. 38, CGAP, Washington, DC. Mark, O. (2012). “M-Pesa Drives Safaricom as Profit Declines to Sh12.8bn,” Business Daily May 10. Mbiti, I. and Weil, D. (2016). “Mobile Banking: The Impact of M-Pesa in Kenya,” in S. Edwards, S. Johnson, and D. Weil (eds.), African Successes: Modernization and Development, Vol. III (Cambridge, MA: NBER and Chicago, IL: University of Chicago Press). Roodman, D. (2012). “Latest Impact Research: Inching Toward Generalization,” CGAP Blog, April 11, available at: https://www.cgap.org/blog/latest-impact-research-inchingtowards-generalization. Rotman, S., Ferrand, D., and Rasmussen, S. (2012). “The Jipange KuSave Experiment in Kenya,” CGAP Brief, October, Washington, DC. Siedek, H. (2008). “Extending Financial Services with Banking Agents,” Consultative Group to Assist the Poor (CGAP) Brief, CGAP, Washington, DC. Suri, T. and Jack, W. (2016). “The Long-Run Poverty and Gender Impacts of Mobile Money,” Science, 354(6317), 1288–92. Tarozzi, A., Desai, J., and Johnson, K. (2015). “The Impacts of Microcredit: Evidence from Ethiopia,” American Economic Journal: Applied Economics, 7(1), 54–89. Van Rooyen, C., Stewart, R., and de Wet, T. (2012). “The Impact of Microfinance in SubSaharan Africa: A Systematic Review of the Evidence,” World Development, 40(11), 2249–62. World Bank (2018). Global Financial Development Report 2017/2018: Bankers Without Borders (Washington, DC: World Bank).

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chapter 35

Ba n k i ng i n Chi na Leora Klapper, María Soledad Martínez Pería, and Bilal Zia

35.1 Introduction Over the last decade, China has been among the fastest growing economies in the world and is poised to become the largest. Between 2007 and 2017, China grew at an average annual real rate of 8.8 percent.1 With a GDP of 11.9 trillion dollars as of the end of 2017,2 China is the second largest economy in the world after the US and is expected to surpass the US economy by 2030.3 In tandem with the performance of the economy, the Chinese financial sector has also experienced rapid growth during the last decade. The assets of the Chinese financial sector grew from 61.7 trillion RMB and 227 percent of GDP in 2007 to 339.5 trillion RMB and 455 percent of GDP in 2016 (Figure 35.1). Currently, China has the second largest financial sector and the largest banking sector in the world (Figure 35.2). By many accounts China is experiencing a credit boom. Over the last decade, total credit to the private non-financial sector (as a percentage of GDP) has been growing at an annual average rate of 9.3 percentage points, and has risen above its long-run trend (Figure 35.3). This so-called “credit gap” stood at close to 20 percent in 2017 and is well above the median level for advanced and emerging markets.4 The relevance of the Chinese economy and the size of its financial sector alone would merit an examination of how the financial sector operates. In addition, the fact that 1  IMF (2017a). 2  IMF (2017a) estimate. 3  The Center for Economic and Business Research predicts (in December 2017) that this will happen in 2030; see https://www.bloomberg.com/news/articles/2019-01-08/world-s-biggest-economies-seendominated-by-asian-ems-by-2030. 4  Credit-to-GDP gaps are computed by the Bank for International Settlements as an indicator of excessive credit build-up. The long-term trend is calculated using a one-sided HP filter with a smoothing parameter of 400,000 and at least ten years of data for each country. The methodology is discussed in detail in Drehmann et al. (2016).

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4,000

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Figure 35.1  Chinese Financial Sector Assets Over Time.

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Un ite d

St at e Ch s Un in a ite d Jap Ki an ng G dom Lu erm xe an m y bo ur g N Fra et n he ce rla n Ca ds na da Sw It itz aly er lan d Ko Au rea str a Ire lia lan d Br az il H Sp on ai gK n on g I n Si di ng a ap Be ore lg iu m Ru ss ia

–

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Figure 35.2  Financial Sector Size across Countries in US dollars as of 2016.

China has been experiencing a credit boom, and that these episodes often precede crises (see  Jordà, Schularick, and Taylor,  2011; Dell’Ariccia et al.,  2012; Gourinchas and Obstfeld, 2012; Schularick and Taylor, 2012; Gorton and Ordonez, 2016), makes the need to better understand how the Chinese financial sector functions even more important. This chapter also examines the benefits and risks of the growing use of technology to deliver financial services. The chapter proceeds as follows: section 35.2 describes the structure and performance of the financial sector, focusing largely on banks. Section 35.3 discusses developments in the shadow-banking sector. Section 35.4 focuses on China’s progress in expanding financial inclusion and tracks the recent expansion of FinTech, especially digital payment products. Finally, section 35.5 concludes the chapter.

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China

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Figure 35.3  Credit-to-GDP Gap for China and Other Countries.

35.2  The Structure and Performance of the Chinese Financial Sector The Chinese financial sector is broadly characterized by two types of financial service providers. “Traditional” financial service providers, including state-owned commercial banks, (e.g., the Postal Savings Bank of China, joint-stock commercial banks and city commercial banks, rural commercial banks, rural cooperative banks, and rural credit cooperatives) play a vital role in the Chinese financial sector. This network of traditional providers is supported by alternative or new providers such as village and township banks and microcredit companies, which were set up to improve the outreach of the financial system among unserved customers in rural areas. More recently, FinTech companies, including non-bank digital payment providers, peer-to-peer lending platforms, internet-based microlenders, internet banks, internet-based insurance, internet-based fund management, and internet equity-based crowdfunding have emerged and are competing with the traditional providers by adopting new innovative business models, delivery channels, and financial products, many of which have helped leverage the massive scale of online e-commerce. Banks dominate the Chinese financial sector. They accounted for 66 percent of financial sector assets and 298 percent of GDP at year-end 2016 (Figure 35.4). Four of the five largest banks, typically known as the Big Five, are the largest publicly listed banks in the world in terms of assets, and rank in the top ten in terms of Tier 1 capital, market valuation and profits.5 But the share of the Big Five in the system has declined by half, from 53 percent in 2005 to 26 percent in 2016, while that for other institutions such as the city bank and rural banks has grown from 6 percent to 14 percent between 2005 and 2016. China’s accession to the World Trade Organization (WTO) in 2001 brought pressure to reform the, until then largely government-owned and almost completely closed, 5  Forbes 2017 rankings and The Banker 2017 rankings.

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Percent of total financial sector assets

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Other financial institutions (not CBRC-regulated) CBRC-regulated non-banks Foreign banks Credit cooperatives, new-type rural financial institutions and postal savings bank City and rural commercial banks Joint-stock commercial banks Large commercial banks (“Big 5”) Policy banks

Figure 35.4  Evolution of Financial Institutions in Asset Share. Source: IMF (2017b).

Chinese banking sector in 2001. China first allowed foreign banks to provide foreign currency services for Chinese residents and enterprises, and in 2004 China opened its local currency market and allowed foreign banks to provide local currency services to Chinese enterprises in selected cities and areas. By April 2007, four foreign banks (Citigroup, HSBC, Standard Chartered, and Bank of East Asia) received approval from Chinese regulators and began accepting deposits in renminbi (RMB) from Chinese residents (Berger, Hasan, and Zhou, 2009). Chinese regulators have also, since then, relaxed the rules concerning foreign acquisition of domestic banks. Nevertheless, the participation of foreign banks in the system has remained very flat at roughly 1 to 2 percent. In an effort to improve the management and governance of Chinese banks, regulators have also allowed banks to list on stock exchanges. For example, between 2005 and 2006, Bank of Communications, Bank of China, China Construction Bank, and the Industrial and Commercial Bank of China had successful initial public offerings in the Hong Kong and Shanghai stock markets, raising over $40 billion in total. Several papers have investigated the consequences of banking sector reforms in China following WTO accession. Focusing on the period of 1994 to 2003, Berger, Hasan, and Zhou (2009) compare the efficiency levels of China’s state-owned banks, foreign banks, and private domestic banks to find that foreign minority ownership within the Chinese banking system is associated with a higher level of profit and cost efficiency and, more specifically, that foreign minority ownership of the state-owned and private domestic banks leads to an amelioration in their efficiency and performance. Yao and Jiang (2007) offer complementary findings in studying Chinese commercial banks between 1995 and 2005, noting that state-owned banks lag behind in terms of efficiency,

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Banking in China   1117 despite overall improvements in banking efficiency. Moreover, the authors find that foreign acquisition is associated with long-term efficiency improvements but find no such evidence for banks that undergo an IPO. Building a regionally disaggregated measure of foreign bank presence and relying on three separate measures of performance (netinterest margins, non-interest income, and costs), Xu (2011) explores the relationship between the foreign bank presence in China and the performance of its domestic banks and suggests that an increase in foreign bank presence in China is conducive to a more efficient and stronger-performing banking system. Jiang, Yao, and Feng (2013) find that partial privatization of the Chinese financial system has improved the performance of its banks. Moreover, banks with minority foreign ownership display a higher degree of efficiency while state-owned commercial banks are the least efficient. Joint-stock commercial banks are associated with a higher level of cost efficiency while city commercial banks are the most profit efficient. Despite the recent reforms, Chinese commercial banks have lower levels of capital and profits than banks in most large developing countries and, in the case of capital, some advanced economies. Chinese banks have less capital than many other countries if we consider both the total level of capital or tier 1 capital relative to risk-weighted assets. Similarly, looking at return on assets, it is clear that Chinese banks are less profitable than those operating in most other large developing countries (Table 35.1). At the same time, Chinese banks have lower non-performing loans (NPLs) than most other countries (Table 35.1). There are a number of important reasons why NPLs in China are deceptively lower than in most other countries. First, loan classification requirements

Table 35.1  Bank Performance Across Countries, 2016 Country China Brazil India Indonesia Mexico Russia South Africa Emerging Markets and Developing Economies (Median) France Germany Italy Hong Kong SAR United States United Kingdom Advanced Economies (Median)

Equity to Assets (%)

Tier 1 Capital (%)

Return on Assets (%)

NPL to Loans (%)

8.14 9.27 7.16 14.41 9.94 10.36 8.2 11.23

11.25 13.7 10.7 22.22 13.22 9.17 14.51 15.13

0.98 1.11 0.37 2.12 1.69 1.2 1.71 1.72

1.74 3.92 9.19 2.9 2.09 9.44 2.86 4.88

5.94 5.98 5.49 9.78 11.59 7.03 7.35

14.48 16.28 11.35 16.37 13.17 16.88 16.28

0.4 0.37 −0.53 1.14 0.37 0.25 0.79

3.64 1.69 17.12 0.85 1.32 0.94 3.21

Source: IMF Financial Soundness Indicators.

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1118   Banking Systems Around the World allow banks to categorize loans that are overdue by more than 90 days as “special mention” rather than “non-performing,” if they deem collateral to be of good quality. At the end of 2016, the share of special mention loans stood at 3.9 percent. Regulations also allow loans to small firms to be classified as non-performing only when they are more than 180 days past due. Second, some banks have moved credit assets into their investment book to circumvent credit quotas and restrictions, or to reduce capital charges and loss provisions. Third, many banks pre-emptively predisposed of loans6 that could become NPLs by means of write-offs, through sales to Asset Management Companies (AMCs) or by transferring assets off-balance sheet but retaining credit risk through financial engineering and implicit guarantees. In particular, because banks provide loans to AMCs to finance their operations or to the securitization vehicles they sell their loans to, loan sales to these entities reduce bad loans on bank balance sheets, but the banking sector as a whole maintains an exposure to bad loans.

35.3  Shadow Banking: Causes and Consequences of its Spectacular Growth 35.3.1  Drivers of Shadow Banking Another important characteristic of the Chinese financial sector during the last decade has been the significant growth of shadow banking (Figure 35.5). The People’s Bank of China (PBoC) Financial Stability Report (People’s Bank of China, 2013) defines shadow banking as “credit intermediation involving entities and activities outside the regular banking system, with the functions of liquidity and credit transformation, which could potentially cause systemic risks or regulatory arbitrage.”7 In tracking the evolution of shadow banking, the International Monetary Fund (IMF) considers the sum of entrusted loans, trust loans and bankers’ acceptances. Combined, these have increased from RMB 0.6 trillion in 2002 to RMB 26.9 trillion in 2017. As a percentage of GDP, these have increased from 5 percent to 33 percent over the 2002–17 period. The rise of shadow-bank credit was made possible by the emergence of shadow savings instruments as wealth management products (WMPs). Between 2007 and 2017, the volume of WMPs grew from RMB 0.5 trillion (i.e., 2 percent of GDP) to RMB 29.5 trillion (i.e., 36 percent of GDP) (Figure 35.6). WMPs are deposit-like instruments 6  Banks are incentivized by their management to keep NPLs low by having NPL targets they have to meet. 7  In 2018 the Financial Stability Board produced a shadow-banking monitoring report which defined shadow banking as “credit intermediation involving entities and activities (fully or partially) outside the regular banking system” (Financial Stability Board, 2018).

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Figure 35.6  Wealth Management Products, 2007–17.

that are typically issued by banks and are not explicitly covered by the deposit insurance scheme. These became popular as a way for banks to circumvent the low deposit rate ceiling, which was only abolished in October 2015 (Lardy, 2008; Wang et al., 2016). Moreover, because they are issued by banks and are structured similarly to deposits many retail investors perceive them as equally safe as deposits. This has enabled their growth and popularity. One of the primary motives for the rise of shadow banking has been governmental suppression of interest rates below market levels, particularly through its enforcement of a deposit rate ceiling (Dang, Wang, and Yao, 2014). This policy grew out of the need to sterilize the PBoC’s massive foreign currency market intervention, while also keeping

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1120   Banking Systems Around the World banks profitable (Lardy, 2008).8 Financial repression has also been a core feature of China’s reform-era growth, as household savings earning low interest rates were transferred through the banking system to supply subsidized credit to SOEs, capital-intensive industries, and real estate developers (Tsai, 2015). Given the limited opportunities in the bonds and stock markets, the main alternatives to traditional deposits for investors seeking higher yields became the real estate market and wealth management products. Investment in WMPs and trust funds are perceived as more attractive because they are more liquid and considered safer than real estate because banks are involved in structuring and distributing these products, even though they are typically not contractually liable when the underlying borrowers do not repay (Borst, 2014; Dang, Wang, and Yao, 2014; Yan, 2016). Aside from controls on interest rates, the rise of shadow banking has been motivated by other regulatory constraints on bank operations. On the asset side, the PBoC imposed loan quotas that prevent banks from lending as much as they would otherwise (Elliott and Qiao, 2015). Banks are also subject to constraining macro-prudential regulations including high deposit reserve requirements, a strict 75 percent limit on their loan-todeposit ratios, and costly capital requirements (Elliott et al., 2015). Furthermore, regulators discourage lending in certain industries that the government feels the need to shrink, which currently includes local government financing vehicles, coal mining, shipbuilding, and real estate development (Hsu and Li, 2015). Since 2005, China has relaxed its regulations banning banks from venturing into the operation of securities houses, trust companies, money market funds, and insurers, instead allowing mixed-operations of banks to increase their competitiveness (Dang, Wang, and Yao, 2014). In response to these changes and because the regulatory constraints have become sufficiently onerous in recent years, banks have chosen to create their own shadow-banking products and to cooperate with shadow financial institutions. In fact, about two-thirds of shadow-bank lending in China results from such regulatory arbitrage (Elliott et al., 2015). Cooperation between banks and shadow financial entities makes perfect sense, as their competitive edge complements each other’s weakness. Banks utilize their vast sales network to help shadow banks raise funds and screen potential borrowers whereas shadow banks can help banks to extend credit creation beyond what is allowed by existing regulations (Dang, Wang, and Yao, 2014). Hachem and Song (2015) focus on stricter liquidity regulation and asymmetric competition among large and small banks as the main driver for the rise in shadow banking. Specifically, they argue that stricter enforcement of the 75 percent cap on bank loan-todeposit ratios in conjunction with large increases in reserve requirements—the PBoC tripled the requirement from 7 percent in 2004 to 21 percent in 2011—was the regulatory 8  To sterilize the inflationary impact of its massive sales of domestic currency, the PBoC continually raised the required reserve ratio of banks and sold them large quantities of central bank bills. To compensate banks for putting so much cash into these low-yielding accounts, the PBoC established regulatory limits on deposit and lending rates, ensuring healthy profit margins.

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Banking in China   1121 trigger. These changes impacted Chinese banks asymmetrically. Whereas small and medium-sized banks found themselves constrained from lending since they were unable to attract more deposits in the presence of the deposit rate ceilings, the Big Four banks were much less impacted because their extensive branches across the country provided them with a distinct advantage in the deposit market (Acharya, Qian, and Yang, 2016). Consequently, smaller banks began issuing WMPs to move activities off-balance sheet and avoid regulation, prompting the Big Four banks to begin issuing their own WMPs to protect market share, despite not needing to move them off-balance sheet (Hachem and Song, 2015). Acharya, Qian, and Yang (2016) posit that, in addition to stricter regulatory enforcement, the Chinese government’s $586 billion stimulus package in response to the global financial crisis was a primary cause of the deposit competition among banks.9 In essence, because the Big Four banks were the main source of funding for the stimulus plan, they experienced a rapid increase in their loan balances, causing them to become much more aggressive in the deposit market to maintain their loan-to-deposit ratio (Acharya, Qian, and Yang, 2016). Regardless of why the Big Four began issuing their own WMPs, doing so forced the cap-constrained banks to become more aggressive and offer even higher returns in order to attract enough WMPs to skirt loan-to-deposit rules. These developments also coincided with inflationary spells during the financial crisis, particularly between February 2007 and October 2008 and from February 2010 to October 2011 when the real one-year interest rate on deposits in Chinese banks was negative, which encouraged savers to move deposits out of banks into higher-yielding investments to preserve the purchasing power of their savings (Elliott and Yan, 2013). Hsu and Li (2015) offer an alternative explanation for the growth of shadow banking, which also focuses on the Chinese government’s fiscal and monetary policy responses to the global financial crisis. Although infrastructure projects comprised 72 percent of the stimulus package, the central government financed only 30 percent of the package, whereas the rest of the investment spending was implemented and financed through local governments (Chen, He, and Liu, 2017). Furthermore, because local governments could not borrow funds themselves, the central government encouraged local governments to use local government financing vehicles (LGFVs) for off-balance financing, mainly from banks (Chen, He, and Liu, 2017). However, some LGFVs struggled with issues such as overstated equity capital, high leverage, and poor financial management, as well as extremely low rates of return (Tsai, 2015). Furthermore, by late 2010, the economy showed signs of overheating, with inflation rising above 5 percent. Consequently, the PBoC switched from an expansionary to a tightening monetary policy, cutting back the stimulus and ordering banks to reduce their lending (Wang et al., 2016). This, somewhat unexpected, credit tightening created a problem for banks, since they had lent significantly to long-term and credit-intensive infrastructure projects that risked both 9  Related to the impact of the fiscal stimulus, Cong et al. (2018) document that the stimulus-driven credit expansion disproportionately favored state-owned firms and lower productivity firms.

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1122   Banking Systems Around the World project failure and a substantial rise in bank NPLs absent continued credit infusion (Dang, Wang, and Yao, 2014). To resolve these financing problems and protect their balance sheets, banks further expanded their off-balance-sheet operations and became increasingly reliant on shadow banking for credit intermediation (Wang et al., 2016; Chen, He, and Liu, 2017).

35.3.2  Who Participates in Shadow Banking? In terms of borrowers, shadow banking has expanded from private entrepreneurs lacking access to traditional banks’ loans, and willing to pay higher rates for credit, to local governments facing unfunded mandates and incentives to demonstrate continued economic growth (Tsai, 2015). In terms of creditors, households, middle-class professionals and corporate savers seeking higher yields provided funds by buying WMPs sold and managed by banks, and financial products originated by trusts or brokers but sold through banks (Ehlers, Kong, and Zhu, 2018). The entities that provide credit intermediation in China’s shadow-banking system can be classified into three broad categories. The first and largest class involves banks as the direct intermediaries, where WMPs sold by banks or their subsidiaries are the main component. Despite their direct involvement, these activities are recorded off banks’ balance sheets and, hence, are not subject to official oversight (Dang, Wang, and Yao, 2014). The second class consists of non-bank financial institutions like trusts, brokers, insurance companies, and security firms. Although some of these entities can raise funds directly from investors, most need to cooperate with banks. Funding costs for these institutions are typically higher than WMPs structured by banks, forcing them to make riskier loans such as to property developers, mining companies and local government financing vehicles (Dang, Wang, and Yao, 2014). The last and most opaque segment of the shadowbanking system comprises interpersonal lending through credit associations, rural cooperative foundations, and pawnshops. Peer-to-peer business lending, including through online platforms, is also becoming increasingly common, whereby companies lend to other companies, sometimes arranged through banks (Tsai, 2015). Approximately two-thirds of the flow of business into shadow banking is “bank-centric” wherein a bank is at the core of the transaction, taking most of the risks and benefits, yet paying non-banks to participate in order to avoid regulatory constraints and costs. Banks dominate the shadow-banking system both because they have a pre-eminent position in terms of accessing individual and institutional savings, and because bank deposits receive implicit credit and liquidity guarantees from the state. Since the scope of the guarantee is vague, there is a deep-rooted perception that the government will bail out the entire bank in case of financial distress (Wang et al., 2016). The other third or so of the business results from a combination of competitive advantages for the non-banks, many due to looser regulation as well as a willingness and ability to reach out to smaller, private sector businesses (Elliott and Qiao, 2015).

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35.3.3  What are the Risks Involved? Is Shadow Banking Good or Bad? Shadow banks can help spur economic growth by making financial services cheaper and more widely available. Shadow-banking activities enabled long-term projects to obtain fresh funds to avoid default and have been especially important in China as a source of funding to the private sector, particularly small to medium-sized enterprises (SMEs) traditionally underserved by the formal banking sector (Tsai, 2017). Shadow banking also helps to correct the capital mispricing and misallocation problems caused by interest rate repression and bank credit restriction in China, resulting in more efficient channeling of financial resources and providing a testing ground for interest rate liberalization (Dang, Wang, and Yao, 2014; Wang et al., 2016). Furthermore, the injection of additional credit protects the broader economy from the dangers of a collapse in the supply of credit, while more diversified financial products and services may make the financial system more robust in the face of negative shocks (Schwarcz, 2016). Shadow banking can also provide banks and investors with a range of tools for liquidity, maturity, and credit risk management (Shen, 2016). However, realizing the benefits of shadow banking entails a tradeoff in terms of reduced financial stability. First, maturity mismatch, unspecified investment, and poor cash-flow management result in high levels of liquidity risk for shadow banking (Gang, 2012). The use of short-term funding sources, such as WMPs and trust loans, to finance illiquid long-term projects such as real estate development, infrastructure projects, and the manufacturing sector has made their operations particularly risky (Elliott, Kroeber, and Qiao,  2015). Furthermore, recognition of potential liquidity problems has made the practice of ever-greening more common (Yan, 2016). This may only serve to exacerbate the problem when investors lose confidence and reduce their buying or withdraw from WMPs. These dangers are compounded by the fact that shadow banks do not have access to central bank liquidity, are less regulated, and operate with smaller safety margins such as much lower capital and liquidity requirements (Elliott and Qiao, 2015). Second, since shadow banks operate outside the regular banking system, they have more flexibility to make profits through securitization. For example, WMPs are used to facilitate the securitization of bank loan assets, taking them off banks’ balance sheets and freeing up funds to make loans. Furthermore, trust companies use funds from WMPs to purchase repackaged bank loans as well as extend credit on banks’ behalf to third parties (Borst, 2014). The resulting build-up of high levels of leverage and the complex financial techniques employed by the shadow banks expose them to greater operational risks (Luo, 2016). Third, shadow banks often lend to riskier customers or in riskier forms such as foregoing collateral protection (Luo, 2016). For example, shadow banks make loans to industries that, after years of aggressive expansion, have overcapacity, raising the risk that indebted companies may fall into default or hit severe cash-flow problems (Yan, 2016). Another risk lies in possible defaults by local governments that have turned to LGFVs to

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1124   Banking Systems Around the World raise funds. Although LGFVs are supposed to repay debts from profits accruing from land transfers and post-development business operations, a recent survey by China’s National Audit Office revealed that less than half of the funds for debt repayment come from project profits, suggesting LGFVs are money-losing ventures (Lu et al.,  2015). Therefore, China’s local governments are facing a high risk of solvency when the local government debts begin to mature, or in the event of an economic slowdown and/or declining land prices (Elliott, Kroeber, and Qiao, 2015). Shadow banking also provides a large part of the credit that is extended to export-related SMEs (Lu et al., 2015), which might not be able to repay their loans in the face of rising costs, more intensive global competition, or tariffs. Last, there is a rising risk of moral hazard in the banking system. Promised returns from shadow banking are usually based on unrealistic future returns and expected high asset prices. Investors continue to fund shadow-banking activities largely because there is a widespread belief that either the bank at the beginning of the chain of transactions will rescue them in the event of a crisis or, failing that, the government will guarantee them against losing their investment (Borst, 2014). The strength of this implicit guarantee is reinforced by the fact that banks and trust companies effectively assure customers that their investments would be guaranteed in order to raise funds at low cost (Wang et al., 2016). Although banks may be reluctant to completely shed responsibility due to reputational risks and social stability concerns, the danger of implicit guarantees is that they may not be honored, either because of incapacity during a crisis or because the two sides to the transaction had different expectations of the implicit guarantee. Following the failure of one implicit guarantee, there is considerable risk of contagion as other lenders become uncertain about the safety of their investments and withdraw their funds. Lacking adequate regulation and oversight, these risks may accumulate unnoticed and unchecked, raising the systemic risk posed to China’s financial sector. In a crisis, the opacity of the shadow-banking system can lead to panic as perceptions of the real strength of a bank or other financial institution can plunge sharply as investors and depositors realize that they do not really know what the balance-sheet categories represent (Elliott and Qiao, 2015). Furthermore, since shadow banking falls outside the public safety nets of deposit guarantees and lender of last resort facilities that protect banks, the public mechanisms to halt such panic are ad hoc in nature and therefore have less credibility and a higher risk of failure, allowing instability at shadow-banking institutions to spread and accelerate faster than with banks (Lu et al., 2015). The potential for contagion into the traditional banking system is further compounded due to the complex interconnections between the banking system and shadow banks (Shen, 2016). This interconnectedness with formal banks, combined with its high leverage that increases the availability of credit, also means that shadow banks are likely to amplify pro-cyclicality, heightening the risks of causing asset price bubbles (Shen, 2016). Although credit expansion provided by shadow banks was needed after the global financial crisis, it also left the economic system heavily in debt. Such rising indebtedness, coupled with potential slower growth, may make businesses more susceptible to financial distress and failure, and also increase the level of NPLs for the banking sector.

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Banking in China   1125 At this time, even if a potential crisis were to emerge, the financial system and the central government appear well positioned to handle it. First, liquidity remains abundant due to high levels of deposits from households and businesses. In the event of a crisis, banks’ non-performing assets would increase, but their funding would not be imperiled (Elliott, Kroeber, and Qiao, 2015). Furthermore, since most shadow-bank products were purchased by wealthy individuals or cash-rich businesses, mass failure of shadow-banking products might result in losses but would not require a fire sale of other assets to meet their debt obligations. Such a crisis of confidence in shadow-banking products would also lead to individual investors flying to the safety of state-guaranteed bank deposits, further improving the liquidity position of the banks. Second, given relatively low central government debt to GDP ratios, even when adjusted for off-balance-sheet obligations such as the need to rescue some local and regional governments, the central government has the fiscal capacity to write off bad loans and recapitalize the banks (Elliott and Qiao, 2015). Third, tight capital control in China and the restrictions on foreign portfolio investments help to reduce the risk of capital flight. China’s external debt is only 7.5 percent of GNI and it has amassed $3.4 trillion in foreign exchange reserves. All this ensures that most of the debt is internal and hence can be met with sovereign credit creation (Elliott, Kroeber, and Qiao, 2015).

35.3.4  What is the Future of Shadow Banking in China? The shadow-banking sector in China has seen impressive growth since the financial crisis, however recent regulatory changes are expected to slow down if not reverse this trend. The stricter regulation has targeted the sale of WMPs as well as other segments of shadow banking such as peer-to-peer lending. Specifically, WMP customers are now required to acknowledge the risks involved on video before banks can accept their deposits. Similarly, the government has imposed caps on peer-to-peer lending and now asks lenders to partner with custodian banks before making loans. Combined with new asset management regulations issued in the second quarter of 2018, these requirements have resulted in an abrupt halt to the previously booming shadowbanking sector.10 The banking sector initially responded to the new rules by offering alternative deposit vehicles, such as structured deposits, but the government could extend its regulation further to meet its de-leveraging targets. The government initially imposed a fast-tracked deadline of mid-2019 for the asset management curbs to be adopted by banks but have since extended it until the end of 2020. Only time will tell what the true impact of the new regulations will be.

10 https://www.economist.com/finance-and-economics/2018/06/14/chinas-tighter-regulationof-shadow-banks-begins-to-bite.

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35.4  Financial Inclusion in China China has succeeded in providing a wide range of financial services to individuals, including poor adults, women, and rural residents. With support from regulatory bodies, the country has seen large-scale, policy-driven initiatives, including improvements in financial infrastructure, expansion of rural branch network and access points, digitalization of large-scale recurrent payments, a surge in new innovative business models with the advent of FinTech companies and other alternative financial providers, and the promotion of greater usage of accounts. Today, China’s rate of account ownership—a basic metric of financial inclusion—is not far behind many high-income economies like Japan, Singapore, and the Republic of Korea. In this section, we provide a quantitative analysis of China’s progress in expanding financial inclusion.11 The primary focus of the analysis is on understanding both ownership of financial accounts and their usage for savings, credit, and digital payments. We also discuss the importance of digital technology in widening access to financial services.

35.4.1  Access to and Use of Financial Services China has achieved considerable success in expanding account ownership over the years.12 In 2017, 80 percent of adults in China had an account at a bank or other financial institution, up from 64 percent in 2011 and unchanged from 2014. But the benefits of having an account come from using the account for savings, developing a credit history and borrowing, and making safer, more transparent, and often less expensive digital payments. About 15 percent of account owners in China have inactive accounts, defined as accounts with no deposit or withdrawal within the past year. This is in comparison to almost half of account owners in India with inactive accounts. Women account owners are as likely as men account owners to hold an inactive account in China, and inactive accounts are more prevalent in rural areas. So how are adults in China using their accounts? Formal savings rates are high, with over 40 percent of account owners reported having saved formally in the past year, while the share was about 20 percent in Brazil, India, and the Russian Federation. 11  We use data from Global Findex, which provides in-depth data on how individuals save, borrow, make payments, and manage risks. See Demirgüç-Kunt et al. (2018) for a description of the data and recent trends. The data is based on interviews with about 150,000 adults in 145 countries. The complete database is available at https://globalfindex.worldbank.org. 12  The 2017 Global Findex database defines account ownership as having an individual or jointly owned account either at a financial institution or through a mobile money provider. The first category includes accounts at a bank or another type of formal, regulated financial institution, such as a credit union, a cooperative, or a microfinance institution. The second consists of mobile phone-based services, not linked to a financial institution, that are used to pay bills or to send or receive money. These mobile money accounts allow people to store money and to send and receive electronic payments.

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Banking in China   1127 Formal borrowing is also high: 45 percent of adults report borrowing in some way in 2017, and about a half of borrowers (or 25 percent of adults) report borrowing formally, either from a bank or using a credit card. The remaining share borrows primarily from family and friends. There has been a surge in the percentage of adults using their account for digital payments.13 For instance, nearly 85 percent of Chinese adults made or received digital payments in 2017, up from 56 percent in 2014. In addition, 35 percent of Chinese adults received private wages in 2017, and between 60 and 70 percent of private sector wage earners reported receiving their wage payments into an account. In fact, nearly 20 percent of Chinese adults received private wages digitally in 2017 which is higher than the average share of adults receiving private wages digitally in India, Indonesia, or Thailand. China has also experienced a surge in online payments and the use of mobile phones or the internet to make purchases or pay bills. Mobile phones and the internet increasingly offer an alternative to debit and credit cards for making direct payments from an account. According to the Global Findex, 40 percent of adults make mobile payments primarily through third-party payment service providers such as Alipay and WeChat, using smartphone apps linked to an account at a bank or another type of financial institution. Despite these improvements in digitizing payments in the private sector, public sector payments are still mostly paid in cash. Only 13 percent of adults in China receive government payments digitally, significantly lower than the high-income country average of 34 percent. This despite evidence that electronic government payments are cheaper and faster and reduce leakages and corruption. Likewise, agriculture is a prominent industry in China, but only 3 percent of Chinese adults receive agricultural payments into an account. This is not surprising since millions of rural adults in China continue to remain outside the formal financial system. However, because a farmer might need to stretch payments between harvest and finance input costs, a formal financial relationship is especially important and can be established through electronic payments to a farmer’s bank account.

35.4.2  Understanding the Unbanked Despite China’s noteworthy progress toward universal financial access and greater usage, with 225 million adults without an account, China still has one of the largest unbanked populations in the world, followed by India, Pakistan, and Indonesia. Moreover, there are great disparities among adults in China. For example, women are 8 percentage points less 13  Digital payments include sending or receiving domestic remittances from or to an account; using a debit or credit card to make a payment; making a payment over a mobile phone or using the internet; paying a utility or school fee from an account; or receiving a wage, government transfer or agricultural sale payment directly into an account.

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1128   Banking Systems Around the World Insufficent funds ONLY BARRIER REPORTED Someone in the family has an account Too far away Financial services are too expensive Lack of necessary documentation Lack of trust in financial institutions Religious reasons 0%

10%

20%

30%

40%

50%

60%

Figure 35.7  Barriers to Account Ownership (% of Adults with No Account). Source: Global Findex Database 2017.Note: The height of the bar is the percentage of adults reporting “any” barrier.

likely than men to have an account. In addition, adults living in the poorest 40 percent of households are 20 percentage points less likely to have an account in comparison to adults living in the wealthiest 60 percent of households. The Findex data also finds that older adults are 8 percentage points less likely than younger ones to have an account. To help shed light on the reasons for the large percentage of unbanked in China, we analyze the question that was asked as part of the 2017 Global Findex survey of adults without an account at a financial institution, asking why they do not have an account. Respondents could offer more than one reason, and most gave two. The most commonly cited barrier was lack of enough money. Sixty percent of Chinese adults without an account at a financial institution said that they have too little money to use one, and roughly 1 in 4 adults cited this as their sole reason (Figure 35.7). More than 30 percent of unbanked Chinese adults said that they do not have an account because a family member already has one. Women were significantly more likely than men to cite this reason. A lack of the proper documentation required to open an account is another important reason, with 20 percent of unbanked adults reporting this as a barrier. The cost of opening and maintaining an account is reported by 13 percent of the unbanked.

35.4.3  Opportunities for Increasing Financial Inclusion Expanding usage of digital technology in China provides various opportunities to further improve financial inclusion. China’s large unbanked numbers present significant opportunities to introduce new financial services. About 185 million unbanked adults in the country have a mobile phone, out of which nearly 105 million are women. High mobile ownership among the unbanked can be leveraged to provide them with convenient access to financial services and further accelerate the country’s progress toward universal financial access.

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Banking in China   1129 Millions of unbanked adults in China still receive regular payments in cash—for wages, from the government, and for the sale of agricultural products. Digitizing such payments is a proven way to increase account ownership. About 30 million unbanked adults in China receive cash payments for the sale of agricultural goods, including 25 million who have a mobile phone. If those payments were moved into accounts, the share of unbanked adults could drop by up to 12 percent. Just as there are opportunities to increase account ownership, so are there opportunities to help people who already have an account make better use of it. For example, 165 million banked adults continue to save “semi-formally” in China, generally making regular payments to a community savings group or other savings scheme, including 75 million banked women. Digital technology could also offer an alternative to cash for utility payments. In China, about 60 percent of account owners who pay utility bills in cash have access to both a mobile phone and the internet.

35.5 Conclusions The Chinese financial sector has grown at an impressive pace over the last decade and its banking sector is now the largest in the world. The fast growth in credit has not translated yet into high NPLs, but there are questions about the adequacy of loan classification in China and close monitoring is required. Regulators’ efforts to slow down the growth of bank intermediation have been accompanied by rapid growth in shadow-banking products, as banks try to circumvent limits on their ability to grow. Both the growth in bank credit and the fact that shadowbanking products might move to banks’ balance sheets in the future is an important source of concern for anyone looking at the Chinese financial sector. In this sense, recent efforts by regulators to curtail shadow banking are a welcome development. China has made important advances in terms of expanding financial inclusion with account ownership, which is now close to the levels observed in high-income countries. Not only is account ownership high, but, importantly, so is account usage. China has also been at the forefront of digital payments promoted by the private sector. Yet, more needs to be done since there are still important disparities in financial inclusion between men and women, urban and rural citizens, and those at the top of income distribution and those at the bottom. Widespread access to mobile phones and the internet in China offer opportunities to leverage technology to more affordably and conveniently expand inclusive access to financial services, such as digitizing government and utility payments.

Acknowledgments We are very grateful to Lukas Autenried, Antoine Malfroy-Camine, Deeksha Kokas, and Jeanne Verrier for excellent research assistance. We appreciate help with finding and interpreting data on China from Ding Ding at the IMF. The views expressed in this chapter are those of the authors and not those of the IMF or the World Bank, or these institutions’ executive directors and management.

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References Acharya, V., Qian, J., and Yang, Z. (2016). “In the Shadow of Banks: Wealth Management Products and Issuing Banks’ Risk in China,” New York University, mimeo, available at: http://pages.stern.nyu.edu/~sternfin/vacharya/public_html/pdfs/ShadowBank-ChinaAQY20161111_all.pdf. Berger, A., Hasan, I., and Zhou, M. (2009). “Bank Ownership and Efficiency in China: What Will Happen in the World’s Largest Nation,” Journal of Banking and Finance, 33(1), 113–30. Borst, N. (2014). “Flying Blind,” International Economy, 28(1), 12–71. Chen, Z., He, Z., and Liu, C. (2017). “The Financing of Local Government in China: Stimulus Loan Wanes and Shadow Banking Waxes,” NBER Working Paper No. 23598. Cong, L.W., Gao, H., Ponticelli, J., and Yang, X. (2018). “Credit Allocation Under Economic Stimulus: Evidence from China,” The Review of Financial Studies, Chicago Booth Research Paper No. 17–19, available at: https://doi.org/10.1093/rfs/hhz008. Dang, T.V., Wang, H., and Yao, A. (2014). “Chinese Shadow Banking: Bank-Centric Misperceptions,” Hong Kong Institute for Monetary Research No. 22. Dell’Ariccia, G., Igan, D., Laeven, L., Tong, H., Bakker, B., and Vandenbussche, J. (2012). “Policies for Macrofinancial Stability: How to Deal with Credit Booms,” IMF Staff Discussion Note No. 12/06. Demirgüç-Kunt, A., Klapper, L., Singer, D., Ansar, S., and Hess, J. (2018). “Global Findex Database 2017: Measuring Financial Inclusion and the FinTech Revolution,” Washington, DC, World Bank. Drehmann, M., Pradhan, S., Wooldridge, P., and Szermere, R. (2016). “Recent Enhancement to the BIS Statistics,” BIS Quarterly Review, September. Ehlers, T., Kong, S., and Zhu, F. (2018). “Mapping Shadow Banking in China: Structure and Dynamics,” BIS Working Paper No. 701. Elliott, D. and Qiao, Y. (2015). “Reforming Shadow Banking in China,” Economic Studies, The Brookings Institution. Elliott, D. and Yan, K. (2013). “The Chinese Financial System: An Introduction and Overview,” John L. Thornton China Center at the Brookings Institution Monograph Series No. 6. Elliott, D., Kroeber, A., and Qiao, Y. (2015). “Shadow Banking in China: A Primer,” Economic Studies, The Brookings Institution. Financial Stability Board (2018). “Global Shadow Banking Monitoring Report 2017,” March. Gang, X. (2012). “Regulating Shadow Banking,” China Daily, available at: http://www.chinadaily. com.cn/opinion/2012-10/12/content_15812305.htm. Gorton, G. and Ordoñez, G. (2016). “Good Booms, Bad Booms,” National Bureau of Economic Research Working Paper No. 22008. Gourinchas, P.O. and Obstfeld, M. (2012). “Stories of the Twentieth Century for the TwentyFirst,” American Economic Journal: Macroeconomics, 4(1), 226–65. Hachem, K.C. and Song, Z.M. (2015). Liquidity Regulation and Unintended Financial Transformation in China (Cambridge, MA: National Bureau of Economic Research). Hsu, S. and Li, J. (2015). “The Rise and Fall of Shadow Banking in China,” Political Economy Research Institute Working Paper No. 375. IMF (2017a). World Economic Outlook Database, October. IMF (2017b). “People’s Republic of China: Financial System Stability Assessment,” IMF Country Report No. 17/358.

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Banking in China   1131 Jiang, C., Yao, S., and Feng, G. (2013). “Bank Ownership, Privatization and Performance: Evidence from a Transition Country,” Journal of Banking and Finance, 37(9), 3364–72. Jordà, Ò., Schularick, M., and Taylor, A. (2011). “Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons,” IMF Economic Review, 59(2), 340–78. Lardy, N.R. (2008). “Financial Repression in China,” Peterson Institute Policy Brief No. PB08-8. Lu, Y., Guo, H., Kao, E.H., and Fung, H. (2015). “Shadow Banking and Firm Financing in China,” International Review of Economics and Finance, 36, 40–53. Luo, D. (2016). The Development of the Chinese Financial System and Reform of Chinese Commercial Banks. London: Palgrave Macmillan. People’s Bank of China (2013). “Financial Stability Report,” People’s Bank of China, Beijing. Schularick, M. and Taylor, A.M. (2012). “Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870–2008,” American Economic Review, 102(2), 1029–61. Schwarcz, S.L. (2016). “Shadow Banking and Regulation in China and Other Developing Countries,” available at: https://scholarship.law.duke.edu/faculty_scholarship/3694/. Shen, W. (2016). Shadow Banking in China: Risk, Regulation and Policy (Cheltenham: Edward Elgar Publishing). Tsai, K.S. (2015). “The Political Economy of State Capitalism and Shadow Banking in China,” Issues and Studies, 51(1), 55–97. Tsai, K.S. (2017). “When Shadow Banking Can Be Productive: Financing Small and Medium Enterprises in China,” Journal of Development Studies, 53(12), 2005–28. Wang, H., Wang, H., Wang, L., and Zhou, H. (2016). “Shadow Banking: China’s Dual-Track Interest Rate Liberalization,” mimeo. Yan, L. (2016). “Shadow Banking in China: Implications for Financial Stability and Macroeconomics Rebalancing,” The Chinese Economy, 49(3), 148–60. Yao, S. and Jiang, C. (2007). “The Effects of Governance Changes on Bank Efficiency in China: A Stochastic Distance Function Approach,” University of Nottingham Research Paper 2007/19. Xu, Y. (2011). “Towards a More Accurate Measure of Foreign Bank Entry and its Impact on Domestic Banking Performance: The Case of China,” Journal of Banking and Finance, 35(4), 886–901.

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chapter 36

Ba n k i ng i n th e Tr a nsition Cou n tr ie s of Cen tr a l , Sou th er n, a n d Easter n Eu rope a n d th e For m er Sov iet U n ion Zuzana Fungáčová, Iftekhar Hasan, Laura Solanko, and Paul Wachtel

36.1 Introduction Banking in the transition countries of Central, Southern, and Eastern Europe and the former Soviet Union is particularly interesting because banks played a very limited role in planned Soviet-style economies. In the formerly planned economies banks provided transactions services and acted as agents of the government planning process. They rarely engaged in the primary function of a modern banking system which is to intermediate funds between savers and investors in order to allocate capital efficiently. A manufacturing firm in the Soviet Union had the same production process as its counterparts in the West, a bank did not. Thus, the creation of modern banking systems was arguably the most important element of the transition process. Thirty years after the collapse of the Soviet bloc, the transition in banking is largely completed with, in some instances, remarkable success. Many advanced transition countries can boast of robust, competitive, modern, market-oriented banking sectors that look no different from those in old EU countries. Nevertheless, there are also many aspects of the industry which reflect the legacy of the transition experience. For example, persistent structural problems in some countries have led to equally persistent bad loan problems. Foreign bank entry led to the rapid improvement in banking technology

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Banking in the Transition Countries   1133 which was often applied to mortgage and consumer lending. The development of a business lending culture, particularly to small to medium-sized enterprises (SMEs), lagged and businesses often complain of the difficulty in finding funding. Finally, a related issue that inhibits banking sector development is the slow pace of institutional reform in many countries and the continued government interference in the sector in some countries. Experiences across the region are by no means uniform, both with respect to the path since transition started and the current state of the industry. To start with, there are transition countries that are now EU members in Central Europe (Czech Republic, Hungary, Poland, Slovakia) and in South East Europe (Slovenia, Bulgaria, Croatia, Romania) and the Baltics (Estonia, Latvia, Lithuania). Their experiences are different from the other countries in SEE that are not EU members (Serbia, Bosnia and Herzegovina, North Macedonia, Montenegro, and Albania) as well as the Former Soviet Union (FSU) countries (principally Russia, Ukraine, and Kazakhstan). The most advanced transition countries in Central Europe joined the EU in 2004, several more followed later and a few have adopted the Euro. Thus, the gap in banking sector development across the region has widened over time. In this chapter we will try to provide an understanding of the banking sectors in the transition countries, three decades after the start of transition and one decade past the global financial crisis. First, we will reflect on the thirty-year history of transition banking from the creation of banking institutions out of the planning structures through the effect of the global financial crisis and the post-crisis experiences. Second, we will focus on the state of the banking industry at the present time and show similarities and differences between banking in this region and elsewhere. Third, we will examine one important consequence of transition banking reforms: the extent to which there is financial inclusion or access to finance.

36.2  History of Transition Banking Transition from a planned to a market economy started with the creation of banking institutions. This birthing process was hardly smooth; it took place amidst massive macroeconomic collapse and considerable economic uncertainty. Not surprisingly, these nascent banking sectors experienced crises ranging from serious bad loan problems to total collapse. Every transition country experienced at least one banking crisis and a variety of responses including recapitalizations, write-offs, privatization and, importantly, the entrance of foreign bank owners. The situations began to stabilize in the early years of the 21st century but the financial crisis and global recession tested the resilience of new institutions and regulatory structures and brought the issue of foreign ownership to the fore. The decade since the crisis has seen continued progress and gradual recovery, although instances of poor banking practice, performance, and regulation persist and there have been some instances of reform reversals as well. In this section, we provide a brief overview of the history of transition banking.1 1  For additional information see Bonin and Wachtel (2003 and 2005), Bonin (2004) and Barisitz (2007).

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1134   Banking Systems Around the World

36.2.1  The First Decades Banking sectors in the European transition economies were relatively underdeveloped compared with the real economies in these countries, due mainly to the legacies of the pre-transition centrally planned economy. In the planning framework, financial intermediation between savers and borrowers was internalized wholly within the state planning process and banks existed to carry out the plan. Credit evaluation and risk management played no role in lending decisions. The national monobank served only as an accounting clearing house for inter-enterprise transactions. Money was entirely passive in that it was used solely as a unit of account in enterprise transactions and as a medium of exchange between households and the state distribution sector. Household savings, oftentimes the result of forced accumulation of monetary balances due to the unavailability of desirable consumer goods, were collected by a state savings bank. There were some exceptions to this rigid planning structure. Pre-transition banking sectors typically included a foreign trade bank, which handled all foreign currency transactions to isolate these from the domestic financial system, and often contained separate specialty banks to oversee the financing of the agricultural and construction sectors. Yugoslavia was always an outlier in the Communist bloc; from the 1950s it had a two-tier banking system with a central bank and commercial banks that were owned collectively. Transition banking starts with the creation of a two-tier system with commercial activities carved out of the portfolio of the national monobank. The top tier consists of a traditional central bank that is charged with pursuing monetary policy, including exchange rate policy, and was usually given responsibility for supervising the nascent banking sector. The second tier consists of the newly created state-owned commercial banks (SOCBs), the state-owned specialty banks, which themselves morphed into SOCBs, any operating foreign and joint-venture banks, and all private domestic banks, including those that entered after the political transition. As a rule, lax entry requirements led to the creation of many new private banks, some of which were of dubious quality, or even fraudulent, and virtually all of which were severely undercapitalized. Hence, the seeds for a banking crisis were planted at the beginning of the transition, or even before, due partly to lax entry requirements which were put in place to foster competition with the dominant state-owned banks. Moreover, the nascent regulatory systems were overwhelmed by the mismatch between their capabilities, which were severely restricted by a lack of human capital, and their mandates, which were provided by quickly adopted standard financial rules and regulations, especially given the inherited loan portfolios of the SOCBs. Although each country’s financial restructuring program involved hiving off the commercial bank portfolio of the national bank to establish the two-tier system, different approaches were taken toward the creation of SOCBs, all of which were established initially as wholly state-owned joint-stock entities. In Hungary, the commercial portfolio was divided along sectoral lines, for example, industry, agriculture, and infrastructure plus the nascent small business sector, to create three SOCBs. In Poland, the commercial

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Banking in the Transition Countries   1135 portfolio was divided along regional lines to create nine SOCBs from regional offices of the national monobank. In an extreme example, designed to foster competition, each of the 145 branch offices of the Bulgarian national bank was granted a universal banking license and a portion of the loan portfolio. A two-tier banking system was established in the Soviet Union in 1987 with the separation of all commercial bank functions from the national monobank and the creation of sectoral banks by enterprises or former branch ministries. With the dissolution of the Soviet Union, branches of the national bank became independent entities and then regrouped into larger banks. There were large numbers of new entrants in newly independent Russia; by 1995, about 2,300 banks were licensed and operating in Russia. Most of the newly created banks were small and poorly capitalized. Many of them were merely internal or house banks owned by industrial enterprises although a few of the de novo domestic private banks were among the largest banks in Russia. However, the sector was dominated by two large SOCBs, the former state foreign trade bank and the former state savings bank. However, the Russian private banking sector contracted due to numerous bank failures during the 1998 Ruble crisis and Russian banking is still dominated by two large state banks (Steinherr, 2006). In the first decade of transition, policies toward foreign bank participation, both in establishing subsidiaries and in purchasing equity stakes in SOCBs, differed considerably across the region. In some countries, policies that invited entry, for example, providing tax holidays, encouraged greenfield foreign operations. Foreign participation in the banking sector was viewed initially by most governments as a vehicle for importing banking expertise and training to augment the scarce domestic human capital in the sector. However, there was also a strong nationalistic resistance to allowing foreign control of the monetary system and a concern that foreign banks would facilitate capital flight. Some governments followed an infant industry approach according to which domestic banks are nurtured to become strong enough to fend off foreign competition when it arrives. Many countries limited foreign participation with restrictive licensing, such as restricting foreign banks to minority stakes in SOCBs or to participating in the resuscitation of ailing domestic banks. Foreign bank ownership started in Hungary which had allowed foreign participation even before transition (Citibank Budapest Ltd. began operations as a foreign-majorityowned, joint-venture bank in 1986). By 1995, about one-third of Hungarian bank assets were owned by foreign financial institutions (Hasan and Marton, 2003). In the former Czechoslovakia some state-owned banks were included in the voucher privatization program, thus restricting foreign ownership. In Poland, the nine SOCBs were slated early on for privatization with minority foreign ownership through a program supported by the US Treasury. In most other countries foreign ownership was miniscule in the mid-1990s though this soon changed. Developing efficient banking sectors required the completion of three interrelated tasks, namely, the resolution of non-performing loans (NPLs), the privatization of the SOCBs, and the establishment of effective regulatory institutions. Privatization and

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1136   Banking Systems Around the World the establishment of market-oriented banking laws legislation and institutions did not lead automatically to good banking practices. To the contrary, the SOCBs and the newly created banks often did not behave like proper commercial banks due to distorted incentives. First, the SOCBs continued to maintain banking relationships with their large clients, that is, state-owned enterprises (SOEs). Such lending was either politically mandated or simply the result of long-standing relationships between clients having little experience in choosing viable projects and banks unable to evaluate the risk of loans. Second, in many countries, de novo banks were created without adequate regulatory oversight. As a result, some de novo banks were used to channel loans improperly to their owners, many of which were enterprises, so that these banks acted as pocket (or house) banks for their owners. Entry requirements for de novo domestic banks were initially very lenient because policy was based on the mistaken notion that competition would be enhanced by easy entry. The proliferation of new, often undercapitalized, banks placed an added burden on an underdeveloped regulatory structure. Not surprisingly, bad loans were a serious problem for all transition economies, due partly to the inherited legacies but also to continuing lending practices. Most governments responded to failing banks with efforts to save them from closure by recapitalization and the removal of bad loans from their balance sheets. However, this did not change bank behavior; lending to SOEs and related entities continued. In the absence of independent market-oriented banking institutions, the flow of new bad loans continued to accumulate. To some extent the bad loan problem was unavoidable because transition recessions and the dissolution of trading relationships within the Soviet bloc generated severe real sector shocks that were mirrored on the balance sheets of the banks. The surprising aspect of banking in the transition countries is not the depth of the crises after the end of communism but the speed with which financial restructuring took place subsequently. The rapid changes in the 1990s and early 2000s can in part be attributed to two related phenomena. First, the desire of European transition countries to qualify for EU membership was a strong force for reform, not only in the eight original transition accession countries but also in the later joiners and in countries still hoping to join. Second, the prospect of EU membership (and ultimately the adoption of the Euro) made these underserved banking markets attractive to European banks once macroeconomic stability was attained and a reasonably effective regulatory structure was in place. Of course, most FSU countries did not enjoy the benefits of such external anchors and banking reform lagged across the FSU. After 1995 the EBRD index of banking reform increased gradually in all the countries (denoting an improvement); although there were a few reversals, several countries attained a score of 4.0.2 Hence, banking sectors in many transition countries prior to the crisis reached, or were rapidly approaching, levels found in developed market economies 2  The scale runs from 1 to 4+ where 1 represents little or no change from a rigid centrally planned economy and 4+ represents the standards of an industrialized market economy.

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Banking in the Transition Countries   1137 with one major difference, namely, an extremely high foreign bank presence. Banking in most countries was highly concentrated, although the concentration ratios were similar to the ones found in countries of a similar size and having similar financial deepening. The relatively high concentration ratios have not prevented competition from developing in many of these banking sectors. The spreads between lending and deposit rates were often in excess of 10 percent in the early transition years, due to instability and high inflation. Spreads declined considerably over the first two decades of transition which may be attributable as much to improvements in the macroeconomic environment as to increased banking competition. Foreign ownership started to spread as governments realized that privatization to foreign buyers is not only a source of revenue but also a means of improving bank performance (Haselmann, 2006). After a decade and a half of transition, privatization of SOCBs with extensive foreign ownership was largely completed in CEE (Central and Eastern Europe), SEE (Southeastern Europe) and the Baltics. Exceptions were Russia and the Ukraine as well as Slovenia, which continued to protect its domestic banks, and countries that continued to be politically unstable. Although foreign-owned banks may prefer large, internationally active firms, both foreign and domestic banks are important sources of credit; moreover, there are significant industry externalities from the presence of foreign banks. Bonin, Hasan, and Wachtel (2005a and 2005b) show that privatization by itself was not sufficient to improve bank performance; rather, joint ownership with foreign strategic investors was the crucial determinant in behavioral change. Foreign ownership restrictions were relaxed in the former Soviet Union in the early 2000s. Kazakhstan, with large capital inflows related to the energy industry, began to allow foreign banks to operate in 2005. Russia relaxed its limits on the overall size of the foreign banking sectors but it retained minima for the number of Russian employees and board members in foreign banks. The largest banks in Russia are still the state-owned giants and there are no apparent plans to privatize these banks, which act as agents for state intervention in the economy. In addition, unstable supervisory environments and weak legal protection have deterred foreign interest in such investments in many FSU countries. Many of the small private banks in Russia were involved in speculative activity and many were insolvent when the Russian government defaulted on its debt in 1998. At the time, weak bankruptcy laws and poor regulation made it difficult to close institutions so that the managers or owners were able to strip banks of any remaining good assets. The Russian banking sector improved after the 1998 crisis with bank closures and consolidations, a growing foreign bank presence, and increasing financial intermediation. However, the Russian banking sector continues to be crisis prone. In all countries, successful restructuring and privatization in the financial sector depends on the establishment of an effective institutional and legislative framework for regulation as well as bankruptcy laws and appropriate accounting standards. In general, arms-length relationships between banks and regulators, and banks and the state, generally are required in order to change the behavior of economic agents who are accustomed to operating in a non-market environment. Moreover, training of bank supervisors and other types of professional human capital development are needed to promote effective

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1138   Banking Systems Around the World implementation of the legislation. Although the basic legal framework for modern banking was established early in the transition, additional related elements that are crucial for its effective functioning took more time to develop. These include modern banking legislation, the adoption of international accounting standards, revised bankruptcy and collateral laws, and effective supervision. A modern banking sector does need a functioning credit information system, which includes a credit registry and ratings agencies, and a reliably functioning court system to mediate contract disputes. Household credit, especially mortgage lending, depends on well-defined property rights over collateral and an effective legislative infrastructure to facilitate the collection of collateral in case of default. Hence, the dramatic growth in household credit reflects significant improvements in supportive institutions. The explosion of retail credit contributed to housing price booms, excessive debt, and instability in some transition countries. The expansion of household lending may be related to the dominance of foreign-owned banks. Using the first EBRD Banking Environment and Performance Survey, Haselmann and Wachtel (2007 and 2010) show that banks in many transition economies shifted their asset portfolios out of government securities toward mortgages and consumer credit. Once the legal environment is in place, lending to households is a commodity. Still, ratios of household credit to GDP are not large by developed country standards. However, the ratio of household credit to the financial wealth of the consumer sector is often high and borrowing in foreign currencies persists, making consumers vulnerable to economic shocks. Lending to enterprises requires developing client relationships and having the ability to evaluate unique situations, both of which require expertise that is generally lacking in foreign banks, although acquired banks may bring such local knowledge. Beck and Brown (2015) find that foreign banks “cherry pick” the best customers and leave opaque borrowers to the domestic banks. The EBRD/World Bank surveys of enterprises in transition countries indicate that many firms, perhaps with the exception of international firms, were financially constrained in the sense that they are unable to obtain bank lending. Based on these surveys, the EBRD concludes that “despite some regional variation, bank loans still play a limited role in enterprise financing” (EBRD, 2006, p. 47).

36.2.2  Challenges from the Global Financial Crisis The resilience of the newly emerging mature and stable banking systems throughout the region was put to the test by the global financial crisis starting in 2008. First, foreign ownership of banks, which had been an important source of managerial and technological improvements in the industry, also served to link the financial systems of the home and host countries. As a result, transition country banks were exposed to the global financial crisis shock coming from the US and Europe. Second, many transition countries experienced retail credit booms in the years leading up to the crisis and, so the banks were exposed to credit risks when the recession spread from the more developed countries to

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Banking in the Transition Countries   1139 the transition region. The impact of the global financial crisis on the region tested the regulatory and supervisory capabilities of these, still relatively new, financial systems. Although the impact of the financial crisis on the region was severe, systemic problems were rare and many banks in the region generally outperformed their counterparts in more developed countries. When foreign banks began to enter the transition countries, the flow of resources and capital was entirely from the developed countries to the transition country hosts. The expertise, technology and know-how, as well as the equity investments in banks and the spillover effect on the domestic industry, were important elements in the transformation of transition country banking. In the credit boom of the 2000s, capital also flowed through these banks to the transition countries. No one discussed the possibility of resources flows in the opposite direction, as weakened international banks transmitted the crisis shock to the transition economies. The crisis showed that foreign ownership could amplify the effect of a home country shock on host transition countries (De Haas, 2014; De Haas et al., 2015). It was feared that foreign-owned banks, particularly if they relied on funding and liquidity from their parent, would transmit the crisis shock to the region. Poor conditions in the home country might lead the parent banks to reduce funding or even try to withdraw capital. If parent banks attempted to limit their losses by reducing foreign exposures, they could trigger systemic crises in banking systems dominated by foreign ownership. Concern about the transmission of the crisis shock led to a joint action plan, the Vienna Initiative (VI), which was adopted in January 2009. Both the International Financial Institutions (IFIs) such as the EBRD, the IMF, and the European Investment Bank and private institutions (i.e., the principal parent banks in the region) participated in the VI. The banks agreed to maintain their exposures to the transition countries and recapitalize banks as necessary, while the IFIs offered support of 33 billion Euros to maintain stability in the region. An expanded plan, VI 2.0, was adopted in 2012 in response to the European sovereign debt crisis. According to De Hass et al. (2015), the contraction in credit by foreign bank subsidiaries in thirty transition countries occurred earlier and was deeper than that of domestic banks during the crisis years of 2008 and 2009. However, these authors find that banks that participated in the Vienna Initiative were less likely to contract credit in the region than banks that did not participate. Popov and Udell (2012) show that transition country firms’ access to credit during the crisis was affected by the balance-sheet conditions of foreign parent banks. Similarly, Bonin and Louie (2017) find that bank lending by foreign banks in transition countries was adversely affected by the financial crisis and the Eurozone crisis. Thus, there is evidence of the international transmission of the crisis shock to the transition countries. Nonetheless, Bonin and Louie (2017) find that the large multinational banks retained their commitment to their second home market, as did Epstein (2014) who argues that it was the business models of the banks themselves, rather than the intervention of the IFIs, that influenced the behavior of the large foreign owners. Hungary was among the first emerging market countries to suffer the fallout of the global crisis. It was vulnerable because of a large fiscal deficit, its reliance on external

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1140   Banking Systems Around the World financing and the extent of domestic, particularly household, borrowing in foreign currency. In October 2008, the IMF, the World Bank and the EU joined forces to provide a $25 billion support program. Importantly, the program included provisions for preemptive additions to bank capital and guarantees for the interbank market in order to forestall a systemic banking crisis. As the Hungarian currency depreciated, the country faced a serious problem since the vast majority of loans in its large mortgage market were denominated in Swiss francs. The regulatory authorities and the government intervened, with limited success, by allowing the repayment of these mortgages at a preferential exchange rate. Although the recession in Hungary deepened and credit contracted, Hungary was able to avoid a systemic banking crisis like that which occurred at the start of transition. Croatia also faced a rapid expansion of household borrowing in the years prior to the crisis, which was fueled by improvements in the banking sector’s capabilities, the entrance of foreign banks, and low external borrowing costs. Croatia imposed prudential constraints on lending activity through a series of innovative central bank actions starting with a ceiling on credit growth above 16 percent in 2003. In 2006, the central bank increased the risk weights on foreign currency loans to domestic customers with the express purpose of discouraging such loans. Although the variety of programs and the frequent changes in their application introduced some uncertainty into the banking environment, Croatia was able to maintain the stability of its banking sector throughout the crisis period. The Russian banking system encountered serious liquidity problems before the crisis. A lack of trust paralyzed the interbank market for a short period in 2004, though this did not have much effect since deposits were concentrated in the large state-owned banks. From 1998 to 2008, the ratio of bank credit to GDP in Russia doubled. Thus, problems were more serious in 2008 when oil prices fell and the Ruble depreciated, while many institutions borrowed abroad in foreign currencies. This time the closure of the Russian interbank market threatened a significant systemic crisis. Deposits were switched into foreign currency and total deposits declined. Non-performing loans increased, loans outstanding fell, and there were some bank closures. The central bank eased its refinancing terms and extended deposit insurance coverage and the government offered support to those enterprises in trouble. The decline in oil prices and Western sanctions put enormous pressure on the Russian economy and the banking system after 2014. The central bank established a bailout fund and three large private banks were closed in late 2017. Similarly, the economic and political crisis in the Ukraine led to the failure of the country’s largest bank in 2016.

36.2.3  Going Forward Credit grew rapidly in the transition countries prior to the global financial crisis which was followed by the European sovereign debt and banking crises, which had spillover effects in many emerging-market banking systems. Thus, the economic contractions in

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Banking in the Transition Countries   1141 many transition countries were severe and the effects were long-lasting. Non-performing loans increased rapidly, which choked off the ability of banks to lend and of firms to borrow. The volume of loans decreased and loan-to-deposit ratios fell sharply. The overhang of NPLs in a stagnating economy perpetuates itself and the crisis impact on the transition country banking systems lasted for almost a decade. Although institutional structures were largely in place, regulators, bankers and firms lacked the experience needed to quickly resolve bad loan problems (see EBRD, 2015, p. 25). First, standards for loan classification were often unclear and regulators were reluctant to enforce requirements for additional provisioning. Second, banks and firms lacked the expertise needed to restructure viable but overleveraged firms. Over time, banks and regulators began to deal with NPL problems with loan sales and improved recovery efforts. In some instances, governments intervened and created asset management companies to take bad loans off bank balance sheets and introduced programs to convert foreign currency loans. The creation of the first pillars of the European banking union (the single supervision mechanism and single resolution mechanism) in 2014 changed the nature of bank regulation by introducing uniform standards and information sharing that eliminates much of the cross-border uncertainty regarding supervision. A European deposit insurance scheme, the third pillar of the banking union, is not yet in place. However, the banking union is only compulsory for Eurozone members, other EU countries can choose to participate. Only Bulgaria and Romania have done so, partially in response to EU pressure and also in an effort to import European regulatory and anti-corruption standards and supervisory expertise. The other non-Euro Area transition economies have taken a wait-and-see attitude. Policymakers feel that the crisis-related problems were not of their making, particularly the spillover effects on interest rates and cross border flows from the Greek crisis. As a result, there is an increasing reluctance to accept any supranational approach to banking regulation and a desire to retain discretion over supervisory decisions. Moreover, there is a resurgence of what might be called “banking nationalism” in the region, resulting in renewed suspicion of foreign banks (Mérő and Piroska, 2016). Bank consolidations and acquisitions in some countries have led to the purchase of foreign subsidiary banks by domestic institutions and efforts to favor national champions. For example, Polish officials talk about the “domestication” of banking, and banks with majority foreign ownership now control only about one-half of bank assets, down from close to three-quarters just prior to the crisis. In Hungary, there have been some bank nationalizations and efforts to favor domestic banks, like OTP which is itself the owner of banks throughout the region. Although banks in the transition countries have made rapid strides in improving performance and services since the early 1990s, the banking sectors in the transition economies still do not possess the financial depth of their EU counterparts, nor are banking services as well developed. State monobanking structures have been replaced by privately owned, market-oriented, well-capitalized banking institutions that are largely independent from the government and from state-owned clients. The legal environment has improved with respect to bankruptcy laws, collateral laws, and confidence in

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1142   Banking Systems Around the World the application of the law. Furthermore, banking regulatory and supervisory capabilities have developed considerably. However, there are dangerous signals of increased political interference in transition banking sectors which represents a significant step backwards. In the next section, we take a closer look at the question: is the transition in banking over?

36.3  Banking Industry Today: Is Transition Over? The discussion above could easily lead to the conclusion that transition in banking is over in the sense that the socialist banking systems are long gone now and firms and households are free to choose a banking institution that best serves their needs. All European transition economies now have a viable banking industry largely based on competing universal and retail banks. After thirty years of transition, banking sectors in most European transition countries largely resemble those in the old EU countries. Some important differences remain, however. This section will briefly describe the current state of banking in the transition countries and where possible make comparisons to the Euro Area.

36.3.1  Intermediation and the Role of Banks Until the global financial crisis, banking sectors grew faster than GDP almost everywhere in Europe, and the transition economies were no exception. The size of the banking sector in relation to GDP peaked in 2009. The deleveraging that followed the 2009 crisis has been notable in the CEE countries but much less pronounced in most of the SEE and FSU areas. The size of the banking sector (measured by banks’ claims on the domestic non-financial sector from the World Bank, 2017–18) is on average about 60 percent in relation to GDP in the transition countries, significantly lower than in the Euro Area. Total assets of monetary financial institutions in the Euro Area is above 300 percent of GDP, while only slightly above 100 percent in Estonia and Latvia and even less in other transition economies (ECB, 2017). The ratio of deposit money bank assets to GDP for each region is shown in Table 36.1. The financial sectors in CEE, SEE, and FSU are more bank-based than their counterparts in the Euro Area. The role of non-bank financial entities like pension funds, insurance corporations, investment funds, and other financial institutions is very limited in these economies. For example, in terms of total assets, the share of the non-bank financial sector in Estonia and Slovakia is less than one-third of the total financial sector. In the Euro Area the corresponding figure is above a half. Even in Poland, a country with by far the most advanced capital markets, non-bank financial institutions’ assets equal only roughly 30 percent of GDP (Impavido, Rudolph, and Ruggerone, 2013). Non-bank

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Banking in the Transition Countries   1143 financial sectors are particularly underdeveloped in FSU economies, where domestic institutional investors are all but nonexistent.

36.3.2  Banking Sector Structure Due to the socialist legacy, banking sectors in our focus countries largely comprise commercial banks only. Traditional cooperative or savings banks have not emerged in the transition region, and in most cases the privatization of former state banks has resulted in a small number of relatively large banks. Only a limited number of de novo banks survived the turbulent 1990s and the tightening regulation and crisis in the 2000s. Russia is a clear outlier with a large number of banks, due to both its economic size and to relatively lax supervision up until 2013. Consolidations and acquisitions have reduced the number of banks everywhere in Europe since the crisis and the transition countries are no exception. Both the number of banks and the number of bank employees have decreased. In per capita terms, the banks in CEE tend to have few employees. In Romania, Lithuania, and Slovakia one bank employee serves over 280 inhabitants, whereas the EU average is still below 180 (EBF, 2017). The current ownership structure of banking sectors in the region differs greatly from the Euro Area average where domestic ownership prevails. As discussed previously, banking sector assets are predominantly foreign-owned in most SEE, CEE, and Baltic countries. The share of foreign banks’ assets exceeded 90 percent in Croatia, the Czech Republic, Estonia, Lithuania, and Romania in 2016 (ECB, 2017b). Also the share of foreign banks in the total number of banks is significantly higher than in any other emerging markets’ group (Arakelyan, 2018). Most foreign banks operating in CEE and SEE are headquartered in other EU member countries. This has greatly helped to streamline banking regulation in the region toward European practices. As most countries of the former Soviet Union never experimented with large-scale bank privatizations to outside owners, the role of foreign banks remains limited in the FSU. Further, especially in Russia, not all foreign-owned banks are genuinely foreign. A large number of Russian banks are registered in various EU countries but are controlled by Russian nationals. State ownership is rare in most of SEE and CEE, and in the Baltics, whereas state-controlled banks continue to dominate banking sectors in many FSU countries. As an example, the asset share of state-controlled banks in Russia ­currently exceeds 60 percent. All customer deposits account for about a half of banking sector liabilities in the Euro Area, but the role of deposit funding continues to be larger in the transition region (see Table 36.2). Deposits cover two-thirds of banking sector liabilities in most of the region. Moreover, the share of household and non-financial corporations in total deposits tends to be high, underlying the fact that many banks in the region focus on traditional financial intermediation. With the exception of a few large countries, banking systems in the EU tend to be fairly concentrated, with the share of the five largest banks in total banking sector assets

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1144   Banking Systems Around the World

Table 36.1  Deposit Money Banks’ Assets to GDP (%), Average for the Region

New EU members SEE (non-EU members) FSU3 Euro Area

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

53 34

59 43

68 53

82 58

77 58

73 58

71 59

69 59

66 59

64 60

34 90

43 96

50 105

61 114

54 112

50 111

51 110

53 108

55 101

55 103

Note: The new EU member states are Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, and Slovenia; non-EU members in the SEE are Albania, Bosnia and Herzegovina, Kosovo, North Macedonia, Montenegro, and Serbia; the FSU3 group includes Kazakhstan, Russia, and Ukraine. Finally, the composition of the Euro Area changes over the years shown. Source: World Bank Global Financial Database. https://www.worldbank.org/en/publication/gfdr/data/ global-financial-development-database. Data compiled by the authors.

just below half in 2016 (ECB, 2017a). The concentration ratio is even higher in the transition economies. The five largest banks control well above 60 percent in most countries, reaching the highest values of almost 90 percent in Estonia and Latvia. Only Russia (until recently) and Ukraine (lately) have had somewhat lower concentration ratios. High concentration ratios reflect both the small absolute size of most of these economies and the dominant role of a small number of very large foreign-owned institutions. High concentration does not necessarily mean low competition. Measuring bank competition clearly is challenging, but banking literature frequently uses the Lerner index, which relies on individual banks’ data. The index estimates a bank’s market power by assessing the bank’s ability to price above its marginal costs. Using this measure, banking competition in the transition economies does not seem to differ from the EU average. Lerner index values (World Bank, 2018) are higher in the Baltics and Russia, but in most countries Lerner index values are very similar to the Euro Area average.

36.3.3  Bank Lending Dollarization and later euroization have been a defining feature of banking in transition. In the early days of transition, dollarization emerged due to a low degree of trust in the domestic monetary authorities and in the new national currencies. As the economies developed, levels of dollarization reduced markedly. In the FSU dollarization has, however, remained at around 30 percent of corporate loans and deposits. In the case of Russia, this is largely due to the fact that major exporters continue to have an obligation to repatriate their typically US dollar-denominated export revenue. In most CEE and SEE economies, however, euroization in lending to both households and enterprises has re-emerged due to the large market shares of foreign banks, expectations of joining the

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Banking in the Transition Countries   1145 Euro Area or unilateral euroization, and in some SEE economies historical mistrust in domestic currencies. The role of foreign-owned banks in fostering euroization has indeed been remarkable. Almost a half of loans extended by Austrian bank subsidiaries in CEE and SEE have been in foreign currency, predominantly in euros (IMF, 2013). Also, the expansion of direct cross-border lending to the non-bank private sector has increased exposure to foreign exchange risks in a number of CEE and SEE countries. Banks in transition countries tend to engage more in lending, with loans-to-assets ratios well above the Euro Area average in most of the countries shown in Table 36.2. Moreover, these banks tend to have a larger share of their assets in loans to domestic non-financial corporations and households. This results from the limited international activities of these banks, but also reflects the very small role of local interbank markets and non-bank financial institutions in these economies. Many banks in the CEE and SEE regions focus on retail lending, which shows up in relatively high shares of household lending in bank portfolios. The shift away from government securities in banks’ portfolios also reflects the relatively moderate levels of public debt in most transition countries. The rise in consumer credit and mortgages is a much more recent phenomenon in the FSU and in Russia, for example, loans to households constitute only about 30 percent of the total aggregate lending and only 16 percent of total assets. The focus on traditional banking activities and the relatively low exposure to global financial markets did help in alleviating the effects of the global financial crisis and the European debt crisis on banking sectors of the transition region. For the last decade, bank profitability has, on average, been higher than in the Euro Area. One factor behind better profitability has arguably been banks’ high net interest margins, especially in SEE and in a number of FSU countries. Relatively higher net interest margins in, for example, Ukraine, Montenegro, and North Macedonia reflect both weaker banking competition and a shakier macroeconomic situation in these countries. Interest margins tend to be clearly smaller in the countries that have joined the Euro Area, Estonia, Latvia, and Lithuania in particular.

36.4  Financial Inclusion in Transition Countries Although modern banking sectors have been established in the region, it remains to be shown whether they are functioning as such. In this section we examine the extent of financial inclusion, that is, the access to and use of financial services. Financial inclusion has been shown to contribute to poverty reduction and economic growth as well as improve financial stability. Increasing financial inclusion has become one of the key policy objectives around the world.

Estonia Lithuania Latvia Slovakia Slovenia Euro Area Bulgaria Croatia Czech Hungary Poland Romania EU-28 Albania BiH Macedonia North Serbia Republic Montenegro loans-to- 88% assets deposits- 63% to-assets loan-to- 140% deposits

80%

65%

67%

70%

57%

67%

72%

66%

53%

68%

66%

56%

42%

61%

64%

60%

62%

75%

48%

73%

74%

55%

71%

68%

61%

63%

67%

68%

52%

81%

75%

74%

76%

76%

106%

136%

93%

95%

103%

95%

106%

109%

84%

102%

97%

107%

51%

82%

87%

79%

81%

Source: European Banking Federation: Facts and Figures 2017. Data compiled by the authors.

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Table 36.2  Balance-Sheet Structure of Banking Sectors at end 2016

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Banking in the Transition Countries   1147 The analysis draws on the Global Findex Database, which consists of nationally representative surveys of more than 150,000 adults in over 140 economies around the world, that were carried out in 2011, 2014, and 2017. We use data from the surveys conducted in 29 formerly planned economies.3

36.4.1  Measuring Financial Inclusion—Account Ownership The Global Findex data provides three main measures of financial inclusion; account ownership and usage, saving behavior, and borrowing. Using all three measures, there has been significant improvement in financial inclusion in recent years. Despite this positive trend, the transition economies still lag behind the Euro Area. The measures also reveal considerable heterogeneity across the region. The main measure of financial inclusion is the ownership of an account4 by an individual. An account is an entry into a financial institution which is used to save or borrow money and also to make transactions. Overall, 69 percent of adults worldwide now have an account, up from 51 percent in 2011 (Demirgüç-Kunt et al., 20185). Unlike some developing economies where accounts by mobile money providers are common, in our sample countries individuals have accounts at formal financial institutions. In the new EU member countries, the proportion of people with accounts was high in 2011 at 77 percent and reached 83 percent in 2017; in the Baltic countries it approached the Euro Area average of 95 percent. On the other hand, in the main FSU countries (Russia, Ukraine, Kazakhstan) about two-thirds of the adults reported having an account. Other FSU countries are less developed in general and also less developed in terms of financial inclusion. While the proportion of adults with an account has more than doubled in these countries between 2011 and 2017, it only reaches 47 percent. The variation within the other FSU countries group is, however, wide ranging, from 29 percent in Azerbaijan to 81 percent in Belarus. As elsewhere, also in transition countries, the extent of financial inclusion measured by account ownership increases with the level of economic and financial development. In addition to the relation between income per capita and financial inclusion mentioned above, there are several individual characteristics that influence account ownership. The gender gap in account ownership, which is observed in developing countries, is not found in transition countries. Generally, financial inclusion is higher in high-income countries and the gap in account ownership between poor and rich is lower in these countries. Within our sample, this gap between poor and rich is higher than the world’s average in all FSU as well as SEE countries including Bulgaria and Romania. In most of these countries the gap has increased over time which might point to a more unequal 3 Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyz Republic, Moldova, Tajikistan, Turkmenistan, Uzbekistan, Estonia, Latvia, Lithuania, Czech Republic, Hungary, Poland, Slovak Republic, Bulgaria, Croatia, Romania, Slovenia, Russian Federation, Albania, Bosnia and Herzegovina, Kosovo, North Macedonia FYR, Montenegro, Serbia, Ukraine. 4  Global Findex database 2017 defines “account ownership” as having an individual or jointly owned account either at a financial institution or through a mobile money provider. 5  All other figures concerning global data reported here come from this source.

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1148   Banking Systems Around the World distribution of income. Surprisingly, despite high levels of financial inclusion, there are large differences (a double-digit gap) in account ownership between poorer and richer adults in some more developed CEE countries (Czech Republic, Hungary, and Slovakia). Financial inclusion increases with age but the gap between the young and the old is about the same in transition countries as in the Euro Area. Exceptions are Slovenia, Ukraine, and Tajikistan, where account ownership is higher for young adults than for the older generation.

36.4.2  Account Usage Having an account is crucial for financial inclusion but even more important is if and how this account is used. In the 2017 survey, about 60 percent of adults in the transition countries report making or receiving at least one payment in the past year, a 19 percentage points increase from the survey three years earlier. In the Euro Area, however, 92 percent of respondents report at least one payment and thus the intensity of financial inclusion in transition countries is still significantly lower. Governments contribute to higher account usage when they use accounts for wages, pensions, and transfers. Overall, in the transition economies 41 percent of individuals report receiving at least one payment from government in the past year, the highest shares being in Latvia (70 percent) and Ukraine (60 percent). About 40 percent of those receiving the payments have opened their accounts in order to be able to receive government payments. The data indicates that in less developed transition economies (Azerbaijan, Georgia, Moldova, Uzbekistan, and Tajikistan) this accounts for the significant increase in financial inclusion. The usage of credit and debit cards in the transition countries is still well below the Euro Area figures. About 35 percent of adults report using a debit or credit card to make a purchase in the past year, in both the 2014 and 2017 surveys, while the average in the Euro Area exceeds 70 percent. Mobile phones and the Internet provide a convenient way to access accounts. In 2017, about 29 percent of account owners in transition economies reported that they have used a mobile phone or the Internet to access their account in the past year while about half of the respondents did so in the Euro Area. Usage varies widely, ranging from about two-thirds responding positively in Estonia and the Czech Republic to below 10 percent in Turkmenistan, Azerbaijan, and Albania.

36.4.3  Financial Inclusion—Saving and Borrowing The use of financial institutions for saving and borrowing is an alternative measure of financial inclusion. The most general question asked about savings is if individuals have saved or set aside money in the past year. In the transition countries 42 percent answered positively in 2017, only a minor increase in comparison to 2014. FSU countries and SEE countries report about one-third of individuals who save and this has not changed over

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Banking in the Transition Countries   1149 time. On average, this indicator in the transition countries is below figures for the whole world and not increasing recently. The level of financial inclusion can also be assessed by credit usage; there is greater inclusion if more individuals borrow. Just about half of the adults in the Euro Area report having borrowed any money in the past year. This proportion is lower in the transition countries (about 40 percent). Formal borrowing from financial institutions is more significant in the more developed transition countries that are now EU members, with the exception of Romania and Bulgaria. In the former FSU countries and SEE countries borrowing from family and friends is the most important source of borrowing. In Russia there is about equal reliance on each of these sources. People borrow for different purposes. Very common is getting a loan to acquire housing. In the Euro Area about one-fourth of adults report outstanding housing loans while globally the average stands at about 10 percent. In the transition countries the average is 13 percent but the variation is very high, from almost no housing loans in Uzbekistan to more than the Euro Area average in Estonia and the Slovak Republic. Interestingly, borrowing money to start, operate, or expand a business has basically the same importance as taking out a housing loan. On the other hand, borrowing for health or medical purposes is common only in former FSU and SEE countries where, on average, over 10 percent of adults report this as the purpose for borrowing.

36.4.4  Barriers to Financial Exclusion Despite the recent increase in financial inclusion in the transition countries, there are still many adults without an account. Global Findex surveys indicate that the most common barrier to having an account is insufficient funds (as reported by about half of the people without an account). The second reason, reported by almost one-third of the respondents in the transition countries, is that another family member already has an account. High costs constitute the third most cited reason for not having an account in the transition countries. High costs were cited by about half of the people without an account in Hungary and Slovakia. Distrust in the financial system as a barrier does not score high globally but it is important in our sample countries, most of which experienced financial crises, bank closures, and hyperinflation in the 1990s. Distrust is cited as a reason for not having an account by almost one-fourth of the respondents with higher proportions in Ukraine (50 percent) and Hungary (49 percent). This is consistent with the World Values Survey measure of trust in banking where the average response for Ukraine was 2.1 on the scale from 1 to 4, while the world average is about 2.5. Ironically, trust in banks is high in Uzbekistan (the average response, 3.24, is the highest among the 52 countries surveyed) where corruption is rampant and financial inclusion is really low. Increasing financial inclusion has become an important policy target in recent years. Several transition countries have taken steps in this direction (e.g., the strategy for increasing financial inclusion adopted in Russia in 2018 or national financial sector strategies addressing financial inclusion in Azerbaijan 2016, Belarus 2017–20, Latvia 2017–19 and Ukraine 2017–20).

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1150   Banking Systems Around the World Although our analysis based on Global Findex data indicates a positive development in the level of financial inclusion, even the most developed of transition countries usually do not reach the levels observed in the Euro Area. Account ownership indicates improvement in financial inclusion. There have been improvements in account usage, often driven by government policy, but the gap with the euro zone countries remains large and greater than the differences in account ownership. Account usage for savings and borrowing is significantly lower than in the euro zone and often lower than global averages.

36.5 Conclusion Although banks in the transition countries have made rapid strides in improving performance and services since the early 1990s, the banking sectors in the transition economies still do not possess the financial depth of their EU counterparts, even if banking services are often well developed in these countries. With a few exceptions, the transition in banking is complete. State mono-banking structures have been replaced by privately owned, market-oriented, well-capitalized banking institutions that are independent of the government and state-owned clients. The legal environment has improved with respect to bankruptcy laws, collateral laws, and confidence in the application of the law. Furthermore, banking regulatory and supervisory capabilities have developed considerably. Thus, any evaluation of the structure of banking in transition countries must be positive. Except for some of the FSU countries, banks in the transition economies have become part of the competitive global financial industry.

References Arakelyan, M. (2018). “Foreign Banks and Credit Dynamics in CESEE,” IMF Working Paper No. 18/3. Barisitz, S. (2007). Banking in Central and Eastern Europe 1980–2006: A Comprehensive Analysis of Banking Sector Transformation in the Former Soviet Union, Czechoslovakia, East Germany, Yugoslavia, Belarus, Bulgaria, Croatia, the Czech Republic, Hungary, Kazakhstan, Poland, Romania, the Russian Federation, Serbia and Montenegro, Slovakia, Ukraine, and Uzbekistan (New York and London: Routledge). Beck, T. and Brown, M. (2015). “Foreign Bank Ownership and Household Credit,” Journal of Financial Intermediation, 24, 466–86. Bonin, J. P. (2004). “Banking in the Balkans: The Structure of Banking Sectors in Southeast Europe,” Economic Systems, 28, 141–53. Bonin, J. P. and Louie, D. (2017). “Did Foreign Banks Stay Committed to Emerging Europe During Recent Financial Crises?” Journal of Comparative Economics, 45(4), 793–808. Bonin, J. P. and Wachtel, P. (2003). “Financial Sector Development in Transition Economies: Lessons from the First Decade,” Financial Markets, Institutions, and Instruments, 12, 1–66. Bonin, J. P. and Wachtel, P. (2005). “Dealing with Financial Fragility in Transition Economies,” in D.  Evanoff and G.  Kaufman (eds.), Systemic Financial Crises: Resolving Large Bank Insolvencies (Singapore: World Scientific Publishing), 141–59.

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Banking in the Transition Countries   1151 Bonin, J. P., Hasan, I., and Wachtel, P. (2005a). “Bank Performance, Efficiency and Ownership in Transition Countries,” Journal of Banking and Finance, 29, 31–53. Bonin, J.  P., Hasan, I., and Wachtel, P. (2005b). “Privatization Matters: Bank Efficiency in Transition Countries,” Journal of Banking and Finance, 29, 2155–78. De Haas, R. (2014). “The Dark and the Bright Side of Global Banking: A (Somewhat) Cautionary Tale from Emerging Europe,” Comparative Economic Studies, 56, 271–82. De Haas, R., Korniyenko, Y., Pivovarsky, A., and Tsankova, T. (2015). “Taming the Herd? Foreign Banks, the Vienna Initiative and Crisis Transmission,” Journal of Financial Intermediation, 24(July), 325–55. Demirgüç-Kunt, A., Klapper, L., Singer, D., Saniya, A., and Hess, J. (2018). “The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution,” World Bank. EBF (European Banking Federation) (2017). “EBF Facts & Figures,” available at: https://www. ebf.eu/facts-and-figures/. EBRD (European Bank for Reconstruction and Development) (2006). “Finance in Transition. Transition Report 2006,” available at: https://www.ebrd.com/downloads/research/transition/TR06.pdf. EBRD (2015). “Rebalancing Finance. Transition Report 2015–16,” available at: https://www. ebrd.com/documents/oce/pdf-transition-report-201516-english.pdf. ECB (European Central Bank) (2017a). “Report of Financial Structures,” October 2017. ECB (2017b). “European Central Bank, Statistical Data Warehouse,” available at: https://sdw. ecb.europa.eu/. Epstein, R. (2014). “When Do Foreign Banks “Cut and Run”? Evidence from West European Bailouts and East European Markets,” Review of International Political Economy, 21, 847–72. Hasan, I. and Marton, K. (2003). “Banking in Transition Economy: Hungarian Evidence,” Journal of Banking and Finance, 27, 2249–71. Haselmann, R. (2006). “Strategies of Foreign Banks in Transition Economies,” Emerging Markets Review, 7, 283–99. Haselmann, R. and Wachtel, P. (2007). “Risk Taking by Banks in the Transition Countries,” Comparative Economic Studies, 49, 411–29. Haselmann, R. and Wachtel, P. (2010). “Bankers Perception of the Legal Environment and the Composition of Bank Lending,” Journal of Money, Credit and Banking, 42, 965–84. IMF (International Monetary Fund) (2013). Financial Stability Assessment/Article IV 2013 on Austria. Impavido, G., Rudolph, H., and Ruggerone, L. (2013). “Bank Funding in Central, Eastern and South Eastern Europe Post Lehman: A ‘New Normal’?” IMF Working Paper No. 148/2013. Mérő, K. and Piroska, D. (2016). “Banking Union and Banking Nationalism—Explaining Opt Out Choices of Hungary, Poland and the Czech Republic,” Policy and Society, 35, 215–26. Popov, A. and Udell, G. (2012). “Cross-Border Banking, Credit Access and the Financial Crisis,” Journal of International Economics, 87, 147–61. Steinherr, A. (2006). “Russian Banking since the Crisis of 1998,” Economic Change and Restructuring, 39, 235–59. World Bank (2018). Global Financial Development Database, available at: https://www.worldbank.org/en/publication/gfdr/data/global-financial-development-database.

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chapter 37

Ba n k i ng i n L ati n A m er ica Developments and Prospects Fernando J. Cardim de Carvalho, Luiz Fernando de Paula, and Jonathan Williams

37.1 Introduction A deep transformation of banking systems in Latin America has taken place during the concluding years of the twentieth century and the nascent years of the new ­millennium. Liberal reforms were widely adopted in the region, frequently related to the financial crises experienced in Latin America in the 1980s and the first half of  the 1990s. Common features of these reforms were the liberalization of interest rates, the attenuation of barriers to entry in the provision of banking services, largescale p ­ rivatization of state-owned banks, and the facilitation of entry for foreign banks. In parallel, but in a largely independent process, liberalization of the capital account of the balance of payments also influenced the evolution of domestic ­financial s­ystems, since it opened new opportunities of investment for resident wealth-holders at the same time in which it made possible for non-residents to buy assets and offer financial services to residents. The downside of such a process, of course, is the increasing exposure of these economies to the volatility of international financial markets. The joint impact of all these changes was to transform deeply the ways financial systems work in Latin America. In fact, the transformation process is still unfolding. Among the most visible changes already achieved is the strong process of bank consolidation that

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Banking in Latin America   1153 has taken place in the period. Of interest are the effects of consolidation on competition and efficiency in banking sectors. In September 2008, Latin American economies were hit by the shock waves generated by the closure of Lehman Brothers. Losses suffered by foreign investors in their markets of origin led them to repatriate their investments, depreciating local currencies (and/or depleting international reserves to the extent that some local authorities tried to limit currency depreciation). Almost all Latin American countries have suffered, at some point in their recent history, serious balance of payments crises, so capital flow reversals led to a deterioration of expectations that amplified the impact of the initial shock. The economies and financial systems of Latin America were, in 2008, better placed to withstand the effects of such exogenous shocks than at any other time in the recent past. Since 2003, Latin America had enjoyed a general upturn in economic growth and macroeconomic stability, including falling inflation and improved fiscal positions (BIS, 2008). In Latin America, banks’ exposure to securitized credits was minimal because the regional market was relatively nascent and regional subprime mortgage securities markets did not exist. Hence, banks in Latin America were spared the credit and market value losses that plagued banking systems in the US, Europe, and, to some extent, Asia. Notwithstanding, the most important crisis transmission channel was the contractionary impact on trade that resulted from the transmutation of the financial crisis into a full-blown economic crisis in 2009. However, the negative impact on the region was relatively more benign than in other emerging economies. In the aftermath of the global financial crisis (GFC) and in the developed and most emerging economies, private banks contracted sharply their loan growth rates. In Latin America, however, the growth in lending by state-owned banks exceeded that of domestic and foreign banks, thereby, performing a countercyclical role. In some countries in Latin America, development banks were of paramount importance. Another factor that helped countries in Latin America to offset the contractions in trade with the US and Europe was the rapid growth of trade with China. China has become the second most important export market for Latin America and the Caribbean with exports increasing to 1.9 percent of GDP in 2017 from 0.4 percent in 2002 (Ray, 2018). The structure of this chapter is as follows. After this Introduction, section 37.2 provides an overview of the recent consolidation of banking sectors in Latin America. In section 37.3, we consider the evolution of financial policy and its contribution toward the recent consolidation process. Section  37.4 investigates the effects consolidation has had on banking sectors. Section 37.5 considers developments in bank regulation and supervision and trends in regulatory capital and asset quality post GFC. Besides updating the chapter on Banking in Latin America in the previous edition of this Handbook, this chapter now includes a new section (37.6) on development banks, including how authorities across Latin America successfully used these institutions to combat the GFC. Last, we develop some concluding notes in section 37.7.

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1154   Banking Systems Around the World

37.2  Banking Consolidation in Latin America: A Quick Overview Banking crises, financial deregulation and the globalization of financial services led to a significant increase in foreign bank penetration of emerging market banking sectors over the second half of the 1990s and into the 2000s, which raised levels of competition and forced both banks and their regulators to change their ways of doing business (Hawkins and Mihaljek, 2001). While these factors shaped the process of bank consolidation in developed and emerging markets, some specific features characterize consolidation in emerging markets (Gelos and Roldós, 2004; IMF, 2007). First, cross-­border mergers and acquisitions (M&A) became an important source of consolidation in emerging markets, yet the exception in developed markets. Second, consolidation was a means to restructure emerging market banking sectors following financial crises rather than to eliminate excess capacity or improve bank efficiency, as in developed markets. Finally, emerging market governments actively participated in the consolidation process, whereas consolidation tended to be “market-driven” in developed markets since it represented financial institutions’ response to the implementation of liberal and deregulatory policies of the 1970s and 1980s. A higher level of bank consolidation exists in Latin America compared to other emerging markets. National governments actively participated in bank restructuring and implemented substantial bank privatization programs, although in countries such as Argentina and Brazil some large banks remain under state ownership. In the 2000s, the consolidation process—especially in Brazil and Mexico—has become increasingly market-driven (as in developed markets). Generally, the desire to enhance competition and efficiency and, in some cases, to restructure public finances, formed the background to almost all privatization programs in the region. The role played by foreign banks in the restructuring and consolidation of domestic banking sectors should not be underestimated. Banking crises across Latin America offered foreign banks an opportunity to expand their business, often by acquiring local financial firms, with encouragement provided by governments’ deregulatory policies and the need to recapitalize domestic institutions (CGFS, 2004). This has happened in Argentina, Brazil, and Mexico. Conse­ quently, foreign banks’ shares of banking sector assets increased substantially in Latin America, exceeding shares found in Asia though not Central and Eastern Europe (Domanski, 2005). Recent developments suggest a partial reversal in the increase in foreign bank penetration in Latin America. IMF (2016, pp. 26–7) reports a new trend toward greater regional integration following mergers and acquisitions by Latin American banks of international banks exiting from the region: a) Regional banks, especially Colombian banks, acquired the businesses of HSBC, Santander, BBVA and Citibank as they exited particularly from Central America,

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Banking in Latin America   1155 but from also Paraguay and Peru; Colombian banks have attained a ­significant market position in Central America, that is, 22 percent of assets on average; b) Two Brazilian banks have adopted a regional perspective and established a significant presence across Latin America: Bank Itaú (a large universal bank) has the strength and the ambition to become the major regional player, expanding mainly via M&A (recent acquisition of Corpbanca in Chile), and through a few greenfield investments in Colombia and Mexico. Similarly, BTG Pactual (an investment bank) aspires to be the investment bank of the region—expanding throughout much of Latin America following the withdrawal of global banks. Latin America had received record levels of foreign direct investment (FDI) in the 1990s, and net FDI has been increasing since the late 1990s for most Latin American countries. In 1998 alone, the region received an inflow of $76.7 billion, equivalent to 41 percent of total FDI to developing countries (ECLAC, 2000, pp. 35–6). However, the proportion of inflows to Latin America continually fell in the 2000s to 19.7 percent in 2007. A resurgence post crisis (24.8 percent in 2010) has withered with inflows returning to pre-crisis levels (19.9 percent in 2015). Yet, net FDI flows (to GDP) to Latin America compare favorably against other emerging markets. In 2015, Chile recorded the largest net inflow (8.4 percent) followed by Uruguay (4.6 percent), Peru (4.4 percent), Brazil (4.1 percent) and Ecuador (4.0 percent). Regional inflows and the stock of inward FDI are concentrated in Brazil and Mexico. The stock of inward FDI as a share of GDP increased between 1998 and 2015 and now accounts for a significant share of GDP for most countries in Latin America, particularly, Chile and increasingly so in Colombia, Mexico, Peru and Uruguay. The inward stock of FDI for Latin America stood at $1,600.6 billion in 2015. In comparison, China’s stock was equivalent to 76 percent of the Latin America total up from 40 percent in 2010 although China’s stock-to-GDP is relatively low when compared to countries in Latin America. Bank restructuring has increased the level of concentration in regional banking sectors. While bank numbers have fallen—considerably in some countries—the accompanying increases in concentration were not as sharp. Table 37.1 shows five-firm asset concentration ratios (CR5) for banking sectors in Latin America plus data for a comparator group of emerging economies, the UK and US. Concentration levels in Latin America increased between 2003 and 2015 consistent with experiences in developed markets, the UK and US. Concentration increased by over 20 percentage points in Brazil (to 81 percent) and Colombia (to 78 percent), which indicates the continuation of a consolidation process, while levels fell by around 10 percentage points in Mexico (to 70 percent) and Bolivia (to 73 percent). In countries such as Mexico and Argentina, the rise in the level of consolidation was closely tied to foreign bank penetration. In Mexico, foreign banks had unrestricted access to all sectors of the banking market after the financial and exchange rate collapse of 1994–5, which forced the Mexican government to implement measures aimed at reducing the high insolvency of banks (including the acceleration of the process of

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1156   Banking Systems Around the World

Table 37.1  Market Concentration and Foreign Bank Penetration 5 Firm Concentration, %

Foreign Bank Number % of All Banks

Country

2003

2007 2010 2015

2003

2007

2013

2004

Argentina Bolivia Brazil Chile Colombia Ecuador Mexico Paraguay Peru Uruguay Venezuela China India Indonesia Russia S. Africa Turkey UK US

63.1 82.1 57.6 73.4 52.7 68.2 81.4 73.8 88.3 72.3 64.4 82.3 44.8 66.1 47.7 99.9 87.3 48.2 31.0

56.1 97.6 61.8 73.2 69.4 70.0 76.8 71.9 91.8 81.7 50.0 69.9 42.3 58.4 28.8 98.9 64.3 76.7 43.7

35 45 34 42 24 15 49 62 60 78 22 7 9 29 12 17 20 51 21

32 40 36 45 29 15 39 62 64 80 23 15 11 46 17 22 39 56 26

32 30 40 41 42 22 37 64 69 78 27 20 12 48 17 24 38 58 31

29 36 19 – 10 12 82 68 41 50 31 – 4 30 7 22 15 9 20

59.5 78.5 76.1 72.1 67.0 72.9 74.1 75.5 88.3 76.3 61.3 63.9 39.9 57.9 36.2 99.3 64.8 75.5 48.1

57.5 73.0 80.5 67.7 77.9 78.1 70.1 67.4 88.0 84.2 70.1 52.5 45.3 56.5 53.3 99.0 65.1 71.4 46.5

Foreign Bank Assets % of All Banks 2007

2013

27 18 25 42 14 13 78 58 49 47 25 2 4 23 10 23 16 14 22

25 16 15 33 15 12 70 51 51 92 18 2 3 27 8 23 14 14 11

Note: Data in italics are for the nearest year to that shown in the column. Source: World Bank, Global Financial Development Database; Claessens and Van Horen (2015).

opening-up to foreign investment), and became market leaders. By 2004, foreign banks held 82 percent of banking sector assets. Notwithstanding, a marked reduction in foreign bank share has taken place over the past decade, reaching 70 percent in 2013 from 78 percent in 2007 (Claessens and Van Horen, 2015). While foreign banks came to dominate domestic banks in Argentina—as they increased their market share from 16.1 percent of total bank deposits in November 1994 to 51.8 percent in December 2001 (Fanelli, 2003, p. 52)—their presence partially wavered after the 2001–2 financial crisis as their market share declined while the market shares of private and mainly public-owned banks increased. The retrenchment caused foreign bank asset share to fall from 29 percent in 2004 to 25 percent in 2013, with foreign bank numbers falling by three percentage points from 35 percent to 32 percent (Claessens and Van Horen, 2015). Domestic private and public banks are market leaders in Brazil. Indeed, private-owned banks responded proactively to foreign bank penetration and became active in domestic M&A (Paula and Alves, 2007). Consequently, foreign bank assets fell to 15 percent from 25 percent between 2007 and 2015 (Claessens and Van Horen, 2015). The consolidation process in Chile proceeded more gradually: it has increased because of M&A in Spain (the home country of the parent banks of the two largest banks in Chile); technically, the enlarged Spanish parent has operated its Chilean subsidiaries as individual entities (Ahumada and

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Banking in Latin America   1157 Marshall, 2001). Consistent with experiences across the region, foreign bank assets fell by nine percentage points to 33 percent in 2013 from 2007. Bank restructuring and privatization ushered in a new wave of cross-border (and domestic) M&A activity. Cross-border bank M&A partially reflects country-specific factors: positively related to shared language (Spanish bank entry; Sebastián and Hernansanz, 2000) and geographical proximity (North American bank entry; Buch and DeLong, 2001); and the availability of access to large, relatively poor countries with widely spaced populations and underdeveloped financial sectors (Buch and DeLong,  2001; Focarelli and Pozzolo, 2001). One can analyze M&A in terms of the financial condition of buyers and targets. An application to Brazil differentiates between M&A involving domestic-owned and foreign-owned banks. The results suggest domestic and foreign buyers acquired target banks that had alternative profiles: domestic buyers prefer to buy underperforming banks while foreign buyers tend to acquire large, slow growing institutions; the implication is that foreign banks see M&A as a vehicle to increase bank size and market share (Cardias Williams and Williams, 2008). One important development in Brazil after, and in consequence of, the 2008 crisis was the large bank merger between Itaú and Unibanco. However, the deal was more of an acquisition of Unibanco, which had become weaker after suffering heavy losses from the depreciation of the Brazilian currency (the Real) following the collapse of Lehman Brothers. Indeed, many large firms had bet that the Real would continue to appreciate and, as a consequence, suffered large losses. Claessens and Van Horen (2014) have constructed a database on foreign bank ownership from which we highlight the following features between 2003 and 2013. Either foreign bank penetration, measured as the percentage of foreign banks in the banking sector, or foreign bank assets share is much greater in Latin America than other emerging markets we select for comparison. Foreign bank asset penetration is lower than their number in much of Latin America barring Mexico and Uruguay, and Paraguay and Peru to a lesser extent. The level of foreign bank penetration is lower in 2013 compared to a decade earlier, which reflects difficulties foreign banks faced in some countries in Latin America, the expansion of private-owned banks, and use of state-owned banks to provide credit during the GFC (see Table 37.1). The changes in foreign bank penetration between 2006 and 2013 suggest one effect of the crisis has been to reduce foreign bank assets share across the region, and in countries such as Brazil and Mexico, by over ten percentage points. Colombia and Peru are exceptions.

37.3  The Evolution of Financial Policy in Latin America The process of transformation of Latin American banking systems shares common features across countries including taking place in roughly the same period. However, the causes of the process diverged from country to country. Post-1945, Latin American

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1158   Banking Systems Around the World financial systems were typically repressed, and governments across the region attempted to accelerate economic growth and transform social and economic structures from the late 1940s albeit with varying success. The objective was to evolve into a developed country, and the way to achieve this was to industrialize as quickly as possible. Inspired by the experiences of Central European countries (cf. Gerschenkron, 1962), Latin American governments, particularly in the largest countries (Brazil, Mexico, Argentina, and Chile) saw in the banking system a powerful instrument to centralize and direct the necessary resources to finance the growth of manufacturing production. Unwilling to rely on the eventual ability of freely operating financial markets to support an accelerated growth process, governments in those countries imposed financial repression (Fry, 1995). This consisted mostly of creating, or enlarging the functions of existing, state-owned banks, setting maximum interest rates to be charged on loans by private banks (frequently adopted in the context of usury laws), and directing the credit supplied by these banks to sectors considered strategic to enhance economic growth.

37.3.1  Financial Liberalization in Latin America: Causes and Outcomes This chapter is not the place to assess how successful these initiatives were in promoting growth.1 The region suffered heavily with the oil shocks of the 1970s. The attempts to deal with the effects of those shocks by increasing short-term foreign debt led to the debt crisis of the early 1980s. This brought the most important economies of the region to a standstill that lasted so long, commentators know it as the “lost decade of economic growth.” As part of the negotiated resolution package for that crisis, almost all countries in Latin America accepted to promote liberalizing reforms, including in the financial sector, and thereby ending the financial repression experiment. Chile was the pioneer in this process (see Foxley, 1983; Stallings and Studart, 2006). Liberal reforms in banking markets, including privatization of state-owned financial institutions, began right after the 1973 military coup that ousted then-President Salvador Allende. The root cause of financial liberalization in the case of Chile was the radically conservative nature of the military regime led by General Pinochet, which aimed at erasing all and any trace of the policies adopted before. As it has happened in similar experiences, strong liberalization policies created new profitable opportunities for banks that raised their competitiveness. However, financial regulation and bank supervision were deficient, either because regulators lacked experience with open markets, or because the state was assumed to be an inefficient player in the economic game, so no investment in upgrading the skills of regulators and supervisors was made. Inevitably, as has been the general experience, this first wave of liberalization ended up generating a profound banking crisis in the early 1980s. To resolve the crisis, the government intervened heavily in the banking system. The authorities gave permission for banks to sell to the government 1  Higher growth rates did occur although at the cost of the emergence of some important disequilibria.

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Banking in Latin America   1159 their non-performing assets, under the obligation of buying them back over time in expectation of the resolution of the crisis. In addition, the adoption of tougher bank regulations aimed to prevent the disorderly expansion of the past from repeating itself. In the case of Mexico, less dramatic events were the inspiration for banking reforms (see Singh et al., 2005; Avalos and Trillo, 2006; Stallings and Studart, 2006). Mexico had also followed the general pattern, set by the largest economies of Latin America in the post-war period, of creating strong state-owned banks to stimulate economic development. Room for private banks was very limited and foreign banks were all but banned from operating in domestic markets. As late as in the early 1980s, rules forbade foreign banks from controlling more than 7 percent of the net worth of the largest banks. The 1982 debt crisis, the ensuing period of economic stagnation, and the conditionality clauses included in the rescue packages negotiated by the Mexican government with creditor banks and multilateral institutions, led the Mexican authorities to a change of heart. The government endeavored to promote liberal reforms in the economy, of which banking reform was an important element (see de Vries, 1987). Later, Mexico’s accession to NAFTA strengthened this drive, which led to a gradual but steady reduction of ­barriers to entry for US and Canadian banks.2 The defining act of Mexico’s reforms, however, was the bungled privatization process of 1991, which took place when there were still strong restrictions against foreign participation in the domestic banking sector. Executives with little or no experience of running banks acquired the privatized banks at excessive prices. The rush to recover their investments and to obtain profits led to a credit boom unrestrained by any kind of proper regulation. Credit rapidly expanded without due attention to credit risks. The fast expansion ultimately caused the 1994 crisis and renationalization of bank assets. In fact, the Mexican government, first in 1995, and again in 1996, bought the huge amount of non-performing assets in banks’ balance sheets through a crisis resolution entity created to manage the problem (Fobaproa).3 Contrary to what was done in Chile, however, those assets were not reabsorbed by the banking system; rather, taxpayers’ money paid for the losses of banks, since Fobaproa’s liabilities were transformed into public debt. The weakness of the banking system led the Mexican government to change the law to allow wider participation of foreign banks in domestic markets, including the acquisition of local problem banks. Consequently, the market share of foreign banks in Mexico was over 80 percent in 2000 (HernandezMurillo, 2007, p. 416). In Brazil and Argentina, the causes of the liberalization process were somewhat more complex due to persistently high inflation. In both cases, most (but not all) reforms were elements of price stabilization strategies. Up until the 1970s, the Brazilian banking system 2  In 1995 a modification increased the limits of foreign participation established under the NAFTA agreement (initially foreign banks could not buy domestic banks whose market share exceeded 1.5 percent). In December 1998, the Mexican Congress approved a further modification allowing foreign investment in domestic banks to reach 100 percent. Subsequently, foreign banks acquired the largest banking institutions (Bancomer, Banamex, and Serfin) (Maudos and Solis, 2011). 3  Estimations of the ratio of non-performing loans-to-total loans reached 52.6 percent by December 1996 (Hernandez-Murillo, 2007, p. 421).

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1160   Banking Systems Around the World had been highly repressed (Carvalho, 1998). State-owned institutions dominated the banking system even though the presence of private banks was strong. Foreign banks serviced mostly foreign companies, and as in other countries, were not allowed to reach domestic clients (Carvalho, 2000). In the mid-1960s, the structure of the Brazilian financial system changed with the imposition of a segmented market model like the one set by the Glass–Steagall Act in the US. Under this model, commercial banks provide short-term credit and payment services; investment banks develop an incipient securities market; specialized institutions finance the acquisition of durable consumption goods; and public institutions give financial support to productive investments in manufacturing, agriculture, and construction.

37.3.2  A New Model and Restructuring Initiatives: Privatization and Universal Banking Thanks to loopholes in the legislation, financial conglomerates, with interests in virtually all segments of the financial system, and in non-financial sectors as well, emerged in the 1970s and early 1980s. In parallel, the acceleration of inflation after the oil shocks of the 1970s steadily reduced the access of private borrowers to credit markets. Banks were increasingly devoting the resources they controlled to buying public debt issued by the federal government, which was unable to control its fiscal deficits. Market segments other than deposit-taking and public-debt-buying, and the institutions supposed to operate them, gradually faded and disappeared. Under these circumstances, in 1988, the Central Bank of Brazil passed a resolution to adopt a German-type universal banking model in place of the segmented model.4 The same resolution lifted interest rate controls. Financial liberalization in Brazil, therefore, began as the result of an acknowledgment that past regulations had become obsolete rather than being the first step of a well-defined strategy (Paula, 2011). In Argentina, developments that were to some extent similar took place in the same period.5 Accelerating inflation, as in Brazil, was the most important problem faced by policymakers at the time. By the late 1980s, the many failed attempts at price stabilization had virtually depleted the arsenal of instruments to control inflation. Moreover, foreign creditors demanded the implementation of financial liberalization policies as a conditionality clause in the resolution package for the debt crisis of 1982. The Argentine government had little choice but to begin a liberalization process, by freeing interest rates and moving toward a universal bank model, leaving to each financial institution the choice of sectors where to operate.

4  The term for universal banks is “multiple banks” in Brazil. 5 Decisions concerning financial liberalization in Argentina since the late 1980s are listed (in Portuguese) in Studart and Hermann (n.d.) and are reproduced and discussed in Carvalho (2008). For an overview of the process, see O’Connell (2005).

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Banking in Latin America   1161 After 1991, with the adoption of the Convertibility Plan (also known as the Cavallo Plan, named after then Finance Minister Domingo Cavallo), in contrast to the more pragmatic Brazilian experience, a radical liberalization strategy was put in place. A central element of this strategy was to open the domestic banking market to foreign banks. The implementation of a restructuring and concentration policy, a response to contagion from Mexico’s Tequila crisis that severely tested both the Convertibility system and the financial sector, promoted widening access to foreign banks; consequently, foreign bank penetration of the Argentinean banking system increased dramatically. Among the ten largest banks in Argentina in December 2000, seven banks were foreign-owned, two were publicowned—the market leaders, Banco de la Nación (Federal) and Banco de la Provincia de Buenos Ayres (provincial)—and only one bank was domestic, private-owned (Paula and Alves, 2007, p. 97). The process of privatization of state-owned banks in Argentina illustrated an important change of views that had already taken place in countries such as Chile and Uruguay. In these cases, the adoption of liberalization was a strategy rather than an expedient, and privatization was not a temporary convenience or an unavoidable evil. Bank privatization was an element, no matter how important, of an overall liberalization process expected to help the region to overcome its long-term inefficiencies. The deep crisis of the early 2000s led to a partial repudiation of this view in Argentina. It is still dominant in Chile and Uruguay, even after the election of center-left administrations at the beginning of the new century. In Brazil, in contrast, this path was explored with caution. In fact, the end of inflation in 1994 caused severe stress in many banks that earned their profits mostly from securing deposits to finance the purchase of public debt, with yields indexed to the rate of inflation. When inflation fell precipitously, after the implementation of the Real Plan in 1994, many banks were practically bankrupt. The Brazilian government, to avoid panic, took measures to allow for splitting problem banks into two parts: a “sane” one, with healthy assets and its corresponding share of liabilities; and the failed one, with the nonrecoverable assets. Other banks eventually bought into the sane part while the Central Bank liquidated the failed part. Argentina adopted the same scheme based on rules used in the US to deal with Continental Illinois Bank in the mid-1980s (De la Torre, 2000). Like in Brazil, Argentina avoided a panic at the cost of pushing bank consolidation forward. In Brazil, the Central Bank decided to invite foreign banks to buy the domestic banks that the authorities wanted to privatize, or the banks facing difficulties that would probably lead them to fail. The rationale behind the decision to widen access to foreign banks was to prevent excess concentration that the authorities expected to ensue, should the leading domestic banks acquire problem banks. Although, the Brazilian government never lifted the legal restriction banning the entry of new foreign banks in the domestic system, it does allow “exceptions” if needed. On stabilizing the economy, and after selling problem banks, the government authorized practically no new foreign bank into the country. Mexico was the last large country in Latin America to open its market to foreign banks. However, Mexico granted foreign

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1162   Banking Systems Around the World banks the most unrestrained access to domestic markets, leading to an almost complete disappearance of domestic private banks, let alone state-owned banks.

37.3.3  Global Financial Crisis and Consolidation The GFC changed the appreciation of the role of state-owned banks in some countries. In the case of Brazil, the three largest federal-owned banks (the National Development Bank, BNDES, Bank of Brazil and the National Savings Bank, CEF) served as instruments for the implementation of anticyclical policies, supplying credit when private banks retreated in the face of increased uncertainty. As a result, the market share of federalowned banks increased during the crisis. These banks maintained their lead position, even after private banks expanded to recover at least part of their lost market share. Argentina has empowered state-owned banks as instruments of anticyclical policy (BCRA, 2012). In fact, since April 2012, the Argentine Central Bank is responsible for promoting growth, full employment, and income distribution, besides maintaining the purchasing power of the peso. This had led to the creation of many programs to spur growth of credit to non-financial firms. The trend toward consolidation is not new to the region. Previously, waves of bank consolidation had taken place in some countries, mostly induced by domestic policies. In Brazil, for instance, in the early 1970s, the Federal government promoted consolidation under the expectation that taking advantage of supposedly strong economies of scale would allow the reduction of interest rates necessary to keep the economy growing as rapidly as it was. Financial repression was still in force and foreign participation was limited. Increasing efficiency via scale economies should lighten the burden of interest rate controls on banks, attenuating the incentives to evade these controls. In any case, Latin American economies are still relatively small. If to the small dimension of these economies one also adds the generally high degree of income concentration, markets for banking services would be even smaller. If scale economies exist in banking, one would expect to find a relatively high degree of concentration in the region anyway. The push for consolidation came from many sources. Political and ideological factors were very important in the case of Chile in the mid-1970s, to allow banks to decide their own policies, including larger and stronger banks to absorb smaller ones. After the early 1980s crisis, the push for consolidation was strengthened by the assumption that larger banks, especially foreign ones, could manage risk more efficiently, especially if prudential regulation was improved, thereby making the system more stable. Concerns with systemic stability help to explain consolidation, in one way or another, in nearly all the region’s recent experiences. Many of the regulatory initiatives adopted to strengthen the stability of banking systems contributed to push consolidation forward. The introduction of modern payments systems, the increasing use of ATMs, Internet banking and so forth, also led to increased consolidation if individual banks must provide their own equipment and other facilities. Even privatization initiatives were defended with systemic safety arguments, on the notion that state-owned financial institutions

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Banking in Latin America   1163 increase the risk of feeding dangerous forms of crony capitalism. Consequently, at the turn of the millennium, the most important banking systems in Latin America came to exhibit a relatively similar ownership structure.

37.4  Financial Penetration in Latin America Latin American financial systems share similar features: financial depth is limited; financial sectors are bank-based since stock markets are mostly small and illiquid, and corporate debt markets even more so; intermediation margins are high by international standards; banking sector concentration has increased; and bank lending is low relative to overall economic activity. A limited access to bank credit and uncertainty about financial stability contributed to economic volatility in the region (Singh et al., 2005). In the previous edition of this chapter, we noted that the trajectory of financial deepening and access to financial services would depend on developments to institutional environments that condition the effective operation of financial intermediaries and financial markets. In what follows, we note a recent, general increase in financial depth and improvements in access to financial services in Latin America but add the caveat that heterogeneity remains an important feature. Whereas financial systems across Latin America grew deeper since the mid-1990s (Rojas Suarez, 2007), the level of financial depth is low in comparison with industrialized countries and other emerging market regions such as East Asia. Table 37.2 portrays trends in financial depth based on alternative indicators for the region and comparator countries. The data show the heterogeneity across Latin America and we summarize the following observations. The ratio of liquid liabilities-to-GDP shows levels of financial depth have accelerated between 2003 and 2015 with few ill effects from the GFC, for instance, Brazil and Paraguay, Peru and Uruguay, albeit to a lesser extent. Financial deepening stalled somewhat between 2007 and 2010 but resumed positive trajectory to 2015 in Chile, Colombia, and Ecuador. Although central bank lending increased as part of resolution strategies to deal with the GFC, nevertheless, the trend is toward a general and significant deepening of private sector financial activity in most countries. Using the ratio of stock market capitalization-to-GDP to proxy developments in equity markets, stock market depth in Latin America lags behind banking sectors except in Chile where depth compares to industrialized countries (Betancour, De Gregorio, and Jara, 2006; Rojas Suarez, 2007). Despite a deepening of stock markets pre-2008, the trend has reversed subsequently with notable reversals in Brazil, Colombia, and Peru. Broadly speaking, stock market depth in Latin America compares unfavorably to some other developing economies. Besides the historically and generally low, albeit deepening, levels of credit, the pattern of credit growth in Latin America has been marked by boom and bust cycles, particularly

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1164   Banking Systems Around the World in economies with lower proportions of bank credit-to-GDP. Credit had expanded sharply across the region in the early 1990s, in part due to increased capital inflows, but it collapsed in many cases after the mid-1990s banking crises and remained subdued for many years. Only after 2004, did credit begin to recover on the back of stronger economic growth, easier global monetary conditions, and progress in bank restructuring (Jeanneau, 2007). Yet, in most Latin American countries, macroeconomic instability has been a critical factor in holding back financial system development and generating a high volatility of credit growth. For example, high short-term interest rates used to combat inflation or defend an exchange rate simply added to banks’ funding costs and increased loandefault rates (Singh et al., 2005). The third indicator in Table 37.2 shows the amount of private credit by banks and other financial institutions in GDP. The post-crisis data confirm the heterogeneous nature of financial developments in Latin America. Private credit is more important to the economy in Chile (106.9 percent in 2015) and Brazil (71.3 percent) with strong growth in private bank credit between 2010 and 2015 in Paraguay (23.4 percent) and Bolivia (18.4 percent). However, private credit holds a greater share of GDP in industrialized countries and in other emerging economies like China. There are legitimate concerns that the composition of bank portfolios probably led to some crowding out of private sector credit. This was because of banks’ tendencies to hold high proportions of government securities in their portfolios, which possibly reflected historical patterns of behavior associated with hyperinflation. In the latter 1990s, banks replaced non-performing loans with sizable portfolios of government securities in Argentina, Mexico, and Venezuela. Whereas banks reacted to fiscal consolidation (in Argentina, Mexico, and Brazil) by reducing the amount of government securities in their portfolios, the onset of the GFC in 2007 caused a reversal as bank liquidity ratios increased in most countries, often by significant amounts (Argentina, Bolivia, Mexico, and Peru). In most other countries, the private sector receives the bulk of domestic credit although government and state-owned firms receive relatively more credit in the larger economies of Brazil (41 percent of GDP in 2015), Mexico (17.7 percent) and Argentina (8.8 percent). Despite a general growth in deposit-taking, the opportunity to raise deposits in Latin America in general remains, especially in countries such as Mexico (29.3 percent of GDP) and Peru (28.7 percent). The final indicator is the ratio of bank credit-to-bank deposits and a proxy for intermediation. In the previous edition, we reported that the level of intermediation increased in most countries between 1990 and 2000. Consistently high levels of banking sector intermediation occur in Chile (149.8 percent in 2015), Colombia (180.8 percent in 2015) and Paraguay (101.3 percent in 2015). Post-crisis, intermediation is higher in Brazil (by 51.3 percent between 2007 and 2015) and Peru (23.4 percent). However, intermediation levels have weakened over time in Bolivia and Ecuador. If financial depth and access to financial services are to increase, there should be developments in the institutional environment, which conditions the effective operation of financial intermediaries and financial markets. Honohan (2007) provides comparative data on households’ access to financial services. He reports that access in Chile is

Table 37.2  Financial Depth and Credit Indicators Liquid Liabilities-to-GDP, %

Stock Market Cap-to-GDP, %

Private Credit-to-GDP

Bank Credit-to-Bank Deposits

2003

2003

2003

2003

2003

2007

2010

2015

2003

2007

2010

2015

2003

2007

2010

2015

Argentina Bolivia Brazil Chile Colombia Ecuador Mexico Paraguay Peru Uruguay Venezuela China India Indonesia Russia South Africa Turkey UK US

27.1 52.6 45.1 32.8 14.4 17.0 23.0 20.0 29.5 51.9 19.5 143.5 58.8 45.1 25.9 41.9 33.7 104.1 62.7

21.0 16.4 32.0 88.1 12.0 6.1 15.1 2.6 21.9 0.5 4.1 31.0 44.6 18.4 41.6 148.4 17.3 109.3 110.7

12.0 46.9 28.2 71.2 20.9 16.6 15.0 16.7 20.1 52.8 8.6 116.6 29.9 19.2 17.8 114.7 13.1 130.0 165.0

55.6 102.7 64.6 135.9 153.1 102.7 65.2 103.8 86.1 107.1 55.7 267.5 61.2 47.2 96.4 116.2 41.2 0.0 76.9

21.0 16.4 32.0 88.1 12.0 6.1 15.1 2.6 21.9 0.5 4.1 31.0 44.6 18.4 41.6 148.4 17.3 109.3 110.7

6.5 6.2 12.5 2.3 0.5 2.3 0.0 3.8 0.0 7.3 0.4 3.6 2.0 7.7 0.9 0.7 2.1 0.6 5.3

7.5 7.1 17.9 1.7 0.5 0.3 0.0 3.0 0.0 9.1 1.5 3.9 3.3 4.3 0.8 0.4 1.0 0.4 12.4

11.7 12.7 20.4 0.5 0.03 1.2 0.0 0.1 0.5 11.0 13.7 2.2 4.0 3.2 0.5 1.3 0.5 0.0 23.5

37.8 50.9 61.6 75.2 29.3 18.4 33.3 18.2 23.6 63.8 12.4 127.2 50.1 38.7 24.3 159.5 37.3 130.0 189.6

21.6 53.6 82.4 79.2 36.9 21.2 38.7 16.0 20.7 27.5 22.3 109.0 57.7 31.5 36.2 192.6 46.3 164.1 216.4

19.8 51.7 94.7 102.8 65.1 23.6 47.5 31.4 25.9 24.9 22.3 129.9 62.2 29.9 45.4 191.8 67.4 190.2 220.5

16.7 62.1 110.2 123.0 51.7 28.5 59.7 55.1 36.6 35.4 39.2 153.4 69.3 41.9 63.2 195.8 75.0 134.7 219.9

21.0 16.4 32.0 88.1 12.0 6.1 15.1 2.6 21.9 0.5 4.1 31.0 44.6 18.4 41.6 148.4 17.3 109.3 110.7

19.4 17.3 77.1 112.1 40.2 8.1 35.6 3.2 54.2 0.6 3.5 80.2 113.3 40.5 100.8 252.4 35.3 129.5 137.4

13.2 15.5 69.6 137.2 64.4 6.8 39.5 2.0 61.1 0.4 1.5 63.8 89.6 39.9 57.5 247.8 37.3 121.8 108.3

8.0 15.9 31.1 82.1 33.3 6.7 35.0 3.8 33.7 0.3 3.7 64.1 71.5 42.0 24.1 245.4 25.7 112.1 143.3

Note: Data in italics are for the nearest year to that shown in the column. Source: World Bank, Global Financial Development Database.

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Country

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1166   Banking Systems Around the World closest to the levels observed in industrialized countries; over 90 percent of households have access to financial services in Western industrialized countries compared with 60–80 percent in Chile, 40–60 percent in Brazil and Colombia, and 20–40 percent in Argentina and Mexico. Recent World Bank (2015) data show the percentage of adults with an account has increased in Brazil (to 68 percent) and Argentina (to 50 percent); access in Bolivia, Ecuador, and Uruguay lies between 40 and 50 percent with a higher level in Venezuela (57 percent) and a lower level in Peru (29 percent). Whereas debit card use has increased across the region, the proportion of account holders with cards exceeds 50 percent only in Brazil (59 percent) and Chile (54 percent). Payments by debit cards and credit cards are highest in these two countries. The financial inclusion data exhibit the heterogeneity that characterizes financial development in Latin America, which infers the potential for future growth. The World Bank’s Global Financial Development Database contains time series on several indicators of access to financial services. We consider trends in branching and automated teller machines (ATM) provision (commercial bank branches and ATMs both per 100,000 adults). In contrast to developing economies where bank branching is declining, there is mild growth in Latin America over 2007 to 2015 although the branch numbers are lower than in the UK (25.2 in 2013) and US (32.9 in 2015) with the exception of Colombia and Ecuador (257.7 and 75.8 in 2015, respectively). While the growth in ATMs is considerably higher than branches in Latin America, only Peru (119.2) and Brazil (114.0) come anywhere near to the UK (131.6). Nevertheless, ATM provision has increased significantly between 2007 and 2015 in Argentina (from 28.5 percent to 60.6 percent in 2015). Chile, Mexico, and Uruguay each have more than 50 ATMs per 100,000 persons in 2015. ATMs are the main mode of withdrawal; 71 percent of account holders use ATMS for this purpose in Latin America as a whole with higher levels in Argentina (78 percent), Brazil (75 percent), Chile and Colombia (both 81 percent), Uruguay (85 percent) and Venezuela (79 percent). The evolution of interest rate spreads infers how effective financial liberalization has been in Latin America. Weaknesses in the institutional environment are a partial explanation for the relatively high, by international standards, spreads observed and the dispersion of spreads across the region (Gelos, 2006). In the first edition of this book, we highlighted a narrowing of bank interest spreads in Latin America from 1993 to the mid-2000s. Table 37.3 updates the story for 2005 to 2016. The convergence of spreads has continued to 2016 with very low rates in Chile (1.8 percent) and Mexico (3.4 percent). Current spreads range between 10 and 15 percent in Paraguay, Peru, and Uruguay, but Brazil remains an outlier (40 percent). Table 37.3 shows deposit rates, loan rates and the real lending rate. Spreads move more with loan rates than deposit rates, meaning that a shock that causes spreads to widen will raise lending rates rather than decrease deposit rates. Lending rates remain relatively and stubbornly high in Latin America in comparison to other emerging economies. Lending rates in Brazil exceeded 50 percent in 2005 and 2016 with real rates exceeding 40 percent. Negative real lending rates existed in 2016 in Argentina and Venezuela.

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Banking in Latin America   1167

Table 37.3  Interest Rates, % Deposit Rate

Lending Rate

Real Lending Rate

Loan–Deposit Spread

Country

2005

2016

2005

2016

2005

2016

2005

2016

Argentina Bolivia Brazil Chile Colombia Ecuador Mexico Paraguay Peru Uruguay Venezuela China India Indonesia Russia South Africa UK US

3.8 4.9 17.6 3.9 7 3.6 3.5 1.7 2.6 2.8 11.6 2.3 – 8.1 4 6 – 3.5

24.3 1.4 12.4 3.8 6.8 4.8 1.3 3.8 2.6 5.6 15.1 1.5 – 7.2 7 7.2 – –

6.2 16.6 55.4 6.7 14.6 9.6 9.7 29.9 25.5 13.6 16.8 5.6 10.8 14.1 10.7 10.6 4.6 6.2

31.2 8 52.1 5.6 14.6 – 4.7 18.1 16.5 16.2 20.8 4.4 9.7 11.9 12.6 10.5 0.5 3.5

−3.8 10.1 44.6 −0.9 8.5 1.8 4.1 18 21.3 12.8 −9.9 1.6 6.2 −0.2 −7.2 4.9 2 2.9

−6.7 9.9 40.4 1.8 8.3 – 0.1 12.2 12.4 8.5 −16.5 3.1 5.8 9.2 8.7 3.2 −1.2 2.2

2.4 11.7 37.8 2.8 7.6 6 6.2 28.2 22.9 10.8 5.2 3.3 – 6 6.7 4.6 – 2.7

6.9 6.6 39.7 1.8 7.8 – 3.4 14.3 13.9 10.6 5.7 2.9 – 4.7 5.6 3.3 – –

Source: World Bank Development Indicators, Monetary Indicators.

Across Latin America and despite a deepening of credit markets, credit is not only scarce but costly too. IADB (2005) data show interest margins in Latin America (at 8.5 percent) exceeded margins in East Asia and the Pacific (5.1 percent) and the developed countries (2.9 percent), although these were slightly lower than Eastern Europe and Central Asia (8.8 percent) between the mid-1990s and mid-2000s. World Bank data through to 2015 confirm the relatively high bank net interest margins in Latin America. Notwithstanding, margins are narrowing, and are lower than pre-crisis levels in Brazil, Chile, Colombia, Mexico, Paraguay, Peru, and Uruguay. The downward trend in bank net interest margins, however, is associated with diminishing levels of bank profitability measured by return on assets in Brazil, Chile, Colombia, and Mexico. One possible explanation might be the increased holdings of liquid assets by banks in those countries before and after the GFC (see Table 37.4). Liquidity levels are larger in Latin America compared to other emerging market countries, such as China and India. Liquidity appears to have increased between 2007 and 2010 because of the GFC inducing a change in bank behavior. However, levels are particularly high in Brazil and Argentina, and Mexico and Uruguay to a lesser extent. The relationship between market concentration and interest rate margins is scarcely analyzed in Latin America. Recent evidence suggests market share exerts little or no

Net Interest Margin

Non-interest Income-to-Total Income

Liquidity

ROA

Country

2003

2007

2010

2015

2003

2007

2010

2015

2003

2007

2010

2015

2003

2007

2010

2015

Argentina Bolivia Brazil Chile Colombia Ecuador Mexico Paraguay Peru Uruguay Venezuela China India Indonesia Russia South Africa Turkey UK US

1.9 4.8 8.9 3.6 5.1 7.1 5.7 7.6 5.2 5.6 16.4 3.3 3.3 5.3 5.4 11.7 5.5 1.9 3.7

3.9 5.1 7.9 4.9 6.4 6.0 8.2 9.6 7.4 8.1 8.3 3.5 3.3 6.1 5.4 3.5 6.1 0.9 3.1

4.9 4.5 6.3 4.7 6.4 6.0 5.6 7.7 7.1 5.3 5.6 2.6 3.1 6.8 4.3 3.0 4.8 2.2 3.8

6.8 5.6 4.3 3.5 4.9 6.5 5.4 6.1 7.1 5.5 12.5 2.7 2.8 5.8 2.6 3.0 3.5 1.4 3.2

73.7 48.1 30.5 44.8 60.5 45.0 40.9 82.3 32.7 63.9 23.3 7.8 39.3 25.9 46.6 30.9 50.3 61.9 43.2

57.8 45.0 32.0 21.7 45.2 45.4 28.2 49.4 29.3 41.6 24.9 12.2 30.1 21.2 54.5 44.2 32.6 55.9 40.8

61.8 43.7 30.5 34.3 39.4 38.7 32.2 55.9 34.0 28.9 33.8 14.0 34.6 23.4 92.3 47.4 30.8 46.0 37.0

15.6 15.8 18.1 15.8 17.7 15.4 14.4 71.7 14.7 82.7 13.6 4.0 22.3 11.7 37.1 5.5 13.0 10.8 23.0

19.2 10.7 63.5 28.2 32.5 37.8 36.1 55.8 27.0 59.3 23.1 17.2 11.2 34.4 44.3 5.4 61.2 49.8 18.5

34.5 13.5 55.3 15.1 19.4 35.9 41.4 39.8 21.8 52.1 34.2 20.6 11.8 36.2 43.4 18.2 20.7 49.9 22.6

42.7 20.7 55.6 20.1 19.8 30.8 48.6 34.3 37.2 46.6 28.7 15.6 8.5 30.3 51.1 17.3 14.4 51.4 20.5

55.0 17.3 61.3 19.3 25.3 23.8 42.8 32.6 35.0 44.2 33.4 16.4 12.3 14.9 39.6 22.9 13.9 45.1 21.5

–3.6 0.3 2.0 1.6 2.1 0.6 1.5 –0.01 1.1 –1.7 5.2 0.7 1.0 1.8 2.4 0.1 2.1 1.2 1.4

1.3 2.2 2.7 2.0 2.3 1.4 2.5 3.2 2.7 2.9 2.5 1.3 1.0 1.7 2.1 1.5 3.0 0.7 0.9

2.7 1.5 1.6 1.7 2.2 1.4 1.5 3.1 2.4 0.7 1.5 1.1 1.1 2.2 0.5 1.0 2.4 0.0 0.7

2.5 1.0 1.1 1.1 1.4 0.8 1.2 2.0 1.9 1.0 3.5 1.0 0.3 1.7 –0.1 0.9 1.0 0.2 1.1

Note: Data in italics are for the nearest year to that shown in the column. Liquidity: liquid assets-to-deposits and short-term funding. Source: World Bank, Global Financial Development Database.

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Table 37.4  Margins, Diversification, Liquidity, and Profitability, %

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Banking in Latin America   1169 influence on interest rate margins; indeed, lower spreads result from markets that are more competitive and from improvements in efficiency (Chortareas, Garza-García, and Girardone, 2012). Such findings, however, do not generalize across the region: in Mexico, for instance, Maudos and Solis (2011) attribute the strong growth in banking system profitability over the immediate pre-crisis period to monopolistic competition. In Central America, bank interest margins have slightly ticked upwards over the period 1998–2014; the wider margins between loan and deposit rates reflecting the exercise of market power by banks (Birchwood, Brei, and Noel, 2017). Tables 37.4 and 37.1 indicate concomitant downward movements in net interest margins and increases in market concentration across the region with some exceptions. There is variation in movements in net interest margins across Latin America with margins trending downwards over time in most countries, with Argentina a notable exception. Notwithstanding, net interest margins in Latin America are higher than in other emerging markets and developed markets.

37.5  The Effects of Banking Consolidation 37.5.1  Market Structure, Privatization, Foreign Bank Penetration, and Bank Performance The privatization of state-owned banks dramatically altered the market structure of banking sectors in Latin America. Privatization has transformed the governance structure of domestic banks as new, private owners (domestic and foreign) assumed control of banks. Generally, and across Latin America, state-owned banks had served political and social purposes and they shared certain characteristics: weak loan quality, underperformance, and poor cost control. Indeed, privatization was a cheaper option than restructuring and recapitalization. The outcomes of bank privatization have varied across countries. For Argentina and Brazil, the evidence suggests that privatized bank performance improved post-privatization (Berger et al., 2005 for Argentina; Nakane and Weintraub, 2005 for Brazil). In stark contrast, the 1991 privatization program in Mexico failed in the mid-1990s with the onset of the Tequila crisis. The crisis revealed deep-seated problems in the banking sector, obscured by weak property rights and ineffective bank regulation, which failed to prevent imprudent behavior by newly privatized banks. Bank privatization failed to the tune of a bailout costing an estimated $65 billion (Haber, 2005). Yet, unlike in Argentina and Brazil, the 1991 Mexican program disbarred foreign banks from entering the auctions. Between February 1995 and December 1998, a post-Tequila second round of restructuring and privatization liberalized the treatment of foreign ownership of domestic banks. This facilitated a large-scale transfer of bank

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1170   Banking Systems Around the World ownership from domestic to foreign hands: foreign banks held 5 percent of banking sector assets in 1995 that leapt to 82 percent by 2003 (Haber, 2005); in 2013, foreign bank asset share stood at 70.1 percent (Claessens and Van Horen, 2015; see Table 37.1). In 2018, foreign banks owned two of the three largest banks in Mexico. One must be cautious when interpreting the apparent positive outcome of bank privatization. The observed post-privatization improvements in bank performance may reflect selection bias. To raise the viability of state-owned banks to prospective buyers, the authorities sanitized bank balance sheets and privatized healthy banks while funding bad banks using public funds (Clarke and Cull, 2000). On Argentina, Berger et al. (2005) report statistically significant differences in the balance-sheet structures of privatized and non-privatized state-banks. Brazil adopted similar transfers. The evidence indicates that utilization of the bad bank model did influence post-privatization bank performance. Bank privatization assisted foreign bank penetration in Latin America as foreign banks acquired large, domestic banks. Policymakers expected greater foreign bank entry to increase competition, leading in turn to efficiency gains and banking sector recapitalization. Foreign bank entry did increase banking sector capitalization in Mexico between 1997 and 2004 by more than $8.8 billion—equivalent to 42 percent of total banking sector capital in 2004 (Schulz, 2006). Country-level evidence suggests bank efficiencies improved at the same time as foreign bank penetration increased. Arguably, this is too general a claim since there are caveats to consider. First, one should distinguish between the performance of existing foreign banks and domestic banks acquired by foreign banks—mainly large banks purchased via cross-border bank M&A. We refer to the latter as foreign bank acquisitions. Second, it is difficult to disentangle the effects of foreign bank entry from other liberalization effects that could have affected bank efficiency. Finally, many studies use proxy measures of efficiency like the ratio of overhead costs-to-assets; there is limited evidence where econometric estimates of bank efficiency were employed (Berger, 2007). One exception finds inter-country differences in bank cost efficiencies with large banks more efficient than both very small and very large banks. Inefficient banks tended to be small, undercapitalized, relatively unprofitable, less risk averse, facing unstable deposit bases and intermediating less. Country-level factors positively relate to banklevel cost efficiencies: faster economic growth rates, a denser demand for banking services, and lower levels of market power (hence, more competitive) (Carvallo and Kasman, 2005). It is difficult to separate the effects of bank privatization and greater foreign participation on bank condition and performance. Earlier studies find little difference in the performances of private-owned domestic banks and foreign-owned banks, though the former did outperform state-owned banks (Crystal, Dages, and Goldberg, 2002). Average loan growth rates were higher at foreign banks compared to domestic banks (in Argentina, Chile, and Colombia), and loan growth stronger at existing foreign banks over acquired foreign banks. In explanation, management at foreign bank acquisitions

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Banking in Latin America   1171 focused on restructuring the former domestic banks and integrating operations with the parent (foreign) bank. This infers that foreign acquisitions adopt a defensive strategy toward market share and growth until the integration process is complete. The cautious nature of foreign bank strategies explains why foreign banks, and especially foreign bank acquisitions, achieve better loan quality than domestic banks, although stronger provisioning and higher loan recovery rates lead to weaker profitability at foreign banks. Foreign banks tend to be relatively liquid, rely less on deposit financing, and realize stronger loan growth during episodes of financial difficulty. The available evidence attributes the relatively superior efficiency in intermediation of foreign banks to their skills in evaluating credit risks and allocating resources at a faster pace than domestic-owned banks (Crystal, Dages, and Goldberg, 2002). Saez-Fernandez, Picazo-Tadeo, and BeltranEsteve (2015) compare the performances of domestic and foreign banks in Latin America and the Caribbean in 2001–13 to determine if efficiency differentials reflect differences in managerial ability and/or restrictions imposed using different technologies. Their evidence shows foreign banks employ superior technologies that realize higher levels of technical efficiency. In Argentina, foreign banks typically entered the market via cross-border M&A rather than de novo entry, and targeted larger and more profitable domestic banks. On average, loan quality, capitalization, and profitability were better at foreign banks than domestic (Clarke, Crivelli, and Cull, 2005). Berger et al. (2005) summarize the effects of governance changes on bank performance: state-owned banks underperform against both domestic and foreign banks due partly to poor loan quality associated with directed lending and subsidized credit. The privatization of provincial banks realized efficiency gains as the amount of non-performing loans fell and profit efficiencies increased. However, improvements in profit efficiency may simply reflect selection bias, since cost efficiencies exhibited little change before and after privatization. M&A activity involving domestic banks and foreign bank entry had little effect on bank performance (Berger et al., 2005). These findings do not apply to Brazil. Foreign banks in Brazil had difficulty in adapting to the peculiarities of the Brazilian banking sector and the dominance of private domestic banks (Paula, 2002). Incidentally, the empirical record is inconclusive on whether foreign banks are more efficient than domestic banks (Guimarães, 2002; Paula, 2002). One study finds foreign banks can realize a good (cost and profit) efficiency performance by either establishing new affiliates or acquiring domestic banks (Tecles and Tabak, 2010). Another study, however, shows state-owned banks to be significantly more cost efficient than both foreign and domestic-owned banks across 2000 to 2007, which confirms predications of the “home field advantage hypothesis” (Staub, Souza, and Tabak, 2010). This is unsurprising in the light of evidence that the operational characteristics and balance sheets of domestic and foreign banks are similar (Carvalho, 2002). Hence, the expected benefits of foreign bank entry have been slow to materialize in Brazil, because foreign banks witnessed and graduated toward operational characteristics similar to large private domestic banks (Paula and Alves, 2007).

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1172   Banking Systems Around the World

37.5.2  Market Concentration and Competition Effects The ongoing consolidation process increased concentration in banking sectors in Latin America. Whereas policymakers expected higher concentration to increase competition and realize bank efficiency gains, it was possible that powerful, larger banks could exploit their market power and not behave more competitively. This alternative scenario suggests that the evolution of highly concentrated market structures could retard the deepening of financial intermediation and the development of efficient banking sectors (Rojas Suarez, 2007). If a non-competitive market structure induces banks into oligopolistic behavior, the implication is that further consolidation could incentivize banks to exploit market power and not prioritize improving efficiency. It is an empirical matter to establish if bank consolidation (greater market concentration) raises competition and banking sector efficiency, or instead realizes heightened market power for banks. Some degree of market power can check if bank risk-­taking and tradeoffs exist between competition and financial stability. One difficulty when considering the relationship between consolidation and competitive ­conditions is how to measure competition. Studies commonly employ the H statistic, which is the sum of the elasticities of bank revenue with respect to input prices (Panzar and Rosse, 1987). Using this approach, banks in Latin America operate under monopolistic conditions, consistent with results from industrialized countries and other emerging markets. Some studies focus on the relationship between market concentration and bank efficiency (measured by parametric or non-parametric techniques) in Latin America in a test of the so-called “quiet life” hypothesis. It posits a negative relationship between bank efficiency and market power because greater concentration—due to M&A—leads banks to exploit market power and behave less competitively. In contrast, the “efficiency structure hypothesis” proposes that the expected relationship is positive (due, among other factors, to the possibility for large banks to exploit scale economies). Empirical evidence fails to support conjecture of the quiet life hypothesis in Latin American banking sectors; rather, bank restructuring promoted competition and yielded bank efficiency gains under conditions of monopolistic competition (Williams, 2012). Efficiency gains, especially scale efficiencies, positively and significantly affect bank profitability, thereby confirming predications of the efficiency structure hypothesis, most notably in Argentina, Brazil, and Chile (Chortareas, Garza-García, and Girardone, 2011). Evidence shows banks in Latin America are more cost efficient than they are profit efficient; that the bulk of inefficiency derives from the revenue side is indicative of a certain level of market power (Tabak, Fazio, and Cajueiro, 2011). Importantly, increases in consolidation did not weaken competitive conditions (Gelos and Roldós,  2004; Yeyati and Micco,  2007; Yildirim and Philippatos,  2007). Despite the general finding, some country-level features and some inconsistencies between studies are worth noting. For instance, banking sector competition has increased in Argentina and has remained constant in Mexico from the mid-1990s into the new millennium; competitive conditions in Brazil and Chile are reported to have changed little (Gelos and Roldós, 2004) or weakened (Yildirim and Philippatos, 2007).

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Banking in Latin America   1173 In general, the literature rejects the notion of collusion between banks; some evidence from Brazil suggests banks possess some degree of market power (Nakane,  2001; Nakane, Alencar, and Kanczuk, 2006). Other Brazilian evidence reveals complexities associated with the identification of competition effects. That Brazilian banking operates under conditions of monopolistic competition does not generalize across bank ownership and bank size. While small banks and state-owned banks operate under monopolistic conditions, large banks and foreign banks behave competitively. Belaisch (2003) contends such differences indicate markedly different competitive conditions in local markets and the national market. In local markets, private-owned banks are more pro-competitive than state-owned banks, although the latter enter markets which the former do not service (Coelho, de Mello, and Rezende, 2007). Small and large banks in Argentina and Chile also face different competitive conditions (Yildirim and Philippatos, 2007). Evidence from Colombia finds more competition reduces banks’ market power (Barajas, Steiner, and Salazar, 1998). Differently from Brazil and Colombia, evidence from Mexico suggests that efficiency gains may have translated into extraordinary profits for banks, being the result of a reduction in competitive rivalry in banking markets. Banks used a cross subsidization strategy, granting loans with very small margins and recuperating this loss by setting higher margins on deposits, which proved very profitable (Maudos and Solis,  2011). During the banking restructuring period (1993–2005), evidence attributes the high net interest margins to operating costs and market power (Maudos and Solis, 2009). The loss of social welfare attributable to the exercise of market power exceeds welfare gains emanating from improved cost and profit efficiencies. Furthermore, an inverse relationship exists between market power (in setting the price of loans) and cost efficiency (Solis and Maudos, 2008). Table 37.5 shows indicators of bank capitalization (bank capital-to-total assets), bank stability (Z score), profitability (ROE—return on equity), and leverage (ratio of assetsto-equity) for selected years between 2003 and 2015. At first sight, greater competition brought about by the changes in the banking industry in the 1990s has not weakened bank safety. Latin America banking sectors seem sufficiently capitalized with little evidence to suggest a shock to bank capital from the GFC. As of 2015, there is little variation in capitalization across Latin America, and capitalization has compared favorably with other emerging markets since 2007. The Z score indicator of bank stability is a product of bank profitability and leverage. Leverage has increased gradually between 2003 and 2015 in several countries and has fallen in some, with the largest reductions occurring between 2003 and 2007 (in Ecuador and Uruguay). Leverage in Latin America compares favorably with other emerging markets, such as, China, India, Russia, and South Africa as well as the UK in 2015. The strong performance in terms of capital helps to offset greater variation in bank profitability (ROE). Bank profitability generally improved between 2003 and 2007 before falling because of the crisis episode. What is worrying is that bank profitability has not rebounded between 2010 and 2015 although ROE exceeds 10 per cent in all countries except Ecuador. Relatively, profitability in Latin America compares favorably with developed and other emerging markets.

Capital-to-Assets

Z score

ROE

Leverage

Country

2003

2007

2010

2015

2003

2007

2010

2015

2003

2007

2010

2015

2003

2007

2010

2015

Argentina Bolivia Brazil Chile Colombia Ecuador Mexico Paraguay Peru Uruguay Venezuela

11.9 12.1 9.6 7.3 11.6 8.8 11.4 9.5 9.3 7.2 14.3

13.1 9.0 11.3 7.1 12.9 8.1 9.6 9.7 8.8 10.5 9.4

11.9 8.4 11.0 7.1 10.3 8.9 10.4 9.4 9.5 9.5 9.8

12.3 7.7 8.5 7.6 14.1 13.0 10.4 7.2 10.1 8.5 10.5

3.3 13.1 15.9 8.8 6.5 4.7 19.6 9.9 14.8 1.9 12.0

6.6 12.3 15.1 8.8 6.9 5.1 26.3 14.8 14.9 6.7 9.4

6.9 10.6 13.1 7.7 7.7 4.6 20.4 13.5 15.4 5.8 6.9

7.4 9.4 11.5 7.1 6.2 5.1 18.3 12.2 14.0 5.1 6.6

–32.5 2.7 19.5 17.5 19.8 14.6 13.6 –0.05 10.6 –28.5 36.0

11.5 22.8 27.6 23.5 20.6 19.9 18.0 26.6 28.1 30.2 19.0

25.1 17.0 17.4 22.1 16.8 13.4 13.1 29.8 23.7 6.7 14.5

21.8 13.2 13.1 14.1 12.4 7.4 11.5 19.2 20.2 10.8 46.7

9.0 8.4 9.6 11.0 9.6 23.1 9.2 9.3 9.7 16.5 6.9

8.8 10.5 10.4 11.7 8.8 13.9 7.2 8.2 10.3 10.6 7.5

9.2 11.6 10.9 12.8 7.7 9.8 8.8 9.6 9.7 9.3 9.8

8.8 12.8 12.1 12.8 8.9 9.2 9.5 9.5 10.4 10.9 13.5

China India Indonesia Russia South Africa Turkey UK US

3.8 5.7 10.4 14.6 8.0 13.7 6.6 9.2

5.7 6.4 9.2 13.3 8.0 12.8 5.5 10.3

6.1 7.1 10.7 12.9 7.0 12.3 5.4 12.7

8.4 7.2 13.6 8.9 7.0 11.0 6.8 11.7

18.7 7.4 3.8 8.7 21.8 7.5 18.0 23.6

28.3 8.4 4.1 6.8 12.4 9.3 6.1 24.6

25.5 9.7 4.5 6.3 13.0 9.4 6.5 26.7

28.6 9.1 5.2 4.3 13.9 7.2 9.8 27.7

18.3 20.7 21.1 13.0 0.7 25.1 10.8 14.9

18.9 16.5 16.7 15.7 25.5 26.6 19.7 8.6

18.8 15.7 20.9 3.9 14.4 19.4 –0.4 6.0

14.7 4.3 13.2 –1.7 15.1 9.4 3.5 9.3

25.1 20.0 11.9 5.3 6.1 11.8 9.3 10.8

14.9 16.2 9.9 7.5 17.1 9.0 28.0 9.8

17.0 14.3 9.5 8.4 15.1 8.2 24.4 9.0

14.3 13.8 7.8 27.6 16.4 9.4 15.7 8.8

Note: Data in italics are for the nearest year to that shown in the column. Source: World Bank, Global Financial Development Database.

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Table 37.5  Bank Capital, Stability, Profitability, and Leverage

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Banking in Latin America   1175

Table 37.6  Cost Structure and Efficiency Overhead Cost-to-Assets, %

Argentina Bolivia Brazil Chile Colombia Ecuador Mexico Paraguay Peru Uruguay Venezuela China India Indonesia Russia South Africa Turkey UK US

Cost-to-Income, %

2003

2007

2010

2015

2003

2007

2010

2015

4.2 6.0 6.1 3.0 7.2 7.8 4.5 27.5 4.5 9.6 8.5 1.4 2.4 3.2 4.5 11.5 5.7 2.9 3.3

4.9 5.8 5.5 2.5 5.8 6.6 5.0 9.4 4.6 6.8 4.6 1.2 2.2 3.5 6.6 3.2 3.6 1.1 2.9

6.2 4.8 4.1 3.1 4.9 5.7 3.7 8.6 4.3 5.1 3.9 0.9 1.9 3.7 80.0 3.1 2.8 0.5 2.8

5.7 4.2 3.1 2.2 3.3 5.0 3.6 16.0 3.4 22.6 5.2 1.2 2.1 3.2 2.5 2.9 2.1 1.7 2.5

92.6 75.0 62.2 54.8 66.5 75.2 62.0 95.0 66.1 87.4 56.7 43.2 48.7 52.8 54.4 71.7 60.5 64.1 56.3

66.6 69.6 56.4 46.9 56.5 68.0 52.2 70.4 50.4 59.9 56.1 36.3 50.6 53.2 63.0 54.9 43.1 57.3 61.6

59.5 68.0 54.6 47.9 54.2 71.2 51.9 69.3 47.0 72.8 64.0 36.3 45.0 48.0 98.7 57.9 43.1 56.3 58.2

92.1 78.5 81.8 56.7 66.5 79.9 68.0 86.5 53.8 96.9 53.5 49.0 64.8 58.2 67.1 100.7 61.0 118.0 72.5

Note: Data in italics are for the nearest year to that shown in the column. Source: World Bank, Global Financial Development Database.

The interval data show the most stable banking sectors, measured by the Z score, are in Mexico (18.3), Peru (14.0), Paraguay (12.2) and Brazil (11.5) in 2015. The data suggest that the maintenance of stability is due to a strengthening of bank capital positions. Nevertheless, the profitability of banking sectors in Latin America exceeds the industrialized countries where stability would also appear to reflect (supported) capital levels. One should read these data with some care, though. It is true that the 1990s and the 2000s witnessed a widespread effort at modernization of regulatory and supervisory methods and institutions everywhere in Latin America. Nevertheless, in part the data may be hiding one important source of fragility, that is, the dependence of the banking industry, at least in some of the largest economies, on the supply of credit to the government. Public debt securities tend to benefit from zero risk weighting (and thus do not require any capital to cover credit risk) adding one more incentive to banks to accumulate them, instead of private credit. As a result, in countries such as Argentina, Brazil, or Mexico, high capitalization may not necessarily translate into higher defenses against insolvency, but in fact, to higher dependency on Treasury policies. It is clear from the data that banking sectors across the region were appearing to have become more efficient over time by realizing lower cost–income ratios. However, data for 2015 signal possible problems in Uruguay (96.9 percent), Argentina (92.1 percent),

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1176   Banking Systems Around the World Paraguay (86.5 percent) and Brazil (81.8 percent) with each banking sector experiencing a sharp deterioration in efficiency between 2010 and 2015 (see Table 37.6). Examining the ratio of overhead cost-to-assets suggests the problem for Brazilian banks relates to income generation since overhead costs are among the lowest in the region. Argentina fits this pattern whereas worsening cost control is a concern for banks in Paraguay and Uruguay. In 2015, the cost and efficiency performance of banks in Latin America was inferior to banks in other emerging markets, which implies the regulatory authorities should take note. In the discussion so far, no attempt has been made to disentangle the impact of foreign bank entry on competition. A priori greater foreign bank penetration should increase competition, and offset potential growth in domestic bank market power resulting from higher concentration. Consistent with expectations, cross-country evidence ­suggests increased foreign bank penetration raises the level of competition (Yildirim and Philippatos, 2007). An alternative view claims increased concentration produces little effect on competition and financial stability; rather, foreign bank entry causes competitive conditions to weaken (Yeyati and Micco, 2007). Intuitively, foreign banks typically acquire domestic banks under duress and consequently operate with relatively high interest margins. For new foreign owners, the franchise value of high margins, and the time needed to transform the fortunes of their acquisitions, can explain why increased foreign bank penetration is associated with weaker, rather than stronger competition. While this possibility is inconsistent with policymakers’ objectives, the franchise value of high margins serves to discipline bank risk-taking because of fears of a dissipation of higher levels of bank profitability. In short, although foreign bank entry may weaken competition, it appears to exert a beneficial effect on banking sector stability (Yeyati and Micco, 2007). Foreign bank entry raises expectations of more competition that conditions how domestic banks behave, thereby constraining their market power (Claessens, DemirgüçKunt, and Huizinga, 2001). Evidence suggests this is the case in Latin America: greater foreign bank penetration lowered interest margins and profits at domestic banks (Yildirim and Philippatos, 2007). Individual country studies offer a rich interpretation of events. Evidence from Colombia suggests foreign bank and domestic bank behavior began to evolve differently following the announcement (in 1990) of impending financial liberalization policies (Barajas, Steiner, and Salazar, 2000). This study controlled for other liberalizing reforms that could affect bank behavior; for instance, differentiating foreign bank entry from entry of new domestic firms, and controlling for the opening of the capital account plus improvements made to bank regulation and supervision. Whereas foreign bank entry conditions domestic bank behavior by reducing excess intermediation spreads over marginal cost, the effect of new domestic entrants on behavior is greater and reduces non-financial costs and interest spreads. The Colombian evidence suggests that bank behavior reflects the degree of market power of banking groups; since foreign banks had relatively little market power they were more able to adapt to changes in competitive conditions (Barajas, Steiner, and Salazar, 2000). In Mexico, the lower administrative costs of foreign banks released downward pressure on administrative costs across all banks, which improved bank efficiency (Haber and

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Banking in Latin America   1177 Musacchio, 2005). Others, for example Schulz (2006), suggest a limited impact of foreign bank entry on bank efficiency because the low level of competitive intensity in the banking sector abated pressures for banks to improve operational efficiency. Evidence from Argentina and Brazil reports of no significant difference in the behavior of foreign and domestic banks with both types of bank reacting similarly to the macro-institutional environment (Paula and Alves, 2007).

37.5.3  Consolidation and the Allocation of Credit The governance changes resulting from bank privatization and foreign bank penetration raised concerns of possible adverse effects on the supply of bank credit. Three concerns found a voice: first, greater foreign bank penetration would affect the stability of bank lending; second, foreign bank entry and/or new private ownership of banks might lead to a reallocation of credit toward certain geographic or product market segments; and third, given the governance changes, would bank credit respond to market signals? Foreign bank penetration has raised foreign banks’ share of bank lending in Latin America. However, foreign bank lending is concentrated in specific market segments, mostly commercial loans markets (including government and interbank sectors) in Argentina, Colombia, and Mexico (Barajas, Steiner, and Salazar, 2000; Dages, Goldberg, and Kinney, 2002). In these countries, foreign banks limit their exposure to the household and mortgage sectors. In Chile, household credit has dominated foreign banks’ loan portfolio increasing from 18.4 percent to 27 percent of total foreign bank loans between 1990–9 and 2000–5 (Betancour, De Gregorio, and Jara, 2006). In Argentina and Brazil, foreign and domestic banks compete in loans markets and share loan portfolio characteristics (Dages, Goldberg, and Kinney, 2002; Paula and Alves, 2007). However, foreign banks in Argentina weight the loan portfolio toward relatively less risky loans (Dages, Goldberg, and Kinney, 2002), which is not the case in Brazil where there is no distinction between interest rates charged by foreign banks and domestic banks, hence the claims that variations in pricing occur within the foreign bank and domestic bank sectors rather than between the two (Carvalho, 2002). Interestingly, the negative impact of the GFC on foreign bank lending to Latin America was cushioned by the specific nature of foreign bank operations in the region. This is one of the reasons why the retrenchment of foreign bank credit to the region was significantly less severe in comparison to other emerging markets. Indeed, the expansion of foreign bank activities in Latin America in the 2000s has largely taken the form of increased domestic currency lending by their local affiliates rather than direct cross-border lending in foreign currencies from headquarters. Furthermore, local affiliates’ funding mostly comes from an expanding domestic deposit base rather than from parent banks or offshore wholesale markets; this feature provided a more stable source of funding during the GFC. Consequently, the resilience of domestic financial systems to external financial shocks has increased (Kamil and Rai, 2010).

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1178   Banking Systems Around the World The effect of bank ownership on credit growth in developing economies, before and after the GFC, explains variation in behaviors. While domestic private banks in both Eastern Europe and Latin America experienced a sharp contraction in lending during the crisis, notable differences in the behavior of foreign and state-owned banks were observed across the regions. In Eastern Europe, loan growth of foreign banks fell more than that of domestic private banks during the crisis, and state-owned banks did not act countercyclically. However, in Latin America state-owned bank-lending growth exceeded domestic private and foreign-owned banks (Cull and Martínez Pería, 2013). Foreign banks are an important source of finance for specific customer segments achieving higher loan growth (better quality and less volatile) than domestic banks (especially vis-à-vis state-owned banks) (Dages, Goldberg, and Kinney, 2002). Foreign banks—and private domestic banks—are responsive to market signals: in particular, lending is procyclical and sensitive to movements in GDP and interest rates, which is indicative of transactions-based activities. The finding of higher loan growth and lower volatility at foreign banks—even during crisis periods—underscores their role as important stabilizers of bank credit (Dages, Goldberg, and Kinney, 2002). After being granted unrestricted access in 1997, foreign banks came to dominate the Mexican banking sector quicker than they had done in other countries: in 1997, foreign banks supplied 11 percent of bank credit which grew to 83 percent in 2004 (Haber and Musacchio, 2005). During this time, a credit crunch occurred and private sector lending in real terms fell by 23 percent between December 1997 and December 2003 (Haber, 2005). On appearance, foreign bank penetration altered bank lending strategies, but this was not the case because the acquired banks had begun to reduce private lending before acquisition. Prior to the 1991 bank privatizations, the ratio of commercial bank loansto-GDP was 24 percent and rose to 26 percent in 1996; subsequently, it declined to 14 percent in 2003 (Haber, 2005). Furthermore, the behavior of foreign bank acquisitions, pre and post M&A, differed little from domestic banks. In brief, the credit crunch was driven by factors affecting all banks and was unrelated to foreign bank entry. In Argentina, bank privatization and foreign bank entry raised fears of a reallocation of bank lending. Initially, fears arose because the acquirers of privatized provincial banks tended to be small, wholesale banks based in Buenos Aires, which were expected to raise deposits in the provinces and allocate resources more in the Buenos Aires province (Clarke, Crivelli, and Cull, 2005). State-owned bank lending had been geographically diversified, though tending to concentrate more in the public sector with fewer manufacturing loans. Other concerns were that the volume of bank credit would decrease post privatization because the transfer of non-performing loans to bad banks meant the size of the privatized provincial banks was smaller than pre-privatization (Berger et al., 2005). Since foreign banks were located mostly in Buenos Aires and financed large-scale manufacturing and utilities firms in that province, commentators questioned foreign bank commitment to diversify lending to the provinces (Berger et al., 2005). Temporarily, privatization and foreign bank entry disrupted credit in the 1990s. Disruptions were most pronounced in provinces that had privatized banks; credit levels fell but quickly returned to pre-privatization levels once privatized banks increased in

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Banking in Latin America   1179 size. Privatization did not affect lending by private domestic or foreign banks. For foreign bank acquisitions, lending grew in importance and as a ratio of total assets, with loans growth allocated more toward consumers than manufacturing (Berger et al., 2005). Fears that foreign banks would concentrate their lending in Buenos Aires did not materialize. Foreign banks did enter provincial markets, and did so aggressively in provinces that had privatized their banks. In contrast, the newly privatized banks decreased lending relative to total assets to control risk by raising prudence (Berger et al., 2005). In summary, foreign bank penetration did lead to an increase in provincial lending because foreign banks offset changes in the lending of domestic banks (Clarke, Crivelli, and Cull, 2005).

37.5.4  Consolidation and Interest Rate Spreads Finally, we review the effects of foreign bank penetration and market concentration on the evolution of bank interest rate spreads and the process of financial intermediation. We determine the effects by comparing spreads charged by foreign banks and domestic banks with evidence coming from several countries (Argentina, Chile, Colombia, Mexico, and Peru). Foreign banks have operated with lower spreads compared with domestic banks (especially de novo foreign banks), but the main impact of foreign bank penetration has been the inducement for all banks to reduce costs rather than a marked decline in spreads. Concentration, on the other hand, could offset the apparent benefit of foreign bank penetration, since higher concentration could raise operational costs and thereby widen spreads, especially for domestic banks (Martínez Pería and Mody, 2004). The convergence of spreads continues to the present. Spreads are correlated more with loan rates than deposit rates (especially in Argentina and Peru) meaning that a shock that causes spreads to widen will raise lending rates rather than decrease deposit rates. While Brazilian spreads remain the highest in the region, nevertheless, the spread in 2015 was around 14 percentage points below the 2003 level. Oreiro and Paula (2010) report that spreads are particularly affected by risk variables (risk premia, interest rate volatility), output growth and the level of short-term interest rates. Whereas spreads in Paraguay (16.2 percent in 2015) and Peru (13.8 percent) exceed most other countries in the region, these spreads have fallen between 2010 and 2015. In Argentina, Chile, Mexico, and Venezuela, spreads are below 5 percent in 2015.

37.6 Regulatory Developments Post GFC Financial regulation had been in a process of modernization at least since the early 1990s in the most important Latin American economies, all of which had adhered to the Basel Agreement of 1988 and its additional guidelines. By 2008, when the crisis

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1180   Banking Systems Around the World became international, many of these countries were in the process of implementation of Basel II. Following the GFC, the Basel Committee on Banking Supervision was directed to increase their membership to include the G20 members, instead of the original G10. The same happened with the Financial Stability Forum, transformed into the Financial Stability Board. The widened membership of these entities now included the members of the G20 plus three Latin American countries: Argentina, Brazil, and Mexico. The three Latin American countries saw themselves as morally obligated to follow their decisions. Accordingly, they committed to implement Basel III, the set of toughened capital coefficients defined to deal not only with the risks already defined in Basel II and Basel 2.5, but also to comply with the new rules included in Basel III, such as the liquidity provisions and the leverage ratio. Thus, at least with respect to Argentina, Brazil, and Mexico, the effort to strengthen banking regulation that had contributed to make their banking systems more resilient against crises is to continue at the same pace (sometimes even more quickly) that is followed by developed economies. The Basel Committee (BCBS, 2013) reported in April 2013 that Mexico already put in place Basel III in what refers to capital rules, while Argentina and Brazil had already published the rules they were to adopt by the end of 2013. It is interesting to note that the report shows the three countries ahead of the United States and of the European Union in the speed of implementation of Basel III. The latest data on risk-weighted capital coefficients provided by the World Bank strengthen the notion that banks in Latin America suffered generally little from the GFC. Table 37.7 shows that banks from Latin America maintained capital-to-risk-weighted assets over 10 percent in 2015. The data are not particularly volatile and there is no visible break in the years around 2008. The resilience shown by banks in the region is a result of the success in maintaining overall macroeconomic stability in the face of adverse shocks coming mostly from the United States first, and then from Europe. However, it is also a measure of the success of these countries in modernizing their financial stability supervisory systems. Table 37.7 includes data on non-performing loans as a share of gross loans. A general picture emerges, namely an intertemporal improvement in asset quality since the early 2000s. The data suggest that the reform processes in Latin American countries, including bank privatization and foreign bank acquisitions, have arrested the formerly high proportions of non-performing loans and significantly reduced them in several countries to levels that are better than those found in other emerging market banking sectors. Nevertheless, and contrary to the trend, the subprime crisis adversely affected asset quality in 2008 and 2009, although Latin America appears less scathed compared with other regions. Indeed, Latin American banking sectors managed to shake off the impact of the crisis quicker than other emerging markets. The GFC did not make a marked impact on bank asset quality and the data suggests the hypothesis that loan management improved in the whole region in the period, either by bank managers or by bank supervisors or both. As a caveat, there is a mild deterioration in quality in some countries between 2010 and 2015. However, asset quality in banking sectors in Latin America is superior to other emerging markets in 2015.

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Banking in Latin America   1181

Table 37.7  Bank Solvency and Asset Quality Capital-to-Risk-Weighted Assets, %

Non-Performing Loans-to-Total Gross Loans, %

Country

2003

2007

2010

2015

2003

2007

2010

2015

Argentina Bolivia Brazil Chile Colombia Ecuador Mexico Paraguay Peru Uruguay Venezuela China India Indonesia Russia South Africa Turkey UK US

14.5 15.3 18.8 14.1 13.0 12.2 14.2 20.9 13.3 18.1 25.1 2.5 12.7 22.3 19.1 12.4 30.9 13.0 13.0

16.9 12.6 18.8 12.2 16.0 19.2 15.9 16.8 11.7 17.8 12.9 8.4 12.3 20.2 15.5 12.8 18.9 12.6 12.8

17.7 11.9 16.9 14.1 17.3 18.3 16.9 13.0 14.0 14.2 13.2 12.2 15.2 16.2 18.1 14.9 19.0 15.9 14.8

13.3 12.7 16.4 12.6 16.9 20.3 15.0 16.1 14.3 14.5 15.1 13.5 12.7 21.3 12.7 14.2 15.6 19.6 14.1

17.7 16.7 4.1 1.6 6.8 7.9 3.2 20.6 14.8 14.3 7.7 20.4 8.8 6.8 5.0 2.4 11.5 2.5 1.1

2.7 5.6 3.0 0.8 3.2 3.7 2.3 1.3 2.7 1.1 1.2 6.2 2.7 4.0 2.5 1.4 3.3 0.9 1.4

2.1 2.2 3.1 2.7 2.9 3.4 2.0 1.4 3.0 2.4 3.4 1.1 2.4 2.5 8.2 5.8 3.5 4.0 4.4

1.7 1.6 3.3 1.9 2.8 4.4 2.5 2.6 3.9 1.6 0.8 1.7 5.9 2.4 8.3 3.1 3.0 1.0 1.5

Note: Data in italics are for the nearest year to that shown in the column. Source: World Bank, Global Financial Development Database.

37.7  Latin American Development Banks: Some New Developments or an Impasse? Development banks were a common feature of Latin American economies during the Import-Substitution-Industrialization (ISI) period. They were believed to be a key instrument to guarantee that credit would be available for industrial investment at interest rates compatible with the risks involved in such activities. All the major Latin American economies created their own national development banks, particularly after the end of World War II. Other countries joined in efforts to create multinational institutions dedicated to finance investment, of which the Corporacion Andina de Fomento (CAF), created in 1970 and still in operation, is the most durable and best-known case. Nineteen countries own CAF—seventeen of Latin America and the Caribbean, and Spain and Portugal—as well as 13 private banks in the region. It aims at promoting a

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1182   Banking Systems Around the World sustainable development model through credit operations, non-reimbursable resources, and support in the technical and financial structuring of projects in the public and private sectors of Latin America. Development banks were deeply affected by the financial liberalization wave that swept the region in the 1980s and 1990s, under the context of the implementation of Washington Consensus policies. They disappeared from countries such as Argentina and Mexico. Some were transformed into financial agencies specialized in supporting specific sectors and activities like small to medium-sized enterprises (SMEs). Surviving institutions, such as, notably, the largest in the region, the National Economic and Social Development Bank (BNDES) in Brazil, had their mission redefined to operate as investment banks or as instruments to facilitate privatization processes in other sectors. Following the discontinuation of active industrial policies in the region, surviving development banks’ credit policies were reoriented to give support to the development of national private capital markets in the cases where this was possible. Development banks also survived in Colombia and Chile. The new millennium witnessed a dramatic change to Latin American politics. With the major exception of Mexico, governments in some of the most important countries in the area shifted to the political left. Brazil, Argentina, Venezuela, Uruguay, Bolivia, and Ecuador, all elected leaders arguing the need to change development standards, to accelerate industrial growth in tandem with income redistribution and to give new responsibilities for governments in the process. Even Chile, which was governed by a left-center coalition for most of the post-Pinochet period, moved, if slightly, to the left. There was not much in common among all these experiences besides the rhetoric of change. Lula da Silva’s administration in Brazil remained largely committed to the free market policies of his predecessor, just adding to it a wider social security intervention to improve the lives of the very poor. Chile and Uruguay remained moderate in their economic policy choices. Venezuela embarked on a policy, the viability of which depended directly on oil prices remaining high, with disastrous consequences. The change in the political scenario did not affect financial markets in Latin America. Financial liberalization and the privatization of state financial institutions did not proceed but neither were they rolled back. The general orientation to support the development and differentiation of local capital markets was maintained in the largest economies. Capital controls remained an instrument-of-last-resort to manage balance of payments problems, except, as it is well known, in the case of Argentina after the 2001 crash and, again, by the mid-2010s, and in Venezuela when economic disorganization was accentuated, after the death of Hugo Chavez. One institution that changed its ways in the period was Brazil’s BNDES. Timidly, at first, and more intensely in the aftermath of the 2008 international financial crisis, the bank’s loans were rapidly expanded as part of an overall state-institutions-led, creditexpansion strategy implemented in 2009 to reverse the contraction of the Brazilian economy. The bank’s balance sheet was expanded significantly by the growth of loans for working capital. After the emergency was successfully contained, with the economy recovering notably in 2010, a new emphasis was given to active industrial policies by the

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Banking in Latin America   1183 government, which maintained the momentum of BNDES’ expansion. Between 2012 and 2014, loan disbursement from BNDES ranged from $76 billion to nearly $85 billion. In comparison, loans from the InterAmerican Development Bank (IADB) ranged from just under $7 billion to $10.6 billion (Zeidan and Filho, 2017). The new industrial policy strategy centered on the notion of national champions, inspired by the experience of the East Asian economies who successfully transited from an underdevelopment position to the status of advanced economies. The bank was to concentrate its loans on those firms and sectors that had, or were judged capable of reaching, a strong position in international markets. The government was not supposed to choose the sectors to be favored, as much as to support the expansion of those businesses that were already successfully reaching international scale. Support was to take the form of making available loans at favored rates for expansion projects. The national champions’ policy was politically controversial since its inception. When Brazil was engulfed by a large-scale corruption scandal by the end of 2015, which is still unfolding, it was inevitable that directing favored loans to specific borrowers would be seen as highly suspect, hurting the public image of BNDES. No evidence whatsoever emerged that bank staff and its decision processes were vitiated in any way. The national champions’ policy was selected at higher levels of government. Nevertheless, in the overall climate of suspicion that was installed in the country, it was inevitable that the bank would pay a heavy price for its role as enforcer of a policy widely considered, at that point, to be corrupt. After these events, the bank’s role was dramatically downsized. Credits were curtailed, and part of its capital reserves were returned to the Treasury. Loan disbursements in 2015 and 2016 stood at $39.2 billion and $24.3 billion, respectively (Zeidan and Filho, 2017).6 Besides, its more important policy instruments, such as the charge of favored long-term interest rates for investment projects in which social returns surpassed private returns, were also affected, cutting the importance of financial subsidies to investment. The implications for the overall economy of Brazil (and, given the size of the country) for the region, should be obvious when one remembers that BNDES was responsible in recent years for about 10 percent of total investment in the country. There is no way to know how permanent such a policy shift is. Brazilian society has been living in turmoil since the corruption scandals and the political crisis began in 2015. The economy is in disarray, public finances are completely disorganized, the political system gives no sign of having the ability to steer the country out of this situation. Some recent downsizing of development banks, however, is observable in other cases, such as, Colombia and Chile, although the reduction pales in comparison to Brazil. In contrast,

6  In 2017, there was a new shift in BNDES’s strategy, with the change in its loans’ interest rate, from “long-term interest rate—TJLP,” fixed by the National Monetary Council of Brazil (according to its inflation target more a premium risk), to “long-term rate—TLP,” adjusted by the headline index of prices (IPCA) and more the real interest rate of the NTN (the Note of National Treasury, a federal public bond) of five years. The main objective of this change is to move the BNDES interest rate closer to private market interest rates and, consequently, to reduce its share in long-term financing in Brazil.

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1184   Banking Systems Around the World loan disbursements by the development bank in Peru have increased to $12.4 billion in 2016 (Zeidan and Filho, 2017). In sum, the BNDES story is impressive, given the sheer volume of resources it handled and its longevity (it was founded in 1952). The founding of new multilateral institutions reflects the rise of China; for instance, the Asian Infrastructure Investment Bank (AIIB), and the BRICS New Development Bank (NDB) controlled by some big emerging economies of the group led by China, but also including Brazil, India, Russia and South Africa. They illustrate an increasing importance given to multilateralism and, at the same time the importance given to the creation of new multilateral financial institutions, the governance of which is independent from the traditional powers, the US, Western Europe and Japan (see Baumann, 2017), that ultimately control even the old InterAmerican Development Bank (IADB). On the other hand, given the dire straits in which countries like Argentina, Brazil, and Venezuela find themselves, the idea of Banco del Sur, launched at the time of Lula da Silva in Brazil and Chavez in Venezuela, is as good as dead (if it was ever feasible). Nevertheless, new attention is also increasingly focusing on modernizing the functions of such institutions, national or multilateral, to cope with the extraordinary technical changes that have reshaped national economies as well as the relations between them. A new emphasis on innovation, flexible production processes and global integration demands deep changes in the modus operandi of existing institutions. Of course, naming objectives is incomparably easier than defining goals and methods to reach them but, increasingly, efforts are dedicated to the issue (de Olloqui, 2013).

37.8 Conclusion The last three decades have witnessed deep changes in the operation of the banking sector everywhere, but without a doubt, these changes have been particularly strong in Latin America. In these years, financial repression was eliminated or drastically attenuated from Mexico to the Southern Cone. The role of state-owned banks was streamlined either by privatization or by increasing specialization in the provision of financial support to special groups of borrowers, such as, medium and small firms, as in the case of Mexico. In a few countries, however, and most notably in Argentina and Brazil, a large sector of state-owned banks survived the financial liberalization process and went on to become leaders in their domestic banking sectors. A common feature of the financial liberalization process in the whole region has been the increasing presence of foreign banks in domestic markets. Led by US and Spanish banks, foreign institutions have aggressively taken advantage of the relaxation of restrictions on the operation of foreign banks in virtually the whole continent. Liberalization, privatization, and foreign bank entry combined with larger macroeconomic policy changes and strategies to generate a process of consolidation in the banking sector of all countries in the region. Consolidation was actively supported by local

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Banking in Latin America   1185 government policies aimed at taking advantage of possible economies of scale and scope in the production of banking services. Nevertheless, the results of these efforts are still to appear more clearly, although there is some evidence of efficiency improvements in bank operations in the region. In the major countries of Latin America, banks faced important difficulties in adapting to the new context of financial deregulation and liberalization. Serious banking sector crises took place in Chile, which pioneered the liberalization process, Argentina, also in the early stages of liberalization, and Mexico. In Brazil, banks suffered strong pressures resulting from the joint impact of deregulation and price stabilization processes in the mid-1990s, forcing the government to create a special crisis-resolution program. Argentina suffered another banking crisis in 2001, connected to the balance of payments crisis that put an end to the Convertibility Plan. Interest rates are currently marketdetermined everywhere except for Venezuela, where controls still subsist. Privatization advanced strongly everywhere, except in Brazil and Argentina, where the leading banks (Banco do Brasil and Caixa Economica Federal in Brazil, and Banco de la Nation Argentina, in Argentina) were kept in the hands of the federal government. Directed credit was reduced or eliminated across the region, again with the partial exception of Brazil, where a federal development bank (BNDES) had been the main provider of longterm credit, but since 2017 there has been a shift in the policy orientation of BNDES toward a more reduced and focused role in the economy. The results of the process have been relatively disappointing, given the high expectations that surrounded the liberalization process in the late 1980s. The jury is still out, of course, given the relatively short time during which these changes have been in place and the turbulence that characterized some periods in the 1990s. There is some evidence of improvement in many cases, but still not enough to generate enthusiasm. Banking crises and stresses, however, have not led to reversals in the financial liberalization process so far. On the contrary, most countries in the area have been investing in building regulatory and supervisory institutions while adhering to modern regulatory paradigms, such as the Basel accords. If the assumptions underlying the process of financial liberalization are in fact true, better results should begin to show in the short term in the form of lower cost of capital, wider access to finance, and better allocation of resources while, of course, maintaining a reasonable degree of financial stability. It is a tall order, but financial liberalization promises no less.

References Ahumada, A. and Marshall, J. (2001). “The Banking Industry in Chile: Competition, Consolidation and Systemic Stability,” BIS Papers No. 4, August. Avalos, M. and Trillo, F. (2006). “Competencia Bancaria en Mexico,” UN CEPAL, August. Barajas, A., Steiner, R., and Salazar, N. (1998). “Interest Spreads in Banking: Costs, Financial Taxation, Market Power, and Loan Quality in the Colombian Case 1974–96,” IMF Working Paper No. WP/98/110. Barajas, A., Steiner, R., and Salazar, N. (2000). “The Impact of Liberalization and Foreign Investment in Colombia’s Financial Sector,” Journal of Development Economics, 63, 157–96.

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1186   Banking Systems Around the World Baumann, R. (2017). “Os Novos Bancos de Desenvolvimento: Independencia Conflitiva ou Parcerias Estrategicas,” (The New Development Banks: Conflictual Independence or Strategic Partnerships), The Brazilian Journal of Political Economy, 37(2, April–June), 287–303. BCBS (Basel Committee on Banking Supervision) (2013). Report to G20 Finance Ministers and Central Bank Governors on Monitoring Implementation of Basel III Regulatory Reform, April. BCRA (Banco Central de la República Argentina) (2012). Financial Stability Report, October. Belaisch, A. (2003). “Do Brazilian Banks Compete?” IMF Working Paper No. WP/03/113. Berger, A.N. (2007). “International Comparisons of Bank Efficiency,” New York University Salomon Center, Financial Markets, Institutions and Instruments, 16(3), 119–44. Berger, A.N., Clarke, G.R.G., Cull, R., Klapper, L., and Udell, G.F. (2005). “Corporate Governance and Bank Performance: A Joint Analysis of the Static, Selection, and Dynamic Effects of Domestic, Foreign, and State Ownership,” Journal of Banking and Finance, 29, 2179–221. Betancour, C., De Gregorio, J., and Jara, A. (2006). “Improving the Banking System: The Chilean Experience,” BIS Papers No. 28, August. Birchwood, A., Brei, M., and Noel, D. (2017). “Interest Margins and Bank Regulation in Central America and the Caribbean,” Journal of Banking and Finance, 85, 56–68. BIS (2008). “Monetary and Financial Stability Implications of Capital Flows in Latin America and the Caribbean,” BIS Papers No. 43, November. Buch, C.M. and DeLong, G.L. (2001). “Cross-border Bank Mergers: What Lures the Rare Animal?” Kiel Institute of World Economics Working Paper No. 1070. Cardias Williams, F. and Williams, J. (2008). “Does Ownership Explain Bank M&A? The Case of Domestic Banks and Foreign Banks in Brazil,” in P. Arestis and L. F. Paula (eds.), Financial Liberalization and Economic Performance in Emerging Countries (Basingstoke: Palgrave Macmillan), 194–215. Carvalho, F.C. (1998). “The Real Stabilization Plan and the Banking Sector in Brazil,” Banca Nazionale del Lavoro Quarterly Review, 206, 291–36. Carvalho, F.C. (2000). “New Competitive Strategies of Foreign Banks in Large Emerging Economies: The Case of Brazil,” Banca Nazionale del Lavoro Quarterly Review, 213, 135–70. Carvalho, F.C. (2002). “The Recent Expansion of Foreign Banks in Brazil: First Results,” Latin American Business Review, 3(4), 93–119. Carvalho, F.C. (2008). “Financial Liberalization in Brazil and Argentina,” in P.  Arestis and L. F. Paula (eds.), Financial Liberalization and Economic Performance in Emerging Countries (Basingstoke: Palgrave Macmillan), 121–41. Carvallo, O. and Kasman, A. (2005). “Cost Efficiency in the Latin American and Caribbean Banking Systems,” Journal of International Financial Markets, Institutions and Money, 15, 55–72. CGFS (Committee on the Global Financial System) (2004). “Foreign Direct Investment in the Financial Sector of Emerging Market Economies,” Report Submitted by a Working Group Established by the CGFS, Basel, BIS, March. Chortareas, G., Garza-García, J.G., and Girardone, C. (2011). “Banking Sector Performance in Latin America: Market Power versus Efficiency,” Review of Development Economics, 15, 307–25. Chortareas, G., Garza-García, J.G., and Girardone, C. (2012). “Competition, Efficiency and Interest Rate Margins in Latin American Banking,” International Review of Financial Analysis, 24, 93–103. Claessens, S. and Van Horen, N. (2014). “Foreign Banks: Trends and Impact,” Journal of Money, Credit and Banking, 46(1), 295–326.

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Banking in Latin America   1187 Claessens, S. and Van Horen, N. (2015). “The Impact of the Global Financial Crisis on Banking Globalization,” IMF Economic Review, 63(4), 868–918. Claessens, S., Demirgüç-Kunt, A., and Huizinga, H. (2001). “How Does Foreign Bank Entry Affect Domestic Banking Markets?” Journal of Banking and Finance, 25, 891–911. Clarke, G.R.G. and Cull, R. (2000). “Why Privatize? The Case of Argentina’s Public Provincial Banks,” World Development, 27, 865–86. Clarke, G.R.G., Crivelli, J.M., and Cull, R. (2005). “The Direct and Indirect Impact of Bank Privatization and Foreign Entry on Access to Credit in Argentina’s Provinces,” Journal of Banking and Finance, 29, 5–29. Coelho, C.A., de Mello, J.M.P., and Rezende, L. (2007). “Are Public Banks Pro-competitive?” Evidence from Concentrated Local Markets in Brazil, PUC-RJ Texto para Discussão No. 551. Crystal, J.S., Dages, B.G., and Goldberg, L. (2002). “Has Foreign Bank Entry Led to Sounder Banks in Latin America?” Current Issues in Economics and Finance, 8(1), 1–6. Cull, R. and Martínez Pería, M.S. (2013). “Bank Ownership and Lending Patterns During the 2008–2009 Financial Crisis: Evidence from Latin America and Eastern Europe,” Journal of Banking and Finance, 37, 4861–78. Dages, B.G., Goldberg, L., and Kinney, D. (2002). “Foreign and Domestic Bank Participation in Emerging Markets: Lessons from Mexico and Argentina,” FRBNY Economic Policy Review, September, 17–36. De la Torre, A. (2000). “Resolving Bank Failures in Argentina: Recent Developments and Issues,” World Bank Policy Research Working Paper Series No. 2295. de Olloqui, F. (ed.) (2013). Public Development Banks: Toward a New Paradigm? (Washington, DC: Interamerican Development Bank). De Vries, M.G. (1987). Balance of Payments Adjustment, 1945 to 1986: The IMF Experience (Washington, DC: IMF). Domanski, D. (2005). “Foreign Banks in Emerging Market Economies: Changing Players, Changing Issues,” BIS Quarterly Review, December, 69–81. ECLatin AmericaC (Economic Commission for Latin American and Caribbean) (2000). Foreign Investment in Latin America and the Caribbean—1999 Report (Santiago: ECLatin AmericaC). Fanelli, J.M. (2003). Estrategias para la Reconstrucción Monetaria y Financiera de la Argentina (Buenos Aires: Siglo XXI). Focarelli, D. and Pozzolo, A.F. (2001). “The Patterns of Cross-Border Bank Mergers and Shareholdings in OECD Countries,” Journal of Banking and Finance, 25, 2305–37. Foxley, A. (1983). Latin American Experiments with Neo-Conservative Economics (Berkeley, CA: University of California Press). Fry, M. (1995). Money, Interest, and Banking in Economic Development, 2nd edn (Baltimore, MD: The Johns Hopkins University Press). Gelos, R.G. (2006). “Banking Spreads in Latin America,” IMF Working Paper No. WP06/44. Gelos, R.G. and Roldós, J. (2004). “Consolidation and Market Structure in Emerging Market Banking Systems,” Emerging Markets Review, 5, 39–59. Gerschenkron, A. (1962). Economic Backwardness in Historical Perspective (Cambridge, MA: The Belknap Press of Harvard University Press). Guimarães, P. (2002). “How Does Foreign Entry Affect Domestic Banking Market? The Brazilian Case,” Latin American Business Review, 3(4), 121–40. Haber, S. (2005). “Mexico’s Experiments with Bank Privatization and Liberalization, 1991–2003,” Journal of Banking and Finance, 29, 2325–53.

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1188   Banking Systems Around the World Haber, S. and Musacchio, A. (2005). “Foreign Banks and the Mexican Economy, 1997–2004,” Stanford Center for International Development Working Paper. Hawkins, J. and Mihaljek, D. (2001). “The Banking Industry in the Emerging Markets Economies: Competition, Consolidation and Systemic Stability,” BIS Papers No. 4, August. Hernandez-Murillo, R. (2007). “Experiments in Financial Liberalization: The Mexican Banking Sector,” Federal Reserve Bank of St Louis Review, 89(5), 415–32. Honohan, P. (2007). “Cross-Country Variation in Household Access to Financial Services,” Paper Prepared for World Bank Conference on Access to Finance, March 15–16. IADB (Inter-American Development Bank) (2005). Unlocking Credit: The Quest for Deep and Stable Bank Lending (Washington, DC: IADB). IMF (International Monetary Fund) (2007). Global Financial Stability Report (Washington, DC: IMF). IMF (2016). “Financial Integration in Latin America,” IMF Policy Papers, March. Jeanneau, S. (2007). “Banking Systems: Characteristics and Structural Changes,” BIS Papers No. 33, 3–16, February. Kamil, H. and Rai, K. (2010). “The Global Credit Crunch and Foreign Banks’ Lending to Emerging Markets: Why Did Latin American Fare Better?” IMF Working Paper No. WP/10/ 102, April. Martínez Pería, M.S. and Mody, A. (2004). “How Foreign Participation and Market Concentration Impact Bank Spreads: Evidence from Latin America,” Journal of Money, Credit and Banking, 36(3), 511–37. Maudos, J. and Solis, L. (2009). “The Determinants of Net Interest Income in the Mexican Banking System: An Integrated Model,” Journal of Banking and Finance, 33, 1920–31. Maudos, J. and Solis, L. (2011). “Deregulation, Liberalization and Consolidation of the Mexican Banking System: Effects on Competition,” Journal of International Money and Finance, 302, 337–53. Nakane, M.I. (2001). “A Test of Competition in Brazilian Banking,” Banco Central do Brasil Working Paper Series No. 12. Nakane, M.I. and Weintraub, D.B. (2005). “Bank Privatization and Productivity: Evidence for Brazil,” Journal of Banking and Finance, 29, 2259–89. Nakane, M.I., Alencar, L.S., and Kanczuk, F. (2006). “Demand for Bank Services and Market Power in Brazilian Banking,” Banco Central do Brasil Working Paper Series No. 107, June. O’Connell, A. (2005). “The Recent Crisis—and Recovery—of the Argentine Economy: Some Elements and Background,” in G. Epstein (ed.), Financialization and the World Economy (Cheltenham: Edward Elgar). Oreiro, J.L. and Paula, L.F. (2010). “Macroeconomic Determinants of Bank Spread in Latin America: A Recent Analysis with Special Focus on Brazil,” International Review of Applied Economics, 24(5), 573–90. Panzar, J.C. and Rosse, J.N. (1987). “Testing for Monopoly Equilibrium,” Journal of Industrial Economics, 35, 443–56. Paula, L.F. (2002). “Expansion Strategies of European Banks to Brazil and Their Impacts on the Brazilian Banking Sector,” Latin American Business Review, 3(4), 59–91. Paula, L.F. (2011). Financial Liberalization and Economic Performance: Brazil at the Crossroads (London and New York: Routledge). Paula, L.F. and Alves, Jr., A.J. (2007). “The Determinants and Effects of Foreign Bank Entry in Argentina and Brazil: A Comparative Analysis,” Investigación Económica, 66(259), 63–102.

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Banking in Latin America   1189 Ray, R. (2018). “China–Latin America Economic Bulletin 2018 Edition,” Global Development Policy Center Discussion Paper, 2018–1. Rojas Suarez, L. (2007). “The Provision of Banking Services in Latin America: Obstacles and Recommendations,” Center for Global Development Working Paper No. 124, June. Saez-Fernandez, F.J., Picazo-Tadeo, A., and Beltran-Esteve, M. (2015). “Assessing the Performance of the Latin American and Caribbean Banking Industry: Are Domestic and Foreign Banks So Different?” Cogent Economics & Finance, 3, 1–17. Schulz, H. (2006). Foreign Banks in Mexico: New Conquistadors or Agents of Change? (Philadelphia: PA: University of Pennsylvania). Sebastián, M. and Hernansanz, C. (2000). “The Spanish Banks Strategy in Latin America,” SUERF Working Paper No. 9. Singh, A., Belaisch, A., Collyns, C., de Masi, P., Krieger, R., Meredith, G., and Rennhack, R. (2005). “Stabilization and Reform in Latin America: A Macroeconomic Perspective on the Experience Since the Early 1990s,” IMF Occasional Paper No. 238. Solis, L. and Maudos, J. (2008). “The Social Costs of Bank Market Power: Evidence from Mexico,” Journal of Comparative Economics, 36, 467–88. Stallings, B. and Studart, R. (2006). Finance for Development: Latin America in Comparative Perspective (Washington, DC: The Brookings Institution). Staub, R., Souza, G.S., and Tabak, B. (2010). “Evolution of Bank Efficiency in Brazil: A DEA Approach,” European Journal of Operational Research, 202, 204–13. Studart, R. and Hermann, J. (n.d.). “Sistemas Financeiros Argentino e Brasileiro,” manuscript. Tabak, B.M., Fazio, D.M., and Cajueiro, D.O. (2011). “Profit, Cost and Scale Efficiency for Latin American Banks: Concentration–Performance Relationship,” Banco Central do Brasil Working Paper Series No. 244, May. Tecles, P. and Tabak, B. (2010). “Determinants of Bank Efficiency: The Case of Brazil,” Banco Central do Brasil Working Paper Series No. 210, May. Williams, J. (2012). “Efficiency and Market Power in Latin American Banking,” Journal of Financial Stability, 8, 263–76. Yeyati, E.L. and Micco, A. (2007). “Concentration and Foreign Penetration in Latin American Banking Sectors: Impact on Competition and Risk,” Journal of Banking and Finance, 31, 1633–47. Yildirim, H.S. and Philippatos, G.C. (2007). “Restructuring, Consolidation and Competition in Latin American Banking Markets,” Journal of Banking and Finance, 31, 629–39. Zeidan, R. and Filho, I.E.C. (2017). “Can Latin America’s Development Banks Be Fixed?” Americas Quarterly, available at: http://www.americasquarterly.org/content/can-latinamericas-development-banks-be-fixed.

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chapter 38

Ba n k i ng i n Austr a li a  a n d N ew Ze a l a n d — Geogr a phic Prox im it y, M a r k et Concen tr ation, a n d Ba n k i ng I n tegr ation Fariborz Moshirian and Eliza Wu

38.1 Introduction This chapter focuses on Australia’s and New Zealand’s banking systems, which are not only geographically proximate and very similar in market structure but strikingly also highly integrated in the provision of financial services across the Oceania region. We examine their combined economic importance, composition, strong performance, resilience, and some of their defining characteristics and regulatory reforms. There are a number of reasons why an analysis of the banking industry in these two largest countries in the Oceania region may be of particular interest. First and most important of all, these banking industries were unique in remaining relatively unscathed by the Great Recession, which started in 2008, when global banks around the world were suffering significant financial losses. Second, the high degree of geographical proximity and banking integration across the Tasman Sea between the two economies of Australia and New Zealand offer interesting perspectives on the benefits and potential costs of having jointly integrated and concentrated banking sectors in small open economies. Third, Australia and New Zealand were the last two countries in the group of Organisation for Economic and Cooperation Development (OECD) members to be without any form of explicit depositor protection or guarantees of bank liabilities prior to the 2008 Great

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Banking in Australia and New Zealand   1191 Recession, so this provides a unique case on the effectiveness of implementing financial safety nets in times of financial turmoil. This chapter is organized as follows. In this section, we provide an overview of the size and significance of the Australian and New Zealand banking Industry. In section 38.2, we discuss the degree of competition in the industry. Sections 38.3 and 38.4 examine the breakdown of the main sources and uses of funds for Australian and NZ banks. Section 38.5 discusses the performance of the banking industry. Section 38.6 discusses the level of government support for the banking sector and section 38.7 highlights the recent regulatory reforms before conclusions are offered.

38.2  Size and Significance of the Australian and NZ Banking Industries The significance and importance of the Australian and NZ banking industries to the operation of their respective financial system and economy cannot be overstated. Authorised Deposit-taking Institutions (ADIs) in Australia collectively hold around 55 percent of the total assets of Australian financial institutions (as at the September quarter 2017) and, hence, constitute the largest part of the Australian financial system. The total value of banking assets held stands at 147 percent of GDP in NZ and 136 percent in Australia (see Table 38.1). This ratio is very high in both Australia and NZ by global standards (with the world average being 55 percent) indicating that the banking systems in Australia and NZ are highly developed and account for a significant portion of national wealth in the two countries. It should also be noted that the proportion of bank asset holdings relative to GDP in Australia and NZ rivals those in both the UK (135 percent) and Japan (166 percent). Moreover, in Australia the financial services industry (which includes ADIs) is highly productive and contributed 9.3 percent to gross domestic product in the aggregate economy, according to the most recent annual data provided by the OECD up to 2017. This can be compared to an OECD average of 5.8 percent for financial service industries in developed countries. This level of contribution by the financial sector in the Australian economy is striking as it exceeds even the contributions made by the financial service sectors in the largest financial centers in the world, like those in the UK (7.1 percent), the US (7.6 percent) and the Eurozone (4.5 percent). In NZ, by contrast, the financial services industry contributed 6.3 percent to its GDP. While the financial services sector is relatively less important in NZ than in Australia and other comparable economies like the US and the UK, it still exceeded the value-added contribution by other primary industries such as Agriculture, Fisheries and Forestry.1

1  Information sourced from: http://archive.stats.govt.nz/browse_for_stats/economic_indicators/ NationalAccounts/Contribution-to-gdp.aspx.

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1192   Banking Systems Around the World

Table 38.1  Size and Importance of the Financial Services Industry in Australia and New Zealand

Total Bank Assets* as % of GDP(b) Value Added Activity(c)**

NZ

AUS(a)

US

UK

Japan

Eurozone

World

147% 6.3%

136% 9.3%

60.2% 7.6%

135% 7.1%

166% 4.2%

103% 4.5%

55% 5.8%***

*Depository institutions only. **Financial services contribution to national GDP. ***Figure only based on OECD countries. Note: (a) The Big Four Banks also comprise 44 percent of the total market capitalization of the ASX200 stock index. Sources: (b) https://fred.stlouisfed.org. (c) https://data.oecd.org/natincome/value-added-byactivity.htm.

The importance of the banking industry in both Australia and NZ becomes even more apparent when we analyze the size of the customer base. In Australia, there are approximately 20 million people over the age of 15. The top four major banks in Australia and NZ are the Commonwealth Bank of Australia (CBA), Westpac Banking Corporation (Westpac), the National Australia Bank (NAB) and Australia and New Zealand Banking Group (ANZ). The Commonwealth Bank and Westpac have customers within that demographic (persons over 15 years of age) totaling 17 and 15 million people, or 85 percent and 75 percent of the population, respectively.2 Although a proportion of their customers are international, these figures nonetheless demonstrate how far-reaching the banking industry is within the broader Australian society in providing financial services for individuals, corporations, and the government sector. Banks provide a wide range of financial products and services to Australian financial consumers and businesses, and cross-selling of wealth management, insurance, and loan products has become widespread within the banking industry. Bank lending is a key source of external financing for small to medium-sized enterprises (SMEs) and agricultural businesses in both Australia and NZ.

38.3  Market Competition The Australian and NZ banking industry is not only highly concentrated but also significantly interconnected. However, the high degree of concentration in the Australian and NZ banking systems are not isolated on the global scale. Both Australia and NZ have the same few large banks operating with significant market power. Within the Australian and NZ banking industry, the aforementioned largest four banks (the Big Four) 2  Information sourced from: https://financialservices.royalcommission.gov.au.

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Banking in Australia and New Zealand   1193

Table 38.2  Overall Industry Concentration and Sectoral Concentration Overall Industry Concentration AUS Big Four

Other Domestic Banks

Other (Foreign)

79% 86%

11% 8%

10% 6%

Loan Volume in AUS(a) Loan Volume in NZ(b),*, ** Sectoral Concentration Loan Sector Concentration by Market Share

AUS Big Four

Other Domestic ADIs

Foreign ADIs

Personal Government NFCs FCs Housing: Owner-occupied Housing: Investment

81.4% 63.5% 72.1% 76% 80.9% 85.5%

11.5% 0.3% 6.2% 3.4% 11.7% 11.4%

7.1% 36.2% 21.7% 20.6% 7.4% 3.2%

* Consistent with the metric used by the RBA and incorporates loans and advances on DI’s books. **In NZ, we aggregate across ANZ, Westpac, ASB (owned by CBA), BNZ (owned by NAB). Sources: (a) http://www.apra.gov.au. (b) https://www.rbnz.govt.nz/financial-stability/ overview-of-the-new-zealand-financial-system/the-banking-system.

comprise 79 percent3 in Australia and 86 percent in NZ of total loan volumes, respectively (see Table 38.2). The Australian Big Four banks also hold around three-quarters of all assets held by Australian ADIs. This is one of the highest concentrations of banking market power within a developed banking system—it is more than twice the banking concentration in the United States and the United Kingdom. However, it is on a par with other smaller advanced economies such as Canada (85 percent) and Sweden (82 percent), which also have similar degrees of banking sector concentration. Other domestic banks, foreign branch banks and credit unions and building societies (mutuals) account for a small proportion of the total assets within the banking sector. There is significant unidirectional banking integration across the two geographically proximate banking industries with the Australian Big Four dominating also the NZ banking industry, with only a meager 8 percent of total loans extended by domestic NZ banks and cooperatives and another 6 percent of the total loans contributed by foreign banks. In contrast, NZ banks have very little presence in the larger Australian banking industry. Both the Australian and New Zealand banking systems are dominated by large Australian banks—the Big Four banks from Australia dominate retail banking, and most of these same institutions also feature prominently in the provision of funds and 3 Sourced from: https://financialservices.royalcommission.gov.au/publications/Documents/somefeatures-of-the-australian-banking-industry-background-paper-1.pdf.

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1194   Banking Systems Around the World wealth management as well as general insurance. Over time, there has also been ­significant consolidation among the largest banks and the formation of large financial conglomerates, which have become increasingly more dominant, posing challenges for financial stability with the loss of diversification potential across financial services. A declining number of smaller banks operate alongside these major financial institutions. Australia’s smaller financial institutions (such as some regional and customerowned banks (mutuals) and foreign-owned banks) achieve comparatively high market shares in targeted markets—for example, consumers in their home state, employees in a particular profession, or dual nationals from their base country. Focusing on such groups allows these smaller players to overcome the disadvantages of potentially limited scale, higher funding costs, or in the case of foreign-owned banks, limited public-facing branches within the Australian and NZ banking scene. The Productivity Commission (2018) in Australia reports that the banking industry is an “established oligopoly with a tail of smaller providers.” Their assessment is that “Price competition in the banking system is limited. Although institutions claim that they compete in loan markets by discounting, such behaviour is not indicative of a competitive market when price obfuscation is common and discounts are specific to groups of customers” (Productivity Commission,  2018, p. 38). Furthermore, the Commission’s view is that the smaller banks and non-bank financial institutions “are not a significant competitive constraint on the major banks’ market power” (ibid.). Heard, Menezes, and Rambaldi (2017) examined the locational decisions made by the four largest Australian banks with regards to where they established or maintained branch- and automated teller machine (ATM)-level presence within the domestic banking sector between 2002 and 2013. Their findings reveal important evidence on banking competition in Australia. Their analysis suggests that there is much persistence in banks’ locational choices as past presence is the most important factor for explaining current presence. Moreover, they find that the four largest banks tend to co-locate branches but the location of other (smaller) banks generally differs from the location of the four largest banks, suggesting that the smaller banks strategically do not compete directly with the four largest banks. The authors highlight that there has been limited competition between large banks and smaller banks within the Australian banking market, both before and after the 2007–8 Global Financial Crisis. Given the historical developments and market structure of the Australian and NZ banking industries, the high degree of concentration has climbed steadily over time but a unique policy exists called the “Four Pillars Policy” that prevents the top four banks from amalgamating within Australia. In both countries, the degree of market concentration within the banking system tends to be pro-cyclical. This means that in times when the economy is in an upturn, the excess credit growth that follows is produced at a greater rate by the few major banks. Paralleled with this expansion in credit growth is an increase in the top four banks’ collective market share. The Australian housing sector, for example—which has seen staggering house price growth of over 100 percent (particularly in Sydney and Melbourne) since the Great Recession—is experiencing a credit bubble dominated by the country’s major banks. In NZ, there has also developed a

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Banking in Australia and New Zealand   1195 ­ ousing price bubble. Total bank credit extended by the Big Four banks in Australia now h account for the bulk of all housing loans (80.9 percent in the owner-occupied segment and 85.5 percent of the loan volumes in the investment segment). Similarly, most of the personal loans (81.4 percent) taken out in Australia are also provided by the Big Four banks. The remaining loans are provided by other domestic deposit-taking institutions and foreign banks. The Big Four banks are also dominant in government loans, financing approximately two-thirds of all government borrowing needs with the other third ­coming from foreign banks. The high degree of bank market power in the Australian and NZ banking industries has allowed Australasian financial institutions to be increasingly more efficient. Over the past decade, the number of ADIs has decreased from 217 (as at the end of the September quarter 2007) to 147 (as at the end of the September quarter 2017), a decline of almost a third of the ADIs that previously existed. This drastic decline in the number of ADIs has occurred due to the decline and changing operations of credit unions, building societies (mutuals) and regional banks that were previously specialized and dominant within their respective Australian states. A consolidation of the banking sector has also occurred over time with the four major banks acquiring significant regional banks to gain rapid increases in market share in order to improve their competitiveness through achieving greater economies of scale. The Four Pillars Policy only prevents the top four major banks from acquiring each other but not the smaller competitors. For instance, in 2008 the Commonwealth Bank of Australia acquired BankWest, which was focused in Western Australia, while Westpac Bank acquired St George Bank, based in New South Wales. The significant degree of concentration in the banking sector may pose increasing fragility in the banking system. However, the findings of Delis, Kokas, and Ongena (2017) highlight that bank market power can also be beneficial as it allows firms that would otherwise not get access to bank credit (the SMEs and riskier firms within a country) to borrow from banks with greater market power and capacity to achieve loan portfolio diversification. Delis, Kokas, and Ongena (2017) posit that banks with more market power also have superior screening and monitoring ability, which helps to enhance the performance of the firms that receive bank credit. Hence, having a few banks with significant market power allows a larger number of smaller and/or riskier business enterprises with good investment ideas to be financed, which improves their performance and is ultimately beneficial for the real economy.

38.4  Balance Sheets—Sources of Funding One of the most striking differences between the Australian and NZ banking industries from their global counterparts is the low percentage of funding sourced from deposits (see Table 38.3). Deposit accounts in Australia and NZ currently comprise 60 percent

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1196   Banking Systems Around the World

Table 38.3  Bank Funding Sources in Australia and New Zealand, and Globally Bank Funding Sources in Australia and New Zealand

AUS(a) NZ(b)

Demand Deposits

Short-Term Debt

Long-Term Debt

Equity

60% 61%

20% 8%*

12% 22%

8% 8%**

Bank Funding Sources Globally (c) Region Eurozone Japan UK US

Consumer Deposit Ratio

Wholesale Funding Ratio

41% 72% 59% 73%

23% 21% 24% 13%

*Short-term debt included any liabilities classified as a derivative instrument. **Equity includes common and preference shares and retained earnings less reserves. Sources: (a) https://www.rba.gov.au/chart-pack. (b) https://www.rbnz.govt.nz/ statistics/s10-banks-balance-sheet. (c) https://www.rba.gov.au/publications/fsr/2012/ sep/pdf/0912.pdf.

and 61 percent of their respective banks’ funding composition. This level is relatively low when compared to other banking industries internationally, such as those in the US (73 percent) and Japan (72 percent). Australian and NZ banks are more similar to UK banks in their funding structures. This is possibly due to the lack of an explicit deposit insurance scheme being in place prior to the 2007–8 Global Financial Crisis, unlike the established formal arrangements for deposit insurance funds in countries like Japan and the US. In contrast, Australian and NZ banks operated under an implicit arrangement with depositor preference whereby, in the event of a bank failure, depositors would be given priority to claim their losses over other debt holders wherever possible. As a consequence of not having any explicit financial safety nets in place, there is a greater reliance on market-based wholesale funding alternatives, such as the listing of certificates of deposit (CDs) in the money market and offshore funding markets (via both shortand long-term debt issuance), an avenue employed greatly by the major Australian banks as local funding markets are relatively small and the pool of funds available is typically more expensive compared to that available internationally due to limited diversification opportunities for local fund providers.4 For this reason, traditionally both Australian and NZ banks have been heavily reliant on external debt funding by international standards. Total wholesale debt funding constitutes 32 and 30 percent of all funding sources for Australian and NZ banks, respectively, while the use of wholesale 4  Information sourced from: https://www.rba.gov.au; https://financialservices.royalcommission.gov.au/ publications/Documents/some-features-of-the-australian-banking-industry-background-paper-1.pdf.

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Banking in Australia and New Zealand   1197 debt funding is much more limited in countries like the US (13 percent), Japan (21 percent), the UK (24 percent), and across most of Europe (23 percent). However, while Australian banks resort more to short-term debt funding (that contributes 20 percent of their total funding as opposed to only 8 percent in NZ), NZ banks utilize more longer-term debt funding (with this funding source contributing 22 percent to their total funding compared with 12 percent for Australian banks). This arguably exposes Australian banks to a greater re-pricing risk than for their NZ counterparts, which tend to be relatively more conservative in their risk management practices and business models employed. There is also a myriad of structural (and statistical) factors behind this discrepancy in funding composition across different economies. Demand for credit by Australian households in the mid-2000s increased concurrently with a decline in the level of savings within the economy, causing deposit growth to flatten and even decline. This was the result of an increasing lending volume in real-estate loans which was accompanied by gradual shifts in asset allocation by households—a trend sparked a decade prior with the introduction of compulsory superannuation5—and saw households store a smaller proportion of their wealth in financial assets, such as deposit accounts with banks.6 Consequently, in the years running up to the 2007–8 GFC, banks’ deposit growth could not match the growth in household credit. Australian banking institutions sought to account for the differential in the supply of funds through wholesale funding markets via foreign debt security issuance. Other factors explaining the historically low intake of deposit funding in Australia’s and NZ’s banking industry include the size and structure of the industry as well as statistical differences in the classification and measurement of certain deposits held at banks (see Stewart, Robertson, and Heath, 2013; Gertler, Kiyotaki, and Prestipino, 2016).

38.5  Balance Sheets—Uses of Funding 38.5.1  Asset Composition of Banks in Australia and NZ and Globally Domestic Australian and NZ authorized deposit-taking institutions are heavily concentrated in housing loans (residential mortgage lending) by global standards.7 In Australia, 5  It is important to note however that the shift in preferences was counteracted to an extent by the asset allocation of Australian superannuation companies (pension funds). A high percentage of their portfolios are allocated to deposit accounts. 6  Information sourced from: https://www.rba.gov.au/publications/rdp/2013/pdf/rdp2013-15.pdf. 7  Data on asset composition for Australian ADIs is sourced from: http://www.apra.gov.au/­publications/ quarterly-authorised-deposit-taking-institution-property-exposures; NZ ADIs is sourced from: https:// www.rbnz.govt.nz/statistics/s10-banks-balance-sheet; US ADIs is sourced from: https://www.federalreserve.gov/releases/H8/current/h8.pdf; and Eurozone ADIs is sourced from: http://sdw.ecb.europa.eu/ reports.do?node=10000029.

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1198   Banking Systems Around the World Assests of AUS ADIs

12% 8% 7%

11% 42%

Assests of NZ ADIs Housing Loans (Owner-occupier and investment) Term Loans Other Loans Cash and other Liquid Assets Securities Other Assets

20%

Assests of US ADIs

6% 13% 14% 8%

21%

38%

4%

8%

8% 45%

35%

Housing Loans (Owner-occupier and investment) Term Loans Cash and other Liquid Assets Securities

Assests of Euro Area ADIs Housing Loans (Owner-occupier and investment) Term Loans Other Loans Cash and other Liquid Assets Securities

12% 16% 22%

25% 20%

5%

Housing Loans (Owner-occupier and investment) Term Loans Other Loans External Assests Securities Other Assets

Figure 38.1  Asset Composition of Banks in Australia, NZ, and Globally.

housing loans comprise 42 percent of loan portfolios, while in NZ banks are even more concentrated and allocate 45 percent of their total assets toward housing loans (see Figure 38.1). These concentrations in housing loans are relatively higher than the holdings of US deposit-taking institutions and are almost three times the concentrations seen in Eurozone deposit-taking institutions. Another distinctive feature of the NZ loan books is that they are also highly concentrated in term loans with 35 percent of the aggregate assets of NZ deposit-taking institutions comprising term loans, exceeding the levels observed in the Eurozone (25 percent), the US (21 percent) and Australia (20 percent). This is likely due to the limited capacity of NZ businesses to borrow for longer terms in external capital markets as the country is relatively small with few large listed companies. In both Australia and NZ, banks remain the key source of external financing for SMEs and the agricultural sector. In Australia, more than two-thirds of businesses with one to four employees, and almost three-quarters of businesses with five to nineteen employees, approached banks for debt financing during 2015–16. Moreover, over 90 percent of rural debt is held by banks in Australia and New Zealand as at 30 June 2017.8 Within housing loans (the mortgage sector), banks in the Australian banking ­sector are funding more property investments than those in NZ, with 41.1 percent of all loans in owner occupied loans versus 25.6 percent for investment property purchases in Australia, and a lesser 40.3 percent compared to 18 percent in New Zealand (see Table 38.4). 8 Sourced from: https://financialservices.royalcommission.gov.au/publications/Documents/somefeatures-of-the-australian-banking-industry-background-paper-1.pdf.

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Banking in Australia and New Zealand   1199

Table 38.4  Sector Concentration by Bank Type in Australia and Loan Type in all Australian and New Zealand Banks Sector Concentration by Bank Type in Australia(a)

Personal Government NFCs FCs Housing: Owner occupied Housing: Investment

AUS Big Four

Other Domestic

Foreign

4.4% 0.2% 25.8% 4.2% 42% 23.5%

5.1% 0% 18% 1.5% 49.8% 25.6%

2.7% 0.8% 55% 8% 27.3% 6.2%

Sector Concentration by Loan Type in all Australian and New Zealand Banks (b)

Personal Government NFCs FCs Housing: Owner occupied Housing: Investment

% of Total Loans in AUS

% of Total Loans in NZ

4.3% 0.2% 28.3% 4.3% 41.1% 21.8%

2.6% 0.6% 38.4%* 2% 40.3% 16%

*Agriculture contributes 14.1% of total loans. Sources: (a) Australian data sourced from: http://www.apra.gov.au. (b) NZ data sourced from: https://www.rbnz.govt.nz/statistics/.

This has been largely driven by rising property prices in Australian capital cities like Sydney and Melbourne in recent years. In contrast, foreign banks located across the Tasman Sea are much less active in mortgage lending. Foreign banks in Australia and NZ are more concentrated in corporate lending (Non-Financial Corporations (NFCs)) than in housing loans, with 55 percent of their portfolios allocated to NFCs and only 27.3 percent in housing loans. This is likely due to the market dominance of local lenders in retail banking and household/­ consumer finance. Consequently, foreign banks have, over time, become more specialized and competitive in corporate lending (to NFCs). Lending to Finance Companies (FCs) is on a small scale in both Australia (4.3 percent) and New Zealand (2 percent).

38.5.2  Growing Reliance on Mortgages Since the 1990s, Australian banks have been heavily concentrated in residential ­mortgage lending. The gradual shift toward housing loans began in the early 1990s as business loan portfolios suffered significant losses during the 1993 recession. Subsequently in

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1200   Banking Systems Around the World the remainder of the 1990s, the Australian corporate sector went through a period of deleveraging and reduced a significant amount of debt on their balance sheets. The late 1990s also coincided with the introduction of Basel I capital requirements, which gave a lower risk weighting to residential loans for regulatory purposes and contributed to a reduction in the proportion of business lending in Australian banks’ loan portfolios from 62 percent in 1985 to 48 percent in 1995. At the same time, residential loan approvals rose from 16 percent in 1991 to comprise 46 percent of banks’ loan portfolios by 1995 and have since remained a relatively stable portion of banks’ loan portfolios.9 The Australian banking industry is unique in that Australian mortgages are dominated by variable interest rate loans (about 80 percent of total loans). The variable interest rates move closely with the Reserve Bank of Australia’s target cash rate used to effect monetary policy but are largely set at the bank lenders’ discretion. This offers borrowers greater flexibility when making prepayments. As mortgage interest payments are not tax deductible in Australia, variable rates allow borrowers to make additional prepayments when rates are low, which allows the borrower to build up a repayment buffer against tougher economic conditions. In the decade since the GFC there has been a marked increase in the spread between the cash rate and the advertised lending rate on household mortgages. The rising value of residential mortgages outstanding in the Australian and NZ banking industries, along with historically high housing prices relative to average income levels in major capital cities, are creating uncertainty as there are concerns that this could be indicative of the development of a housing credit bubble. Australian and New Zealand house prices (particularly on the east coast in Australia and in Auckland in NZ) have more than doubled since the GFC, causing the value of housing loan approvals to increase by almost 70 percent from around 16 billion AUD in 2009 to A$27bn in 2017. Strong demand for property with a growing population in major cities in both Australia and New Zealand, combined with geographic and regulatory constraints on land release and housing supply, a historically low cash rate with near zero interest rates worldwide, and growing household debt relative to low income levels (105 percent of GDP in 2009 to 122 percent in 2017), are creating increasingly concentrated loan portfolios skewed toward residential real estate loans.

38.6  Efficiency and Profitability The operations of Australian and New Zealand banks are highly efficient and have only become more so since banking deregulation took place in the 1980s. Avkiran (2000) and 9 See http://www.apra.gov.au/Speeches/Documents/1508-ABE-Lunchtime-Briefing-Banking-onhousing-26August2015.pdf; https://www.rba.gov.au/publications/rdp/2013/pdf/rdp2013-15.pdf; https://www. rba.gov.au/speeches/2010/sp-ag-300310.html; https://www.rba.gov.au/chart-pack/household-sector.html.

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Banking in Australia and New Zealand   1201 Sathye (2001) find that Australian domestic banks have been more efficient than their foreign competitors. They empirically investigate the x-efficiency (technical and allocative) in Australian banks using non-parametric techniques to compute standard efficiency scores. Banks in Australia were typically less efficient overall compared with the banks in European countries and in the US. Their earlier results indicate that the inefficiency in Australian banks was largely attributable to the wasting of inputs (technical inefficiency) rather than choosing the incorrect input combinations (allocative inefficiency). Sturm and Williams (2004) also considered the impact of foreign bank entry on banking efficiency in Australia during the post-deregulation period 1988–2001. They found that major Australian banks have consistently used their size and dominance as an effective barrier to entry to new foreign bank entrants. Competition emanating from diversity in bank types has enabled further efficiency improvements. Sturm and Williams (2008) find further evidence to suggest that banks from more financially sophisticated nations and those that have operated in Australia for a longer timeframe are more efficient within Australia. Overall, foreign banks benefit from an early mover advantage into the Australian and New Zealand banking industry. Similarly, Lu et al. (forthcoming) recently examined the cost and profit efficiency of banks in New Zealand and find that foreign banks in New Zealand are typically more efficient than domestic banks but the Australian-owned banks in New Zealand operate more efficiently than foreign-owned banks from other countries, suggesting that there are significant economic benefits from the high degree of banking market integration across Australian and New Zealand banking markets. Their results build on Tripe and To’s (2002) previous findings that the performance of foreign-owned banks in New Zealand depends (similar to that for foreign entrants in Australia), among other factors, on the length of time that they have been operating in the host country. Smaller deposit-taking institutions, like credit unions and building societies, populate a regulated sub-sector of the Australian financial system. These mutuals have had to adapt to significant changes in market competition post banking deregulation and have remained competitive by diversifying their interest and non-interest income sources and embracing technological changes and keeping costs low through achieving scale efficiencies (Worthington,  2000; Esho, Kofman, and Sharpe,  2005). However, their objectives, ownership structures and cultures remain different to commercial banks and Worthington (2004) finds that most of the consolidation in this sector has occurred through “friendly mergers” with the perceived compatibility in associational bond and membership being an important driver. McAlvey, Sibbald, and Tripe (2010) also find similar drivers of credit union mergers in New Zealand. Brown and Davis (2009) discuss the challenges for mutual financial institutions in Australia to meeting minimum capital requirements since the formal adoption of the Basel risk-weighted regulatory framework. Using a sample of the largest Australian credit unions, they provide empirical evidence to show that Australian credit unions shifted to using shorter-term profit targets in managing their capital buffers above those binding regulatory minimums since the Basel rules were first introduced into the Australian banking sector in 1992.

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1202   Banking Systems Around the World Indeed, at present Australian and NZ banks are highly operationally efficient by global standards.10 On average, the Australian and NZ banks have a cost-to-income (C-I) ratio that is slightly lower than banking sectors in other developed economies like the US, Japan and in the Eurozone (see Table 38.5). The C-I ratio for Australian banks is 53 percent and for NZ banks it is 42 percent which is much closer to the efficiency of the four major banks (C-I ratio of 43 percent) that dominate both markets. Elsewhere, the C-I ratios are 58 percent for European banks, 59 percent for US banks, 63 percent for Japanese banks, and even 77 percent for UK banks (on average). This indicates that there are differences in the operating activities and lending portfolios of Australian and NZ banks relative to other banks internationally. First, the Big Four and their NZ subsidiaries have historically focused on traditional commercial banking activities. In comparison, “universal” banks situated in the United States and continental Europe (specifically Switzerland and Germany) have additional arms in investment banking and wealth management services. These activities have higher levels of staff remuneration relative to commercial banking operations which, on average, increases personnel (employeerelated) expenses for the financial institutions. Second, lending concentration in certain segments can also help explain the differential in cost-to-income ratios. Household lending for example, is more homogeneous than Commercial and Industrial (C&I) loans with respect to loan applicants, and are thus more likely to benefit from technological developments and scale economies created in processing and monitoring loans. This helps to avoid the excess costs associated with relationship-based lending activities. Australian and NZ banks have 42 percent and 45 percent, respectively, of their assets concentrated in housing, both owner occupier and investment, compared with a smaller 16 percent within the Eurozone (as discussed above) and this can account for much of the cost efficiencies achieved relative to other banks internationally.

Table 38.5  Cost-to-Income Ratios Cost-to-Income Ratios(a)

C-I*

NZ

AUS

US

UK

Japan

Eurozone(b)

Egypt (lowest)

Brazil (highest)

42%

53%(c),**

59%

77%

63%

58%

28%

98%

*Includes all financial institutions with assets greater than US $10 Billion. **Four major Australian banks recorded a Cost-to-Income (C-I) Ratio of 43% in 2017. Sources: (a) https://marketintelligence.spglobal.com/our-thinking/ideas/cost-to-income-ratios-ofbanks-worldwide. (b) https://www.ecb.europa.eu/pub/pdf/other/reportonfinancialstructures201610. en.pdf. (c) https://home.kpmg.com/au/en/home/insights/2017/11/major-australian-banks-full-year2017-snapshot.html.

10  Data sourced from: http://www.rba.gov.au/publications/fsr/2014/sep/pdf/0914.pdf.

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Banking in Australia and New Zealand   1203 Due to their efficient operations and business models, the Australian and NZ banks are also more profitable relative to global standards.11 The return on equity (ROE) for both the Australian and NZ banking industry has consistently been above 10 percent with the four major banks’ ROE being around 15 percent in recent years (see Table 38.6). In these two banking sectors, average ROE has been 14 percent in NZ and a slightly lower 12.3 percent in Australia. ROE, is a measure of profit, expressed as a percentage of shareholders’ equity. It shows how much profit a corporation (like a bank) generates with the funds invested by its shareholders. The high profitability indicated by these ROE figures in the banking industry has been the result of strong economic growth over the past two decades in both Australia and New Zealand as well as low Cost-to-Income ratios achieved by the banks. The Australian and NZ banking sectors have not faced an economic downturn for the longest period of time compared to international counterparts in the US, UK, and Europe and this has supported growing profitability enjoyed by bank shareholders. Australian and New Zealand banks currently have higher returns on equity than banks in many other major developed markets. Those returns are about twice as high or more than the returns of Japanese, European, and UK banks. The returns earned by US banks are only a few points below the Australian and New Zealand levels. Interestingly, banks in the smaller banking industry in NZ enjoy greater profits from their traditional lending activities as the net interest margins experienced at 2.1 percent is one of the highest outside of the US. Australian banks have slightly lower net interest margins at 1.7 percent compared with NZ banks and are more similar in terms of the interest rate spreads charged on their traditional lending businesses when compared to European and UK banks (at 1.8 and 1.4 percent, respectively). This suggests that the banking industry is fairly competitive in the lending business, despite the high concentration within the sector. As we have seen, the Australian and NZ banking sectors perform extremely well ­overall relative to global markets—this fact becomes even more obvious when considering the performance of the four major banks that operate in the Oceania region. The C-I ratio for Australia’s Big Four banks has fallen roughly 20 percent over the previous two decades to 43.4 percent in 2017. This means that on a global scale, the C-I ratio of the Big Four has been at the bottom end for the past decade—a key contributor to

Table 38.6  Profitability

ROE(a) NIM(b)

NZ

AUS

US

UK

Japan

Eurozone

World

14% 2.1%

12.3% 1.7%

9.6% 3.2%

3.5% 1.4%

6% 1%

6.9% 1.8%

10.2% 3.6%

Sources: (a) https://fred.stlouisfed.org. (b) https://fred.stlouisfed.org.

11  Caveat: A precise international comparison cannot be made, mainly due to differences in accounting standards employed by banks around the world.

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1204   Banking Systems Around the World consistent profitability (measured by the ROE). This reduction reflects growing ­competitive advantages in commercial banking operations. Technological developments in  the space of loan approvals (specifically the processing of residential mortgages using more hard than soft information) allow banks to streamline these products to their customers. This has allowed the banks to reconfigure the operating model of local branches and at the same time cut back on the size of their costly branch networks. Traditional transaction activities are increasingly being pooled through net banking and mobile phone applications, which has allowed local bank branches to focus on product sales and cross-selling to customers, thereby increasing income for the institution relative to the costs incurred.12

38.7  Explicit and Implicit Government Support for Banks During the Global Financial Crisis of 2007–8, governments in a large number of countries around the world strengthened deposit protection arrangements and introduced explicit guarantees for financial institutions’ liabilities (see Demirgüç-Kunt, Kane, and Laeven, 2014). Australian and NZ banking systems are unique in that they were the two last OECD countries that did not have explicit deposit insurance on bank deposits or other forms of bank debt in place prior to the GFC. Prior to the GFC, the two banking systems relied on depositor preference, in which it is understood that all deposits have a higher ranking than the claims of ordinary unsecured, non-preferred creditors. However when explicit deposit insurance schemes and wholesale funding guarantee schemes were implemented en masse in advanced economies in response to the extremely difficult funding conditions experienced during the GFC, Australian and NZ financial regulators quickly followed suit. They implemented protection schemes that were designed to promote financial system stability and to encourage the ongoing provision of credit by supporting confidence in the financial sector and reducing actual and perceived risks, thereby assisting financial institutions to access deposit and wholesale funding (at a reasonable cost) during a time of considerable financial turbulence. In Australia, two explicit protections were implemented for the first time—the Financial Claims Scheme (also known as the Australian Government Deposit Guarantee) was introduced first to protect retail depositors to the value of 1 million AUD and Australian Government Guarantee Scheme protected large deposits and wholesale debt funding. During the period between 12 October 2008 and 31 March 2010, the Australian Government implemented the Guarantee Scheme for Large Deposits and Wholesale Funding (Australian Government Guarantee Scheme hereafter) to offer increased depositor protection and guarantee arrangements for financial institutions’ wholesale 12  Sourced from: http://www.rba.gov.au/publications/fsr/2014/sep/pdf/0914.pdf.

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Banking in Australia and New Zealand   1205 debt. The Australian Government Guarantee Scheme was announced in October 2008 and commenced on 28 November in that year. Under this scheme, eligible ADIs were able to offer government-guaranteed deposits greater than 1 million AUD, and government-guaranteed wholesale debt funding with maturity out to five years in exchange for a risk-based fee (see Luong et al. (2019) for details of the scheme). It was designed to provide protection for large deposits greater than 1 million AUD and banks’ wholesale debt funding to maintain continual confidence in the financial system. It was introduced in response to the evaporation of liquidity in the global financial system at the height of the 2008 Great Recession. The scheme was implemented to restore financial system stability in Australia and to encourage the ongoing provision of credit by supporting confidence and assisting ADIs to access wholesale funding from international credit markets at a reasonable cost during the time of considerable turbulence and liquidity shortage. The scheme also ensured that Australian institutions were not placed at a disadvantage, compared to their international competitors, who could access similar government guarantees on bank debt. The scheme was administered by the national central bank (the Reserve Bank of Australia) for the federal government. Eligible ADIs were able to apply to have their eligible wholesale funding securities guaranteed under the scheme. The scheme was voluntary and subject to an approval process and the payment of a monthly fee by the ADI on the amounts guaranteed. Following improvements in funding and market conditions, the Australian government closed the wholesale funding guarantee to new borrowings on March 31, 2010. Outstanding large deposits and wholesale funds of approximately 160 billion AUD with up to five years of maturity remained at the time of the removal of the government guarantee. In the context of the Financial Claims Scheme introduced in Australia for retail deposits during the GFC, Yan et al. (2014) showed that market deposit rates and deposit growth for ADIs became much less sensitive to bank fundamentals once the scheme was in place, meaning that market discipline had been weakened to some extent by the introduction of a formal explicit deposit protection arrangement. Yan et al. (2014, 2015) find that the introduction of the explicit domestic deposit insurance scheme lowered the perceived risks for Australian financial institutions and this, in turn, led to a reduction in market discipline by depositors for protected banks and mutuals (building societies and credit unions). They find this to be reflected in the lower interest rates demanded by depositors resulting in a major reduction in funding costs for financial institutions after the introduction of the Financial Claims Scheme. Luong et al. (2019) closely examine the effects of the Australian Government Guarantee Scheme and find that the introduction of the wholesale funding guarantee was effective in helping larger ADIs to secure wholesale debt funding at reasonable costs during the GFC and as intended, it supported consumer confidence by lowering actual and perceived bank risks within the financial system. They find that the Australian Government Guarantee Scheme led to a significant reduction in bank funding costs for those ADIs that voluntarily paid to adopt the government guarantee for their longerterm liabilities (with a maturity up to five years). Moreover, they find that larger banks continued to enjoy lower funding costs even after the subsequent removal of

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1206   Banking Systems Around the World the government guarantee scheme. This suggests that the effects of the Australian Government Guarantee Scheme may continue to persist in the form of an implicit ­subsidy for an extended period, even well beyond the closure of the Australian Government Guarantee Scheme, given the precedence with having an explicit government guarantee on bank liabilities. This can continue to help banks to maintain better access to off-shore funding markets. However, despite the significant reduction in banks’ funding costs, the authors do not find evidence to suggest that the government guarantee increased risk-taking in banks that voluntarily paid for the guarantee. Consistent with this revelation, Bollen et al. (2015) also found a significant reduction in both systematic and systemic risks in Australian banks with the introduction of the government guarantee scheme during the GFC. Corroborating with the cross-country study of Anginer, Demirgüç-Kunt, and Zhu (2014), the empirical evidence indicates that the warranted introduction of explicit protection at the height of the GFC was beneficial as it effectively reduced bank risk (especially systemic risk) and served to maintain confidence in the banking system without creating moral hazard problems, unlike in normal times. Overall, the explicit protection offered by the government through the Financial Claims Scheme and the Australian Government Guarantee Scheme strengthened the overall stability of the Australian financial system by ensuring that financial institutions continued to have access to capital market funding during the most intense phase of the crisis and banks continued to extend credit to support investment throughout the economy. However, it remains that there is a perception that the four major banks dominant in the Australian and NZ banking industries are too big and too systemically important to fail and they continue to enjoy some implicit subsidies in funding costs that help to maintain their competitive advantages relative to smaller domestic financial institutions. The empirical evidence clearly indicates that the large Australian banks can borrow more cheaply because their lenders expect them to receive government support during financial crises and this perception has continued since government support was officially extended at the height of the 2007–8 Global Financial Crisis. Furthermore, the Productivity Commission (2018) argues that by “incorporating perceived government support in their relative ratings of Australia’s banks, rating agencies further embed the major banks’ ‘too big to fail’ status” (p. 38).

38.8  Resilience of the Australian and New Zealand Banking Systems 38.8.1  Capital Requirements The Australian Prudential Regulation Authority (APRA) enforces the capital adequacy requirements of all Australian banks. In 2013, APRA implemented Basel III and

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Banking in Australia and New Zealand   1207 increased the requirements for both the quality and quantity of regulatory capital. As a result, the composition of Tier 1 and Tier 2 capital has also changed. Tier 1 capital must be at least 6 percent (of risk-weighted assets), of which 4.5 percent must be from common equity. The combination of Tier 1 and Tier 2 capital must be at least 8 percent of risk-weighted assets. Regarding the capital buffer levels, APRA requires all locally incorporated ADIs to hold a capital buffer consisting of three components: a capital conservation buffer, a countercyclical capital buffer and an additional buffer (1 percent of risk-weighted assets) for domestically systemically important banks (D-SIBs) like the “top four” major Australian banks, constituting a common equity tier 1 (CET1) ratio of 9.5 for most banks and 10.5 for the largest banks (see Table 38.7). In the NZ banking industry, banks are well capitalized relative to the local prudential capital requirements (CET1 ratio of 7 percent) with the four largest banks reporting a higher weighted average CET1 ratio of 10.5 percent. However, this level of capitalization places NZ banks in the bottom quartile of banks globally as the world’s major banks reported a median CET1 ratio of 12.1 percent as at February 2017. This does not suggest that the capital framework in NZ is inadequate but, rather, it reflects the different approaches and timing in implementing the new capital requirements under Basel III to accommodate for idiosyncrasies within a country’s financial system. In December 2015, for example, the APRA estimated that after factoring differences in risk-weight exposure measurements across economies, the major Australian banks would record a CET1 ratio 3.5 percent higher under an internationally uniform prudential methodology.13,14 Bui, Scheule, and Wu (2017) recently examined the financial resilience of the Australasian banking industry. The authors conducted simulations to assess the

Table 38.7  Capital Requirements

CET1 Ratio

AUS

NZ

9.5%*

7%**,(a)

US*** 10%(b)

UK 9.875%****

Eurozone 7.875%*****

*for Banks listed as a D-SIB, CET1 ratios 1% higher. **equal to the minimum level recommended in Basel III. ***D-SIB listed. 2019 target. ****Comprised of 4.5%CET1 + 1.5% Pillar 2 (discretion) + 1.875% CCB + 1% CCCB. *****Comprised of 4.5%CET1 + 1.5% Pillar 2 (discretion) + 1.875% CCB. Sources: (a) https://www.rbnz.govt.nz/regulation-and-supervision/banks/prudentialrequirements/information-relating-to-the-capital-adequacy-framework-in-new-zealand. (b) https://www.forbes.com/sites/greatspeculations/2017/03/10/how-the-largest-u-sbanks-have-strengthened-their-core-capital-ratios-since-2012/#f5bc4e7445ac.

13  Sourced from: https://www.rbnz.govt.nz/research-and-publications/speeches/2017/speech-2017-03-07. 14  RBNZ conducted a similar study and found an increase in CET1 ratios of 1 to 2 percent.

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1208   Banking Systems Around the World c­ onsequences of banks having higher capital buffers (above the minimum regulatory requirements) on financial system resilience, banks’ cost of debt, and credit supply and found that in spite of its high level of concentration, the Australasian banking system has a strong ability to withstand or recover from losses, should they occur in the near future. The authors examined the likely unconditional losses to the Australian financial system at the aggregate level using systemic metrics such as the Value-at-Risk (VaR), conditional VaR (CoVaR), and also Expected Shortfall (ES) under varying levels of capital buffers. They find that a moderate increase in bank capital buffers of around 2 to 3 percent would be sufficient to maintain system-wide resilience, even after taking economic downturns into consideration. Their findings affirm that higher capital buffers are associated with lower system-wide losses. Banks that hold capital buffers in excess of the regulatory requirement are able to absorb losses more sufficiently, and hence, are less likely to pass the losses onto the whole system. Furthermore, while banks benefit from paying a lower cost of debt when they have a higher capital buffer, lending volumes are reduced, indicating that credit supply may be hampered if bank capital levels are raised too high for banks in the financial system. Cummings and Durrani (2016) analyzed the loan loss provisioning (LLP) practices of Australian banks and found evidence that Australian banks are prudent in mitigating the impact of external credit market conditions under the Basel regulatory framework in their provision of credit supply, and actively increase their provisions in anticipation of future lending growth by allocating their earnings and capital buffers to pre-fund future credit losses. Brown, Do, and Trevarthen (2017) provide further evidence to show that the Australian banking sector is highly resilient as, during the 2007–8 Global Financial Crisis, globally active international banks retrenched home and stopped lending to the Australian market. However, with limited global operations, the major Australian banks were able to absorb and manage the liquidity shock. This subsequently resulted in these domestic banks carrying a significantly greater proportion of revolving credit facilities in their syndicated loan portfolios after 2008. Domestic banks’ willingness and ability to deal with the disruption in credit supply and to hold a greater proportion of high liquidity risk revolvers were largely supported by the increasing levels of their transaction deposits. This was particularly encouraged by the introduction of explicit deposit insurance and government guarantees for bank liabilities (Luong et al., 2019).

38.8.2  Recent Banking Regulatory Reforms There have been major episodes of banking deregulation, financial system inquiries (FSI), and subsequent regulatory reforms based on recommendations emanating from the FSIs that have shaped the Australasian banking industry. There is now much more political attention on Australian banks and their activities with the introduction of a new bank levy and the launch of a Royal Banking Commission. The most recent FSI took place in 2014, post the Great Recession. The key recommendations emanating from

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Banking in Australia and New Zealand   1209 the 2014 FSI related to the capital standards for Australian banks as, like in the rest of the world, there is an ongoing debate concerning the appropriate size of capital requirements for banks to mitigate system-wide losses, and the economic tradeoff associated with raising more capital. From a macro-prudential perspective, raising the level and quality of capital in the banking system is the traditional regulatory approach to ensure that there is effective loss-absorbing capacity. Thakor (2014) shows theoretically that higher capital is associated with higher lending, higher liquidity creation and banks’ value as well as their survival likelihood during the crises. In the aftermath of the Great Recession suffered in the rest of the world, an extensive Financial System Inquiry was conducted and reported in 2014 by the Australian Government (Australian Treasury, 2014) to provide recommendations to enhance the financial resilience of the Australian financial system and banks became a key focus, given the weaknesses shown in the global banking sector, especially with regards to their loss absorption capacity. The inquiry identified that Australian banks were not as strongly capitalized as they ought to be and recommended that banks increase their capital requirements to the levels of the top quartile of all banks in the world to improve their loss absorption capacities. Following that recommendation, banks had to engage in large equity capital raisings to shore up their regulatory capital levels to world-class standards. This has made Australian banks and the financial system as a whole even ­better capitalized to weather any future economic shocks in years to come. Overall, the new higher capital requirements coming from the FSI in Australia, and as part of the additional Basel III capital and liquidity arrangements, do impose extra constraints on banks’ balance sheets. Based on scenario analysis, Cummings and Wright (2016) showed that the higher capital requirements recommended by the FSI would flow on to result in only a modest increase in the borrowing costs faced by bank customers (in the order of 20 basis points annually for a 5 percentage point increase in the ratio of equity capital to bank assets). The Prudential Regulator, APRA’s more conservative approach relative to other banking systems around the world should also help to lower the cost of funds for banks based on the recent findings of Bui, Scheule, and Wu (2017) on the tradeoffs associated with higher capital requirements for Australian banks. However, excessively high capital requirements may instead force banks to curb their lending and reduce credit supply throughout the economy. On balance, using more capital funding and holding more liquidity is likely to enhance the stability of the financial system and give more confidence to wholesale investors, creditors, and depositors, as reflected in lower risk premia required by these providers of funds to banks in the highly integrated Australian and New Zealand banking industries. During 2017, the Australian Federal Government introduced a major bank levy on the five largest banks in the country (the Big Four plus the Macquarie Bank). This bank levy was designed to contain excessive risks in domestic systemically important banks, and to help to raise new revenue to augment depleted government coffers following taxpayer-funded support for banks that took place during the financial crisis. More specifically, the objectives of the bank levy are to ensure that large banks in Australia contribute to the government budget in the short and long term; make a fair contribution given the

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1210   Banking Systems Around the World risks that they pose to the financial system and wider economy; and operate on a more level competitive playing field with smaller banks. The bank levy is expected to raise 6.2 billion AUD over the first four years of its operation. Chronopoulos, Sobiech, and Wilson (forthcoming) have recently examined the impact on shareholders from the Australian Federal Government’s introduction of this bank levy. They perform an event study using abnormal daily stock prices for a small sample of commercial banks operating and listed in Australia that were both affected and not affected by the new bank levy around the announcement of the bank levy on May 9, 2017. The results of their event study analysis indicate a material loss of shareholder value following the announcement of the bank levy for the large Australian banks that were directly affected by this policy decision. The cumulative abnormal returns for the banks liable to pay the new bank levy suggest a decline in value of the order of 5.2 percent, which is both statistically and economically significant. This indicates that market expectations regarding the effects of the sudden introduction of a bank levy on large Australian banks are detrimental for shareholder value. In late 2017, following repeated banking scandals involving the major banks over a number of years, the Australian Federal Government established the Royal Commission into Misconduct in the Banking, Superannuation, and Financial Services Industry and appointed the Honorable Kenneth Madison Hayne AC QC as the Commissioner for this major inquiry.15 The Royal Banking Commission started investigating the extent of misconduct in the Australian financial services sector in early 2018 and identified in its September 2018 Interim Report some fundamental issues in the provision of consumer financial services and perverse remuneration structures that existed within the financial services industry. The judiciary inquiry has publicly revealed that the large financial institutions in Australia have abused their oligopolistic powers and have breached laws when issuing home loans, credit cards, and other consumer loans and financial products. Public trust in the Australian financial services industry has been compromised through the repeated revelations of malpractice across a broad range of financial products and services offered by the industry. Banks have become too focused on crossselling financial products, not just to those customers who did not need them, but even to customers who were no longer living; their greed has been publicly condemned, as have their sales-driven profit-maximization strategies. It has also been highlighted in the judicial inquiry that when misconduct by the banks has been revealed in the past, it either went unpunished or the consequences did not meet the seriousness of what had been done. The responsible financial regulators rarely, if ever, took full enforcement action and went to court to seek public denunciation of, and punishment for, misconduct and the penalties they settled for were nearly always much more trivial than what they could properly have asked a court of justice to impose upon the banks. On February 4, 2019, Commissioner Kenneth Hayne delivered his final report on the banking and financial services industry and made a number of referrals to the financial regulators, the Australian Securities and Investments Commission (ASIC) and APRA, to further 15  See details at: https://financialservices.royalcommission.gov.au.

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Banking in Australia and New Zealand   1211 investigate and take appropriate action over cases of misconduct identified. Critically, he also provided seventy-six recommendations to overhaul the financial sector and, in particular, highlighted the need to end conflicted remuneration within the Australian financial services industry.

38.9 Conclusions The Australian and New Zealand banking systems are highly integrated with all “top four” Australian banks having significant investments and operations within the relatively smaller New Zealand banking sector. The two most prominent banking ­industries in the Oceania region are highly interconnected and this naturally results in similar banking market structures and regulatory supervision frameworks for banks to operate under. Australian and NZ banks were resilient throughout the Great Recession that started in 2008 and they have displayed relatively stronger financial performance compared to banking industries in other developed economies, which suffered economic downturns and credit losses that weighed heavily on US and European banks through the recent Great Recession and European Sovereign debt crisis. They were remarkably resilient to the liquidity shortages that engulfed the rest of the world during the 2007–8 global financial crisis period. They have also absorbed the higher capital requirements that have been prescribed by banking regulators post-crisis relatively well. The Australian banking system has always been well capitalized and increasingly more so with recent recommendations for higher capital requirements emanating from the 2014 Financial System Inquiry that encouraged banks to become among the strongest of all the banks in the world. Despite the significant level of market concentration, both the Australian and NZ banking industries remain two of the most stable banking ­systems in the developed world, and are well supported and closely supervised by financial regulators within a sound regulatory framework. However, the recent Royal Banking Commission in Australia has identified some fundamental issues in the provision of consumer financial services, and public trust in the Australian financial services industry has been compromised through repeated revelations of malpractice across a broad range of financial products and services offered by the industry. This has renewed interest in boosting competition within the banking sector in order to improve upon financial consumer outcomes.

References Anginer, D., Demirgüç-Kunt, A., and Zhu, M. (2014). “How Does Deposit Insurance Affect Bank Risk? Evidence from the Recent Crisis,” Journal of Banking and Finance, 48, 312–21. Australian Treasury (2014). “Financial System Inquiry: Final Report,” Commonwealth of Australia, Canberra.

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1212   Banking Systems Around the World Avkiran, N.K. (2000). “Rising Productivity of Australian Trading Banks Under Deregulation,” Journal of Economics and Finance, 24, 122–40. Bollen, B., Skully, M., Tripe, D., and Wei, X. (2015). “The Global Financial Crisis and Its Impact on Australian Bank Risk,” International Review of Finance, 15, 89–111. Brown, C. and Davis, K. (2009). “Capital Management in Mutual Financial Institutions,” Journal of Banking and Finance, 33, 443–55. Brown, C., Do, V., and Trevarthen, O. (2017). “Liquidity Shock Management: Lessons from Australian Banks,” Australian Journal of Management, 42, 637–52. Bui, C., Scheule, H., and Wu, E. (2017). “The Value of Bank Capital Buffers in Maintaining Financial System Resilience,” Journal of Financial Stability, 33, 23–40. Chronopoulos, D.K., Sobiech, A., and Wilson, J. (forthcoming). “The Australian Bank Levy: Do Shareholders Pay?” Finance Research Letters. Cummings, J. and Wright, S. (2016). “Effect of Higher Capital Requirements on the Funding Costs of Australian Banks,” Australian Economic Review, 49, 44–53. Cummings, J.R. and Durrani, K.J. (2016). “Effect of the Basel Accord Capital Requirements on the Loan–Loss Provisioning Practices of Australian Banks,” Journal of Banking & Finance, 67, 23–36. Delis, M., Kokas, S., and Ongena, S. (2017). “Bank Market Power and Firm Performance,” Review of Finance, 21, 299–326. Demirgüç-Kunt, A., Kane, E., and Laeven, L. (2014). “Deposit Insurance Database,” IMF Working Paper No. WP/14/118, July. Esho, N., Kofman, P., and Sharpe, I. (2005). “Diversification, Fee Income, and Credit Union Risk,” Journal of Financial Services Research, 27, 259–81. Gertler, M., Kiyotaki, N., and Prestipino, A. (2016). “Anticipating Banking Panics,” American Economic Review, 106, 554–9. Heard, C., Menezes, F., and Rambaldi, A. (2017). “The Dynamics of Bank Location Decisions in Australia,” Australian Journal of Management, 43, 241–62. Lu, Y.F., Gan, C., Hu, B., Toh, M.Y., and Cohen, D. (forthcoming). “Bank Efficiency in New Zealand: A Stochastic Frontier Approach,” New Zealand Economic Papers. Luong, T.M., Pieters, R., Scheule, H., and Wu, E. (2019). “The Impact of Government Guarantees on Banks’ Wholesale Funding Costs and Lending Behavior: Evidence from a Natural Experiment,” Pacific-Basin Finance Journal, in press. McAlvey, L., Sibbald, A., and Tripe, D. (2010). “New Zealand Credit Union Mergers,” Annals of Public and Cooperative Economics, 81, 423–44. Productivity Commission (2018). “Competition in the Australian Financial System,” Australian Government Productivity Commission Inquiry Report Overview and Recommendations, No. 89, June. Sathye, M. (2001). “X-Efficiency in Australian Banks,” Journal of Banking and Finance, 25, 613–30. Stewart C., Robertson, B., and Heath, A. (2013). “Trends in the Funding and Lending Behaviour of Australian Banks,” Research Discussion Paper 2013–15, Reserve Bank of Australia, Sydney. Sturm, J.-E. and Williams, B. (2004). “Foreign Bank Entry, Deregulation and Bank Efficiency: Lessons from the Australian Experience,” Journal of Banking and Finance, 28, 1775–99. Sturm, J.-E. and Williams, B. (2008). “Characteristics Determining the Efficiency of Foreign Banks in Australia,” Journal of Banking and Finance, 32, 2346–60. Thakor, A. (2014). “Bank Capital and Financial Stability: An Economic Trade-Off or a Faustian Bargain?” Annual Review of Financial Economics, 6, 185–223.

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Banking in Australia and New Zealand   1213 Tripe, D. and To, H.M. (2002). “Factors Influencing the Performance of Foreign-Owned Banks in New Zealand,” Journal of International Financial Markets, Institutions and Money, 12, 341–57. Worthington, A. (2000). “Technical Efficiency and Technological Change in Australian Building Societies,” Abacus, 36, 180–97. Worthington, A. (2004). “Determinants of Merger and Acquisition Activity in Australian Cooperative Deposit-taking Institutions,” Journal of Business Research, 57, 47–57. Yan, X., Skully, M., Avram, K., and Vu, T. (2014). “Market Discipline and Deposit Guarantee: Evidence from Australian Banks,” International Review of Finance, 14, 431–57. Yan, X., Skully, M.T., Avram, K., and Vu, T. (2015). “Credit Unions, Market Discipline, and the Australian Deposit Guarantee,” Monash University Working Paper.

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Index

Note: Boxes, Figures and Tables are indicated by an italic “b”, “f ”, “t” and notes are indicated by “n” following the page numbers.

A

ABCP, see asset-backed commercial paper (ABCP) ABN Amro bank  361 ABS, see asset-backed securities (ABSs) ABSA bank  1089 access to financial services, see financial inclusion Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI)  361, 380 accounting principles and practices  114 accounting systems  48–9 Act on Provision of Trust Business by Financial Institutions (1943), Japan  1044 Action Program Concerning Enhancement of Relationship Banking Functions (2003 and 2004), Japan  1056, 1057 Additional Credit Claims framework, Europe 456 adjustable rate mortgages (ARMs)  165, 471, 478–9, 479f, 481, 489f Adrian, Tobias  20, 530–65 adverse selection and asset selection  511–13 and contagion  860 driving liquidity dry-ups  610–11 information disclosure  615, 802 and joint liability lending  407–9 and shadow banking  546 Africa 1076–109 agent banking  1098–9 bank-and branch-level evidence  1087–9 banking concentration  1083 banking losses  890 benchmarking banking systems  1085–6

branching 1097–9 characteristics 1077 competition 1083 credit registries  1096 credit unions  332 creditor rights  1096 cross-border entry  1106–8 data available  1078–9 deposits to GDP  1079–80, 1080f efficiency  1082–3, 1087 enterprise access to finance  1089–91, 1090f exchange rate pegs  582 financial development  1079–85, 1080f financial inclusion  1080, 1082, 1082f, 1086, 1091–6, 1092f, 1093t, 1094f, 1095f, 1099–100 financial innovation  1096–7 financial stability  1083–4 foreign-owned banks  1089, 1106–8 gender gap  1092–6, 1094f, 1095f global financial crisis  1083, 1084 household access to finance  1091–6, 1092f, 1093t, 1094f, 1095f income gap  1092–6, 1094f, 1095f labor force gap  1094f, 1095f liquid liabilities to GDP  1079–80, 1080f long-term finance challenge  1104–6 maturity distribution  1083 microfinance 418 microinsurance 1100 mobile banking  1102t, 1103–4 mobile money accounts  1092 mortgages 1083 new challenges  1104–8 overcoming barriers to financial inclusion 1096–104

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1216   index Africa (cont.) overhead costs  1088, 1088t personal identification  1100 population density  1086 private credit to GDP  1079–80, 1080f, 1081f, 1085–6, 1085f privatization 1089 profitability 1082–3 property registration  1096 rainfall insurance  1100 regulatory reforms  1107–8 short-term loans  1083, 1084f technological innovation  1101–4 agency problems in shadow banking  549–50 agent banking  1098–9 aggregate shocks, and systemic risk  862–3 AIG  626, 903, 986 Alibaba 558 Alipay 558 Allen, Franklin  16, 39–57 Allen, Linda  17, 153–77 Allen and Gale framework  43–4, 45, 607, 608, 859–60, 862, 863, 865 Allende, President Salvador  1158 Almost Ideal Demand System  237 Amanah (demand deposits)  370 American International Group, see AIG amortization  471, 479–80 Ancient Rome and Greece  953–4, 970 Anginer, Deniz  22, 685–703 Anglo-Irish Bank  901 Anzen credit cooperative  1059 Argentina ATMs 1166 bank failures  921, 923 bank insolvencies  890 bank runs  892, 899 banking crises  895 credit 1164 cross-border entry  1178 currencies 582 deposit insurance  696 efficiency 1175 financial inclusion  1166 financial liberalization  1160–1 foreign-owned banks  1156, 1161, 1171 global financial crisis  1162 privatization  1161, 1169

Argentine Central Bank  1162 ARMs, see adjustable rate mortgages (ARMs) artificial intelligence (AI)  268–9 ASF, see available stable funding (ASF) Ashcraft, Adam B.  20, 530–65 Ashikaga Bank  1060 Asia East Asian crisis  51, 865, 891 financial inclusion  1092f financing structure  40–1 G-SIBs 104 interest margins  1167 interest rates  1167 mergers and acquisitions  931, 933f, 934f Asian Infrastructure Investment Bank (AIIB) 1184 asset commonality, and contagion  49–50 asset management, and financial stability risks 562–3 asset purchase program (APP)  1019 asset quality review (AQR)  1023 asset relief interventions, response to global financial crisis  639 asset transformation role  64–8, see also maturity transformation asset-backed commercial paper (ABCP) and bank runs  547 evolution 509 guarantees 519 securitization  72, 154–5 and shadow banking  535, 539 asset-backed securities (ABSs) benefits and risks to investors  522–3 evolution 506–7 growth in demand  503–4 issuance  507, 508t, 517–18 OTD model  198 securitization  154–5, 503, 517–18 and shadow banking  535, 546–7 asset-backed securities purchase program (ABSPP) 1019 asset-based lending (ABL)  437, 1057 asymmetric information banking problems  853–4, 860 coordination games  46 and corporate complexity  115 and financial instability  579–80 and information sharing  802

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index   1217 and moral hazard  523 and securitization  511–12, 548–9 and systemic risk  853–4 ATMs, see automated teller machines (ATMs) Australia 1190–211 authorized deposit-taking Institutions (ADIs)  1191, 1195, 1205 bank assets  1191, 1192t, 1197–9, 1198f bank failures  921 bank levy  1209–10 banking concentration  1192–5, 1193t capital buffers  1207–8 capital requirements  1206–8, 1207t, 1209 competition 1192–5 debt funding  1196–7 deposit insurance  691, 1205 deposits 1195–6 efficiency 1200–4 financial services  1191 financial system inquiries (FSI)  1208–9 Four Pillars Policy  1194–5 funding sources  1195–7, 1196t funding uses  1197–200 global financial crisis  1204–6 house price bubble  1194–5, 1200 loans  1199, 1199t malpractice and misconduct  1210–11 mortgages, residential  1197–200 profitability 1200–4 regulatory reforms  1208–11 resilience of the banking system  1206–11 size and significance of banking  1191–2, 1192t tax subsidies  340 Australia and New Zealand Banking Group (ANZ) 1192 Australian Federal Government  1209–10 Australian Government Guarantee Scheme 1204–6 Australian Prudential Regulation Authority (APRA)  1206–7, 1209, 1210 Australian Securities and Investments Commission (ASIC)  1210 Austria 334 authorized deposit-taking Institutions (ADIs)  1191, 1195, 1205 automated clearinghouse (ACH)  265–6, 285, 289t, 292, 982

automated teller machines (ATMs)  297–8, 982, 1166, 1194 automobile loans  270, 437, 981 available stable funding (ASF)  211 Azerbaijan 1147

B

back end ratio  472 bad loans  661, 1132, 1136, 1141 Bagehot (Walter) recommendation  589–90, 603, 609, 898–9, 900 bail-ins  630–2, 656–76, 857, see also total loss-absorbing capacity (TLAC) alternatives 674–5 BHCs  632, 657, 663 bonds 175n frameworks and experience  657–61 market discipline  752–3, 754–6 meeting of objectives  666–70 objectives 656–7 and other instruments  670–3 overall consequences  673–4 regulation 1023–4 social costs and benefits  663–4, 669, 673 theoretical motivation  661–5 theoretical research  663–5 bailouts  630–55, 675–6 alternatives 674–5 and banking crises  888–90, 895 central banks  624, 625–6 costs 634 experiences 635–41 funds distributed  652 G-SIBs 95–6 incentive distortions  634 meeting of objectives  645–54 objectives 632–5 overall consequences  655 role of LOLR  603–4 social costs and benefits  631, 644, 652, 655, 663–4, 674 sovereign debt crisis  2–3 and systemic risk  856 theoretical motivation  641–4 balance sheets  370–2, 370t, 371t, 708t Banca Eutiria  1024 Banca Marche  1024

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1218   index Banca Monte dei Paschi di Siena SpA (BMPS) 660 Banca Popolare di Vicenza  660 BancAlliance 439 Banco Azteca  418 Banco de Espirito Santo  670 Banco de la Nación  1161 Banco de la Provincia de Buenos Ayres  1161 Banco del Sur  1184 Banco Espirito Santo (BES)  660, 1024 Banco Internacional do Funchal (BANIF)  661 Banco Popular  661 Banco Santander  661 Bancorp 996 Bangladesh  360, 406, 414, 417 bank assets Australia  1191, 1197–9, 1198f China 1115–16 Europe  1002, 1006 European Union (EU)  1010t Eurozone  1007, 1009t, 1010t global  39–40, 40f, 1198f Islamic banking  362 Japan 1034 New Zealand  1191, 1197–9, 1198f risk  8, 1021 UK 1191 bank branching, see branching bank capital, see capital bank consolidation Brazil 1162 Chile 1162 and hard information  444 Latin America  1154–7, 1162–3, 1169–71, 1177–9 and relationship banking  68–70 and small business lending  433, 446–51 US 991–4 bank culture and corporate governance  144–7 research studies  14–15 risk-taking 85–6 bank failures  910–24 and contagion  612–13, 918–19 and contagion versus fundamentals as causes of  911–13 and deposit insurance  693

economic consequences  692–3 in the global financial crisis  903, 910 Great Depression  913–17 Iceland 899 Ireland 899 Islamic banking  376, 379–80 Japan 1059–60 late 20th century  922–3 management and fraud  887–8 payments 312–13 pre-depression era  919–22 role of LOLR  603 US  897, 915–17, 919–21 bank holding companies (BHCs) bail-ins  632, 657, 663 bailouts  644, 666 Basel III  205 capital requirements  725t credit enhancements  515 forecasting 747 leverage ratios  727t liquidity requirements  212 ownership 255 performance 253–4 stress tests  728 supervision 749 Bank Insurance Fund  986 Bank Itaú  1155, 1157 bank levy  1209–10 Bank of Africa  1089 Bank of America  636, 993, 996 Bank of Brazil  1162 Bank of China  103, 116, 1116 Bank of Communications  1116 Bank of Cyprus  659 Bank of East Asia  1116 Bank of England  123, 328, 729, 899n Bank of Japan (BoJ)  587, 590, 1053, 1057 Bank of Montreal  919–20 Bank of New York  636 Bank of Portugal  660 Bank of US  914–15 bank performance  229–56, see also ­performance measurement China  1117–18, 1117t and competition  779t, 780–1 EU 1004–16

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index   1219 Europe 1004–16 Latin America  1169–71 non-structural approaches  252–5 structural approaches  246–52 transition countries  1145 Bank Recovery and Resolution Directive (BRRD), EU  3, 632, 658, 659, 668, 746, 753–5, 1023 bank restructuring and banking crises  898–9 Latin America  1154, 1155–7 transition countries  1136 bank runs and banking crises  44–7, 892–4 and contagion  918–19 and contagion versus fundamentals as causes of  911–13 and deposit insurance  686–7 distinguished from banking panic  858 and liquidity  78, 184n and liquidity shortages  687–8 market discipline  741–2 maturity transformation  606, 692 shadow banking  547 and systemic risk  608, 858 bank size and financial crises  455 historical trends  341–4 and local outcomes  351 post-crisis regulatory reforms  1012 and relationship banking  454–5 and small business lending  447–50 bank-borrower relationship  65–70, 197, 1056 Bankers Trust  158 Bankhaus Herstatt  312–13 banking decade following global financial crisis  1–28 emerging research themes  4–16 and the real economy  953–71 Banking Act (1933), US, see Glass-Steagall Act (1933), US Banking Act (2009), UK  753 banking and financial crises  44–51, see also sovereign debt crisis (2009–11); subprime crisis (2007) around the world  885–905 and bank runs  78

and bank size  455 and banking panics  44, 892–3 and business cycles  873 and contagion  47–51, 612, 893–4 costs 895–6 and credit booms  872–3 and debt  871 diverse origins  887–92 dynamic regulation  904–5 early history  886–7 East Asian crisis  51, 865, 891 and financial liberalization  889 and government policies  890 impact 47 information disclosure during  614–16 Japanese banking crisis  1058–62 and LOLR  898–900 macro boom and bust  890–2 Malaysian banking crisis  889 management and fraud  887–90 Mexican Tequila crisis  888 and monetary policy  623–5 and mortgages  491–4 1920s and 1930s  913–16 and regime changes  888–9 response and prevention  897–900 Savings and Loans crisis  609 and small business lending  454–5 sudden and fast-moving  892–4 and systemic risk  847–8, 863 theories to explain  44–7 Banking Code (2010), Netherlands  132 banking competition, see competition banking complexity, see Global Systemically Important Banks (G-SIBs) banking concentration Africa 1083 Australia  1192–5, 1193t Canada 1193 Eurozone 1007 Latin America  1155, 1156t, 1172–7 New Zealand  1192–5, 1193t Sweden 1193 transition countries  1137, 1144 Banking Co-partnership Act (1826), UK  328 banking globalization, see cross-border entry Banking Law (1981), Japan  1039

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1220   index banking nationalism  1141 banking panics  614 and banking crises  44, 892–3 Chicago banking panic  911, 915–16 and contagion  867 and contagion versus fundamentals as causes of  911–12 distinguished from bank run  858 Great Depression  913–17 role of LOLR  603–4 Banking Reform Act (2014), UK  1020 bankruptcy as alternative to bailouts  674–5 market discipline  753 social costs and benefits  674–5 and success of bail-ins  649 BankWest 1195 Barclays  103, 104, 328 Barings Bank  156, 888 Basel Committee on Banking Supervision (BCBS) 81n, 127–9, 708, 751–2, 753, 897, 904–5, 1180 Basel I capital requirements  194–5, 202, 708 market discipline  756, 758 risk-weighted assets (RWA)  718, 718t Basel II capital requirements  195, 202, 203f market discipline  82–4, 756–8 Pillar 3  751, 756–9 quality of capital  715–16 risk-weighted assets (RWA)  709, 718–19, 719t three pillars  751, 897 Basel II.5 reforms  719 Basel III and banking crises  898 capital distribution  731–2, 732f capital requirements  8, 84, 161, 202–7, 203f, 210, 709, 721–9, 1020–1 End Game reforms  720, 726 implementation  1, 3 Latin America  1180 liquidity creation  183 liquidity requirements  210 market discipline  756–9 mortgages 490

Pillar 3  756–9, 759t quality of capital  716, 717t, 729, 730–1, 731f quantitative impact  729–32 quantity of capital  716–17, 717t, 729, 730f re-regulation 987–8 risk weights  720, 905 shadow banking  550 three pillars  751–2, 897 BCCI 888 Bear Sterns  50, 81n, 156, 903, 986, 993 Beck, Thorsten  27, 1076–109 behavioral economics, and decision-making  814, 820, 821, 822 Belarus 1147 Belgium  10, 296, 334, 1006 Bergengren, Roy F.  332 Berger, Allen N.  1–28, 431–59 Bernanke, Ben  587, 633 BHCs, see bank holding companies (BHCs) biases cognitive 825–7 and decision-making  820–1, 825–30, 838–9 forecasting  764–5, 765t and systemic risk  852 Big Data mining (data analytics)  70 Bitcoin  13, 267, 274–5, 302, 996 Black, Lamont K.  20, 431–59 Blank, Michael  25, 953–71 Bliss, Robert R.  23, 736–68 blockchain technology  13, 263, 267–8, 274–5, 301–2 BNP Paribas  104, 117 boards of directors and corporate governance  132–3, 141–2, 147–8 diversity 142–4 independence 145 BOJ-NET payment transfers  286 Bolivia  592, 696, 1155, 1164 bonds  743, 746, 763–4 bonuses cash 137f EU bonus cap  14, 132, 137–8, 1021–2 and global financial crisis  901 and risk-taking  136–8 boom and bust, and banking crises  890–2 Boone (2008) Competition Indicator  784–5

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

index   1221 Boot, Arnoud W.A.  17, 62–87 Boot-Thakor model  42, 348 borrowing benefits and risks of securitization  520–2 consumer decision-making  816–18 Boubakri, Narjess  19, 359–99 Bouwman, Christa  18, 181–216 branching Africa 1097–9 and banking competition  794 commercial banks  982f and deregulation  983 Europe 1006 Latin America  1166 productive 982 Brazil ATMs 1166 bailouts 890 bank consolidation  1162 bank stability  1175 banking concentration  1155 competition 1173 credit 1164 development banks  1182–4 efficiency 1176 financial inclusion  1166 financial intermediation  1164 financial liberalization  1159–60, 1161 foreign direct investment (FDI)  1155 foreign-owned banks  1156, 1161, 1171 global financial crisis  1162 interest rates  1166, 1179 mergers and acquisitions  1157 private credit  1164 privatization 1169 regional banks  1155 textiles industry  964 Breuer, Peter  20, 530–65 Brexit 1025 BRICS New Development Bank (NDB)  1184 bridge bank structure  659, 660, 997, 1060 Brunei  361, 362 Bryant model  184, 605–6 BTG Pactual  1155 Buch, Claudia M.  25, 928–46 Buffett, Warren  162 Bulgaria  291, 1135, 1141

Bulte, Erwin  19, 404–25 Bundesbank  582, 583 business cycles and banking crises  44–6 and credit  871 and debt  873 and financial stability  579–80 business services after global financial crisis  988–91 offered by MFIs  421–4, 422f, 423t business strategies after global financial crisis  988f performance measurement  253–4 US 988–91 buyer of last resort (BOLR)  622–3

C

Caldwell and Co.  915 Calomiris, Charles  24–5, 910–24 CAMELS supervisory rating system  215 Canada  292, 294, 332, 696, 919–20, 1193 Cape Verde  1079 capital balance sheet  708t China 1117 definition 707–8 distribution  731–2, 732f and financial stability  495–6 human  405–6, 421–2, 424 injections of in response to global financial crisis  639, 640t Latin America  1173, 1174t quality  715–16, 717t, 729, 730–1, 731f quantity  716–17, 717t, 729, 730f research studies  8–9 tier 1  202, 715–16, 717, 717t tier 2  715, 717t capital asset pricing model (CAPM)  157–8 capital conservation buffers (CCBs) Australia 1207–8 and capital requirements  721–3, 721t, 723t countercyclical 204t, 722, 723t research studies  8 capital market funding and bank lending  70–3 and relationship banking  73 Capital Purchase Program (CPP)  615, 636

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1222   index capital ratios  193, 194f, 195, 984 capital requirements after the global financial crisis  707–33 Australia  1206–8, 1207t, 1209 and banking crises  897 Basel II  202–7, 203f Basel III  161, 203f, 715–20, 721–9, 729–32 and deposit insurance  701 Eurozone 1207t higher bank  710–11 history 708–9 and liquidity creation  190–6, 207–10 and liquidity requirements  214–15 literature review  709–15 lower bank  711–13 New Zealand  1207–8, 1207t optimal bank  713–15 regulation  84, 202–10, 1020–1 research studies  8 sectoral 496 and shadow banking  210 UK 1207t US 1207t Capital Requirements Directive II (CRD II), EU 516 Capital Requirements Directive IV (CRD IV), EU  1, 8, 14, 1020–2 capital strategies, performance measurement 252–3 capital structure and corporate governance  134–5 performance measurement  243–4 Caprio, Gerard  24, 885–906 Caribbean 582 Carletti, Elena  16, 39–57 Carmassi, Jacopo  17, 95–129 Carvalho, Fernando J. Cardim de  27, 1152–85 cash bonuses  136–8, 137f and negative interest rates  294–6 and tax evasion  291 use of  289–90, 289t, 292–3 vault  191, 192f cash cards, use of  293–4 cash reserve requirements  190–3, 192f, 196 Casu, Barbara  20, 503–26 CATFIN systemic risk indicator  174, 616, 672 causality debate  954–6

Cavallo, Finance Minister Domingo  1161 Cayman Islands  114 CBCs, see commercial bank clearinghouses (CBCs) CDOs, see collateralized debt obligations (CDOs) CDSs, see credit default swaps (CDSs) CEE, see Central Eastern Europe (CEE) Central America  1154–5, 1169 Central Bank of Brazil  1160, 1161 central banks  573–95, see also lender of last resort (LOLR) and bailouts  624, 625–6 and deposit insurance  687–8 financial stability policy  589–95 governance 581–2 independence  579, 581–2 interest rates  619f as lender of last resort  79–80, 589–90 and liquidity provision  79, 617 monetary policy  579, 582–9 science 573–81 total assets  618f transition countries  1134 Central Eastern Europe (CEE)  1132–50 bank lending  1144–5 banking sector structure  1143 financial inclusion  1148 financial intermediation  1142 CEO compensation, see executive pay Cetorelli, Nicola  20, 25, 530–65, 953–71 CHAPS payment transfers  286 Charles Schwab Corporation  352, 996 charter value  252, 642, 662 Chase Bank  361 Chavez, Hugo  1182, 1184 checks (cheques)  288, 289t, 291–2, 982 Chen, Ruiyuan (Ryan)  19, 359–99 Chicago banking panic (1932)  911, 915–16 Chicago Board of Trade (CBOT)  163 Chicago Board Options Exchange (CBOE), Volatility Index (VIX)  646 Chicago Mercantile Exchange (CME)  163 Chile ATMs 1166 bank consolidation  1162 cross-border entry  1177 deposit insurance  696

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index   1223 financial inclusion  1164, 1166 financial intermediation  1164 financial liberalization  1158–9 foreign direct investment (FDI)  1155 foreign-owned banks  1156–7 interest rates  1166 private credit  1164 China 1113–29 bailouts 889 bank assets  1115–16 bank claims on non-bank financial institutions  557, 557f, 558–9 bank performance  1117–18, 1117t capital 1117 credit booms  1115f credit intermediation  556–9 economic growth  1113 efficiency 1116–17 financial assets  1113, 1114f, 1115, 1116f financial inclusion  1126–9 financial intermediation  1122 financial sector size  1113, 1114f FinTech 1115 foreign-owned banks  1116–17 global financial crisis  1121 G-SIBs 103 and Latin America  1153, 1155 local government funding  1121, 1123–4 MMFs 558 mobile banking  1127, 1128 non-bank credit intermediation (NBCI) 556f online banking  1127, 1129 regulatory arbitrage  558 regulatory constraints  1119–21 shadow banking  533, 1118–25, 1119f, 1123 SIVs 155 structure and performance of financial sector 1115–18 traditional banking  1115 unbanked population  1127–8, 1128f wealth management products (WMPs)  155, 1118–20, 1119f, 1121, 1123, 1125 China Construction Bank  1116 CHIPS payment transfers  286, 307–9, 312–13 Citi 156 CItibank 361

Citibank Budapest  1135 Citigroup  636, 903, 986, 993, 1116 city banks  1040–1 clearing houses  688 CLS Bank, see Continuous Linked Settlement (CLS) Bank CoCos, see contingent convertible bonds (CoCos) Codetermination Act, Germany  148 collars (option positions)  165 collateralized debt obligations (CDOs)  167–8, 507, 508t, 509 collateralized loan obligations (CLOs)  513 Colombia ATMs 1166 banking concentration  1155 branching 1166 cross-border entry  1176 financial inclusion  1166 financial intermediation  1164 regional banks  1154–5 combined loan-to-value (CLTV) ratio  472 commercial and industrial (C&I) loans  648 commercial bank clearinghouses (CBCs) 614 Commercial Bank of Africa (CBA)  1103 commercial banks, see also community banks bank ratios  990t composition by size  343t consolidation  991–4, 994t defining features  322b, 326–7 deregulation 983–4 deregulation and industry consolidation 345 distribution 992f entry and exits  346–7, 347f, 349–50 and global financial crisis  984–7 historical origins  327–8 historical trends  341–4, 342f joint-stock liability  325 mortgage market share  348–50 numbers  977, 982f, 993f performance 229–31 profitability 1011 ratios 984f services 979 today 328 versus universal in Japan  1052

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

1224   index commercial loans  647 commercial paper (CP)  154–5, 200, 535, 978, 981–2, 1034 commercial real estate (CRE) bonds  549 commercial real estate (CRE) loans  437, 647–8 Commodity Futures Trading Commission (CFTC) 162 Commonwealth Bank of Australia (CBA)  1192, 1195 community banks accessibility and social implications  350–3 competition 346 composition by size  343t current challenges  353–4 decline 992 defining features  321, 322b, 326 deregulation and industry consolidation 344–6 dominance 980 entry and exits  346–8, 347f, 352 financial and technological innovations  348–50, 353–4 historical trends  341–4, 342f institution types  326–35 local specialization  335–40 mergers and acquisitions  344–6, 345f regulation 350 resilience 325–6 services 980 transformation in market structure  341–50 Community Development Capital Initiative (CDCI) 636 Compartamos, Mexico  413 compensation in banking  135–40 competition 776–805 Africa 1083 Australia 1192–5 and bank strategy  788–94, 796–7 Brazil 1173 and capital market funding  73 and community banks  346 and conduct  788–94 definition 776 and deposit insurance  694 and deregulation  801

effects of cross-border entry  940–2 Europe  800, 1014–16 and financial stability  797–801 and industries  960–3 and information sharing  802–5 Japan 1046–7 Latin America  1172–3 market structure and conduct  788–94, 795–6 measurement 777–88 and microfinance  415 New Zealand  1192–5 in providing payment services  300–1 and regulation  794–801 and relationship banking  68–70 role in real economy  959–60 and small business lending  433–4, 451–3 and success of bailouts  651, 654 competition-fragility hypothesis  797–8, 799, 1016 competition-stability view  798, 799, 1016 complaints 300 Composite Indicator of Systemic Stress (CISS), ECB  869 Comprehensive Assessment, Europe  641 Comprehensive Capital Analysis and Review (CCAR)  456, 638, 728 concentration, see banking concentration Conditional Value at Risk (CoVaR)  11, 173, 315, 616, 645, 868–9 conduct and competition  788–96 and complaints  300 misconduct  145, 1210–11 and regulation  796 conflicts of interest  76 conforming loan limit  485 conjectural-variations method  778, 785–6, 790–1, 795 consolidation, see bank consolidation Constant Net Asset Value (CNAV) MMFs 550–1 constant-money-growth rule  583 Consumer Financial Protection Bureau (CFPB)  15, 987 consumer protection  15 consumers, financial decisions  814–34

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index   1225 contagion and bank failures  612–13, 911–13, 918–19 and banking crises  893–4 domino effect perspective  612–13 empirical evidence  867–70 and financial crises  47–51 and financial innovation  48–9 versus fundamentals as causes of bank failures 911–13 and global financial crisis  50–1 illiquidity  175, 612 illiquidity view  613–14 information disclosure  614–16 and lender of last resort  611–17 and liquidity shocks  48–9, 607–9, 859, 870 measuring links between financial institutions 616–17 microeconomic studies  918–19 and systemic crises  611–17 and systemic risk  850, 858–62 Continental Illinois bank  868, 893 contingent convertible bonds (CoCos)  175n, 670–3 Continuous Linked Settlement (CLS) Bank  286, 312–13 contract terms flexibility 66–7 intertemporal smoothing  66 and success of bailouts  650 and systemic risk  853 contracts co-signing 408 microcredit 419–20 contractual saving  818 Convertibility Plan (Cavallo Plan), Argentina 1161 Cooperative Bank of Peloponnese  659 cooperative banks  328–31 defining features  322b, 328–9 historical origins  329 today  329, 330t, 331 Corpbanca 1155 Corporacion Andina de Fomento (CAF) 1181–2 corporate complexity, see Global Systemically Important Banks (G-SIBs) corporate debt  166, 521

corporate governance  131–48 and bank culture  144–7 and bank performance  246–7 of banks  131–3, 147–8 boards of directors  132–3, 141–2, 147–8 difference between banks and non-banking institutions  131–3, 134–5 Islamic banking  380 policy implications  147–8 research studies  14–15 role of banks  53–4 shareholder-orientated 141–2 corporate sector purchase program (CSPP) 1019 corporate social responsibility (CSR)  382 costs of banking crises  895–6 payments 296–7 cost-to-income ratios  1202–3, 1202t countercyclical capital buffers (CCyBs)  204t, 722, 723t Countrywide Financial Corporation  482 CoVaR, see Conditional Value at Risk (CoVaR) covered bond purchase program (CBPP)  1019 CRAs, see credit rating agencies (CRAs) credit costs 1167 daylight 310–11 and decision-making  816–18 Latin America  1163–4, 1167, 1177–9 transition countries  1138 US 980 credit booms  492–6, 864–6, 871–3, 1113–14, 1115f credit bubbles  593–4 credit cards costs  296–7, 300 and decision-making  823 increase 982 interchange fees  298–9 loans 270 rationality of use  831–4 reasons for  292 and securitization of debt  506 security 301 use of  285, 289t

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1226   index credit cooperatives  1044–5 credit crunches global  894, 901–3 Japan  1061–2, 1063–5 Latin America  1178 Spain 873 credit default swaps (CDSs)  165–9, 743–4, 746–7 credit derivatives  166–9, 517 credit enhancements  515–16, 517f, 541 Credit Guarantee Corporation Law, Japan 1058 credit guarantee corporations (CGCs)  1058 credit guarantees  455–6, 542 credit intermediation chain 536f China  556–9, 1122 financial innovation  537–9 and shadow banking  536f, 537 Crédit Lyonnais  888 Crédit Mobilier  328 credit rating agencies (CRAs) and banks  75–7 and global financial crisis  900–1 problems  549, 553–4 regulatory reforms  552 role in financial systems  64 and securitization  513, 525 Credit Rating Agency Reform Act (2006), US 77 credit registries  802–5, 872, 1096 public 803–4 credit reporting  348–9 credit risk  155–6 contagion 48–9 Islamic banking  379 management 489–90 measurement 160–1 and risk-weighted assets (RWA) 718–19, 720 success of bailouts  647 credit scores financial innovation  348–9 model 161 for mortgages  473f past reaction to  995 small business (SBCS)  266–7, 1057

credit shocks  5–7 credit spreads  763–4 Credit Suisse  103, 1012 credit supply research studies  6–7 and residential mortgages  494 success of bailouts  647–50, 653–4 and systemic risk  857 Credit Union National Extension Bureau  332 credit unions, see also community banks and competition  991–2 composition by size  343t defining features  322b, 331–2 deregulation and industry consolidation 344–6 entry and exits  346–7 expansion 353 historical origins  332 historical trends  341–4, 342f and mortgages  350 numbers 993f tax subsidies  340, 350 today 332–3 CreditMetrics 161 creditors, and corporate governance  131, 134–5, 147–8 crises, see banking and financial crises; sovereign debt crisis (2009–11); subprime crisis (2007) crisis management  855, 875, 903, 1017–18 crisis management group (CMG)  121–2 Croatia  1140, 1143 cross-border entry  924–46 Africa 1106–8 and banking globalization  929–35 changing patterns in complexity  934–5 determinants of through acquisitions 935–40 effects on efficiency and competition 940–2 effects on risk  942–4 Latin America  1176–8 Mexico 1176–7 through mergers and acquisitions  929–34 cross-border payments  302 cryptocurrencies  13, 263, 267, 274–5, 301–2, 996–7

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index   1227 Cull, Robert  27, 1076–109 culture, see bank culture Cyprus  3, 658–9, 667, 668, 669, 697, 903, 1003 Cyprus Popular Bank (Laiki Bank)  659 Czech Republic  1143, 1148 Czechoslovakia 1135

D

data and data-processing and competition  70 on corporate complexity  127–9 daylight credit  310–11 daylight overdrafts  309–10 de Bandt, Olivier  24, 847–75 de Larosière Report  1018 de novo banks  1136 debit cards costs 296–7 increase 982 interchange fees  298–9 reasons for  292 security 301 use of  272–3, 285, 289t, 290 debt and banking crises  871 corporate  166, 521 government 51 inside debt  140 rationality of  831 yields 745–7 debt instruments in Islamic banking  367, 368–9, 368t debt-based compensation  140 decision-making biases 838–9 cognitive biases  825–7 consumers’ financial  814–34 extensiveness of decision processes  815–19 fast and frugal heuristics  837–8 financial 816–18 framing 821 heuristics and biases  820–1 for household durables  816–18 and hyperbolic discounting  823–5 investment and borrowing  816–18 market environments  838–9 and mental accounting  822–3

prospect theory  821–2 rationality 819 rationality of credit card use  831–4 savings 818–19 Degryse, Hans  23, 776–805 delegated monitoring role of banks  42, 53–4 DeLong, Gayle L.  25, 928–46 Delta CoVaR  173 demand deposits Amanah 370 and banking crises  892–3 and liquidity  688 and maturity transformation  686 Demirgüç-Kunt, Asli  22, 685–703 Democratic Republic of the Congo (DRC) 1090 Denmark  334, 582, 693 deposit funding  1143, 1144t, 1146t deposit insurance  685–703 Australia 1205 and bank failures  693, 922–3 and bank runs  686–7 countries with  689–92, 689f, 690f, 692f coverage limits  698–9 covering bank liabilities  691, 691f design and the institutional environment 698–702 economic benefits  692–4 economic costs  694–8 economic rationale  686–8 and guarantees  135 history of adoption and changes  688–92 increasing integration of banks and financial markets  85 and moral hazard  688, 694–8, 699 regulation 701 risk-based pricing  699–701, 700f supervision 701 and withdrawal risk  184 Deposit Insurance Corporation, Japan  1053, 1060 deposit markets  791–3 Depository Institutions Deregulation and Monetary Control Act (DIDMCA) (1980), US  191, 335, 346, 983 Depository Trust and Clearing Corporation 313

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1228   index deposits Australia 1195–6 demand  370, 686, 688, 892–3 Latin America  1164 New Zealand  1195–6 deregulation and banking competition  801 and commercial banks  983–4 and community banks  339–40, 344–6 and entrepreneurship  961–3 Europe 1004–11 increasing integration of banks and financial markets  83–4 real economy  956–7 US  5, 983–4 derivatives, and risk-taking  162–9 Desjardins, Alphonse  332 Deutsche Bank  103, 104, 300, 758 Development Bank of Japan  1046 development banks  1181–4 Dexia bank  638 DeYoung, Robert  25–6, 977–98 Dhan Foundation  414 diabolic loop link  620 Diamond model  42 Diamond-Dybvig model  47, 78–9, 184, 186–7, 213, 547, 605–6, 607, 610, 687–8, 695, 911 digital currencies  292–4 direct market discipline  739, 740 disclosure information 614–16 and Pillar 3  757–9, 759t discount brokerage  995–6 discount windows and bank failures  916–17 and global financial crisis  985–6 lending  308, 604 and liquidity  10, 182, 185 and regulation  189 response to financial crises  637 stigma 615 discounting, and decision-making  823–5 discrete choice models  787, 872 discretionary saving  818–19 distributed ledger technology  267–8

diversification boards of directors  142–4 and contagion  50 Europe 1012 G-SIBs  104, 105t and risk-taking  232–5, 232f Dodd-Frank Act Stress Test (DFAST)  728 Dodd-Frank Wall Street Reform and Consumer Protection Act (2010) (DFA) bail-ins 657 capital requirements  8, 210 compensation 14 credit rating agencies  77 financial markets integration  84 implementation 3 market discipline  752, 753 regulatory changes  456–7 repeal of certain provisions  674 re-regulation 987 resolution authorities  123–4 resolving large banks  997–8 securitization 516 Dominican Republic  887–8 domino effect perspective  612–13 Donaldson, Piacentino and Thakor model  182, 185–7, 193, 207, 213 Dow Jones CDX (DJ CDX)  167 Draghi, Mario  6, 622 Dubai Islamic Bank  360 Dun and Bradstreet  349 Dybvig, see Diamond-Dybvig model dynamic incentives, joint liability lending  410, 413, 415 dynamic model of bank runs  46 dynamic provisioning  6, 457, 496

E

E*Trade 996 earnings quality in Islamic banking  381–2 Eastern Europe  1132–50, see also Central Eastern Europe (CEE) bailouts 641 credit unions  332 global financial crisis  1178 information sharing  802

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index   1229 interest rates  1167 non-performing loans  889 relationship banking  351 retail banking  1005 ECB, see European Central Bank (ECB) Ecobank 1089 ECOFIN Council  3 econometrics, and market discipline  763 economic activity, see real economy Economic and Monetary Union (EMU)  1002 economic behavior  815–30 economic costs of banking crises  895–6 economic growth credit booms  1113–14 and Islamic banking  386–8 Economic Growth, Regulatory Relief and Consumer Protection Act (2018), US  457 economic role of banks  64–8 economies, importance of banks  39–41 economies of scale Australia 1195 and bank competition  938 and bank consolidation  991 and bank performance  247–52 financial institutions  247–52 impact 433 importance 1011–12 Japan 1047–8 large banks  437, 449, 981, 1011–12 Latin America  1162, 1185 risk-taking 232–5 shadow banking  535 economies of scope and bank competition  794–5 and cross-border entry  940 Europe  1005, 1012–13 financial institutions  247–9, 254 Japan 1048 Latin America  1185 Ecuador  582, 1155, 1164, 1166 Edge Act (1919), US  113 efficiency Africa  1082–3, 1087 Australia 1200–4 China 1116–17 effects of cross-border entry  940–2

Europe 1011–14 Islamic banking  372–6, 373t Japan 1047–52 Latin America  1170–2, 1175–7, 1175t Mexico 1173 New Zealand  1200–4 and success of bailouts  650 efficiency structure hypothesis  779–81, 1172 efficient markets hypothesis  740 El Salvador  582 electronic payments  303, 982 Elliehausen, Gregory  23, 814–40 Emergency Economic Stabilization Act (2008), US  635–6 emergency liquidity assistance (ELA) conditions for provision  609–10 and financial crises  608 and global financial crisis  603–4 and LOLR  620, 859 and systemic risk  855, 875 Emigrant Savings Bank of New York  918 employment Europe 1006 and success of bailouts  649 endowment effect  826 enhanced supplementary leverage ratio (eSLR) 725–6 Enron  76, 76n enterprise access to finance  1089–91, 1090f entrepreneurship and bank competition  961–3 and Islamic banking  388 equipment lending  437 equity, and banks  74–5 Equity Bank  1086, 1088–9, 1097–8 equity instruments in Islamic banking  367, 368t equity prices, and monitoring  748–9 equity-based compensation  138–40 Estonia  1142, 1143, 1144 Ethiopia  1092, 1099–100 euro (currency)  622, 1000 Euro Area, see Eurozone Euro crisis, see sovereign debt crisis (2009–11) Euro1 payment transfer  286

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1230   index Europe  1000–26, 1190–211 bail-ins 632 bailouts  631, 635–8, 640t, 652–4 bank assets  1006 banking reform  964 banking union  1004, 1018, 1022–5, 1141 cash use  290–1, 292 checks (cheques)  288–9, 292 commercial banks  326 competition  800, 1014–16 cooperative banks  329, 330t, 331 credit unions  332 deregulation 1004–11 diversification 1012 efficiency 1011–14 employment in banking  1006 financial inclusion  1092f funding sources  1197 global financial crisis  638, 901, 1016–19 government support  1017 industries 964 integration  1004–11, 1007f joint stock banks  328 large banks  1011–12 leverage 134 mergers and acquisitions  1005, 1007, 1011 MMFs 551 new regulatory architecture  1019–25 numbers of banks  1006 payment services  286 post-crisis business models  1012 post-crisis regulatory reforms  1012 profitability  1011–14, 1015t risk 1014–16 savings banks  334 securitization  509–11, 510f, 552 SEPA initiative  298 small business lending  431, 454, 456, 458 sovereign debt crisis., see sovereign debt crisis (2009–11) stress tests  729 structure and performance of banking 1004–16 universal banking model  1001 European Banking Authority (EBA)  1018, 1022 European banking union  1004, 1018, 1022–5, 1141

European Central Bank (ECB) bail-ins 658 bailouts 3 and banking union  1004, 1018, 1022–3, 1141 establishment 1000 LOLR policy  622–3 long-term refinancing operations (LTROs) 10 outright monetary transactions (OMT)  6 research studies  6 response to sovereign debt crisis  1018–19 supervisory role  590 total assets  618f European Commission  1002 response to global financial crisis  638–9, 641, 1002, 1017 European Company Statute  1005 European deposit insurance scheme (EDIS)  1004, 1025 European Economic Community (EEC)  1000 European Financial Stability Facility (EFSF)  3, 639, 1003 European Insurance and Occupational Pensions Authority (EIOPA)  1018 European Securities and Markets Authority (ESMA) 1018 European System of Financial Supervisors (ESFS) 1018 European Systemic Risk Board (ESRB)  81, 550, 1018 European Systemic Risk Council (ESRC) 1018 European Union (EU) bail-ins  658–61, 666–70 bailouts  638–41, 640t bank assets  1002, 1010t Bank Recovery and Resolution Directive (BRRD)  3, 632, 658, 659, 668, 746, 753–5, 1023 banking integration  1001 banking structure  1004–16 banking supervision  1001 Basel II  196 bonus cap  14, 132, 137–8 capital requirements  205 Capital Requirements Directive II (CRD II) 516

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index   1231 Capital Requirements Directive IV (CRD IV)  1, 8, 14, 1020–2 competition 803 Council of Finance  1018 deposit insurance  690, 694 expansion 1000–1 FinTech 12 First Banking Directive (77/780/EEC) (1977)  1001, 1004 government support to banks  1002–3 house prices  492–3, 493f large banks  1007, 1010t market discipline  754–5 mortgage credit tools  495 numbers of banks  1008t Payment Services Directive 2 (PSD2)  269, 300 Recovery and Resolution Directive (2014), EU 1020 regulatory reforms  753–4 Second Banking Directive (89/646/EEC) (1989)  964, 1001–2, 1011 single market  328 single resolution mechanism (SRM)  1004 single supervisory mechanism (SSM)  1004 White Paper on The Completion of the Internal Market  1001 Eurozone bank assets  1002, 1007, 1009t, 1010t banking concentration  1007 capital requirements  1207t economies of scale  249–50 expansion 1001 financial services  1191 financing structure  39–41, 40f household assets  40–1, 41f implementing LOLR policy  621–3 large banks  1010t liquidity creation  620 low interest rates  592 non-financial corporations  41, 41f numbers of banks  1007, 1008t pension schemes  40 risk-sharing 43 shadow-banking 533 sovereign debt crisis., see sovereign debt crisis (2009–11)

evergreening 1065–6 exchange rates  582–3 executive pay, see also bonuses compensation 136–40 regulation 1020–1 and risk-taking  135–40 exposure at default (EAD)  489 extreme-value theory (EVT)  868

F

failures, see bank failures Fair, Isaac and Co. (FICO), see FICO (Fair, Isaac and Company) scores Fair Credit Reporting Act (1970), US  348 Faisal Islamic Bank of Egypt  360 Faisal Islamic Bank of Sudan  360 fake warehouse receipts  185–6 Fannie Mae  485, 490, 505, 903, 986–7 Fast Pay payment transfer  308 fast payments  24/7 302–3 Federal Credit Union Act (1934), US  332, 341 Federal Deposit Insurance Corporation (FDIC)  84, 123–5, 327, 347, 637, 657, 689, 986, 997–8 Federal Deposit Insurance Corporation Improvement Act (FDICIA) (1991), US 195 Federal Deposit Transaction Account Guarantee Program (TAGP)  637 federal funds market  185 Federal Home Loan Bank (FHLB)  349, 551, 637 Federal Home Loan Mortgage Corporation (FHLMC), see Freddie Mac Federal National Mortgage Association (FNMA), see Fannie Mae Federal Reserve automated clearinghouse (ACH)  982 banking panics  604 cash reserve requirements  190–3 and commercial banks  984 discount window., see discount windows establishment 288 forward guidance  588 global financial crisis  50–1, 637, 985–6, 987 independence 582 liquidity creation  620, 621t

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1232   index Federal Reserve (cont.) liquidity provision  80 and living wills  124–5, 657 as LOLR  185, 190 monetary policy  591 Regulation Q  980, 983 stress tests  728–9 supervisory role  590 systemic risk  308–9 term auction facility (TAF)  10 total assets  618f Federal Reserve Act (1914), US  135 Fedwire payment transfer  286, 306 fiat currency  892 FICO (Fair, Isaac and Company) scores  271, 348, 438, 443, 549, 981, 995 Fidelity 996 Filene, Edward  332 Final Report of the High-level Expert Group on Reforming the Structure of the EU Banking Sector, see Liikanen Report, EU Financial Access Survey database (FAS)  16 Financial Accounting Standards Board (FASB), US  539 financial assets banks’ share  977 China  1113, 1114f, 1115, 1116f distribution  977–9, 978t Japan  1034, 1035t, 1037f, 1039, 1040f residential mortgages  483–8 Financial CHOICE Act (under consideration), US 674 Financial Claims Scheme (Australian Government Deposit Guarantee)  1204, 1205–6 financial contagion, see contagion financial crises, see banking and financial crises; global financial crisis (2007–9) financial development Africa  1078–96, 1080f Islamic banking  386–8 financial education intervention studies  834, 836–8 financial fragility hypothesis  850–2 financial imbalances  850

financial inclusion Africa  1080, 1082, 1082f, 1086, 1091–6, 1092f, 1093t, 1094f, 1095f, 1096–104 China 1126–9 Islamic banking  388 Kenya 1088–9 Latin America  1163–9 and payments  303–4 research studies  15–16 transition countries  1145, 1147–50 financial innovation Africa 1096–7 and community banks  348–50 and contagion  48–9 definition and determinants  263–5 organizational forms  275–8 processes 265–9 products 269–75 shadow banking  531, 537–9 and technological innovation  262–79 US 980–3 financial institutions increasing integration with banks  62–87 measuring links between  616–17 performance 229–56 risk sharing  45 Financial Institutions Recovery and Reform Act (1989), US  349 financial intermediaries, see also shadow banking Great Recession  966–70 growth rate  534f market discipline  762–3 private information  172 role 530 and shadow-banking  533f share of assets  977–9, 978t financial intermediation Latin America  1164 theory 65 transition countries  1142–3 financial liberalization Argentina 1160–1 and banking crises  889 Brazil 1161 Latin America  1158–60

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index   1233 financial literacy behavioral studies  837–8 effects on behavior  835–7 and microfinance  421 research studies  15, 834–5 financial markets different economies  39–41, 40f increasing integration with banks  62–87 and liquidity provision  79 market discipline  82–5 and risk sharing  45, 80 financial services  1191 Financial Services Action Plan, Europe  1005 Financial Services Agency (FSA), Japan  1053, 1060 Financial Services Authority, UK  614 financial stability Africa 1083–4 and asset management  562–3 and business cycles  579–80 and competition  797–801 and credit intermediation  556–9 and FinTech  564–5 Islamic banking  376–80 market discipline  736–8 and mortgages  491–6 and payments  314–15 prime brokerage  563–4 and regulation  797–801 and securitization  524 shadow banking  542–4 and structured leverage finance  559–61 Financial Stability Board, G20  96–7, 118, 120, 122–3, 127–9, 531–3, 549–50, 753, 1180 Financial Stability Oversight Council (FSOC), US  81 financial stability policy  589–95 and financial supervision  590–1 and liquidity provision  589–90 and monetary policy  591–5 financial statement lending  437 financial sustainability perspective  425 financial system inquiries (FSI)  1208–9 financial systems bank-based versus market-based  52–3, 69 causality debate in real economy  954–6

composition of liabilities of financial business  537–9, 538f residential mortgages as a vulnerability 491–4 role of banks  39–57 role of credit rating agencies  64 financing, and competition  801 financing structure of different ­economies  39–41, 40f Finca DRC  1098 Finland 329 FinTech China 1115 definition 438 development 263 and efficiency  1013 financial stability risks  564–5 and future of banking  995–7 investment 354 marketplace lenders  277–8 and mortgages  278 and payment services  300 process innovations  267–9 product innovations  274–5 research studies  12–14 US 995–7 FinTech lending  354, 438–9, 442–3 fire sales  861, 869–70 First Banking Directive (77/780/EEC) (1977)  1001, 1004 fiscal costs of banking crises  895–6 Fiscal Investment Loan Program (FILP), Japan 1045 fiscal policy  856 fixed rate mortgages  471, 478–9, 479f fixed-asset lending  437 fixed-for-floating rate swaps  165 Flannery, Mark J.  23, 736–68 Fobaproa, Mexico  1159 Ford 167 forecasting biases  764–5, 765t market discipline  747–8 foreclosure (mortgages)  473–5, 474f, 481–3 foreign bank entry, see cross-border entry foreign direct investment (FDI)  1155

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1234   index foreign-owned banks Africa  1089, 1106–8 Argentina  1156, 1161, 1171 Brazil  1156, 1161, 1171 Chile  1156–7, 1177 China 1116–17 and competition  796–7 Japan 1044 Kazakhstan 1137 Latin America  1154–7, 1156t Mexico  1155, 1156, 1161–2, 1169–70 Russia 1137 and small business lending  451 Soviet Union  1137 transition countries  1135–9, 1143, 1144–5 Fortis bank  638 forwards (financial futures)  163–4 fragile banks  78–80 Frame, W. Scott  18, 262–79 framing, and decision-making  821 France bank assets  1002 banking reform  964 checks (cheques)  292 credit and debit cards  292 guarantees 1017 joint stock banks  328 recapitalizations 1017 savings banks  334 fraud, and banking crises  887–90 Freddie Mac  485, 490, 505, 903, 986–7 Freixas, Parigi and Rochet model  47–8, 608, 609–10 Freixas, Xavier  21–2, 602–26 Friedman, Milton  575, 913–15, 918 Friedman-Phelps natural rate hypothesis  576 fundamentals, versus contagion as causes of bank failures  911–13 funding fragilities, and shadow banking  547 funding sources Australia  1195–7, 1196t global  1195–7, 1196t New Zealand  1195–7, 1196t securitization 71 funding uses Australia 1197–200 New Zealand  1197–200

Fungáčová, Zuzana  27, 1132–50 future of banking  995–8 futures  162, 163–4, 165n

G

G20 (Group of 20 Heads of State), and G-SIBs  96–7, 100, 118–19 Garn-St.Germain Act (1982), US  191, 335, 346, 983 gender, and board of directors  143–4 gender gap Africa  1092–6, 1094f, 1095f transition countries  1147–8 General Motors  166, 167 Germany bailouts  639, 641, 653, 654 banking concentration  1007 banks and growth  52 cooperative banks  329 credit and debit cards  292 cross-border entry  936 deposit insurance  691, 696 employment in banking  1006 guarantees 1017 Hausbank system 54 joint stock banks  328 monitoring role of banks  54 recapitalizations 1017 savings banks  334–5 Ghana 1100 Gharar (speculation)  359, 365–6, 376 Ginnie Mae  485, 505 giro transactions  285, 287–9, 290–1, 292, 297, 305 Glass-Steagall Act (1933), US  84, 113, 339, 980, 984 global finan cial crisis (2007–9) Africa  1083, 1084 Argentina 1162 Australia 1204–6 and bailouts  95–6, 635–8 and bank failures  903, 910 Brazil 1162 China 1121 and commercial banks  328 and contagion  50–1 and credit booms  872–3

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index   1235 Croatia 1140 a decade after the  2–4 effects 51 and emergency liquidity assistance (ELA) 603–4 Europe 1016–19 Hungary 1139–40 and Islamic banking  377–80, 378t Japan 1062–3 Latin America  1153, 1162–3 and mortgage policies  495 New Zealand  1204–6 reasons 51 regulation 904–5 role of LOLR  625–6 Russia 1140 and securitization  72, 900–2 and small business lending  434, 453–8 and systemic risk  176–7, 850 transition countries  1138–40 Ukraine 1140 US  635–8, 900–4, 984–7 views on systemic crisis  611–12 Global Financial Inclusion Database (World Bank)  16, 304 global games theory  46, 48, 860 global investment banks  994t global systemically important banks (G-SIBs) accounting principles and practices  114 after the global financial crisis  99–113 asymmetric information  115 bail-ins 666 bailouts 95–6 capital requirements  205–7 capital surcharges  723–6, 725t changes to business models  1012 classification 95n corporate complexity  95–129 cross-border complexity  104, 105t, 120–2 data and data-processing  127–9 definition 723–4 drivers of corporate complexity  113–18 enhanced supplementary leverage ratio 725–6 geographical diversification  104, 105t and globalization  934–5 leverage ratios  726–7, 730f

listed 176t mergers and acquisitions  115 and non-financial corporations  116–18 policies to enhance resolvability  118–25 quantity of capital  730f regulation  3, 113 regulatory changes during and after  456–7 and resolution authorities  119–25 risk-based capital  724 size and complexity  100, 101t, 103–4 subsidiaries  104, 107t, 112t, 116–18 surcharges 206t and systemic risk  175–6 and systemic stability  97–9 taxation 113–14 total loss-absorbing capacity (TLAC) 727–8 in 2017  724t US  111, 112, 113 globalization, see cross-border entry Goddard, John  26, 1000–26 Goldman Sachs  111, 116, 156, 159, 439, 636, 986 governance, see corporate governance government debt  51 government guarantee lending programs 1057–8 Government National Mortgage Association (GNMA), see Ginnie Mae government policies and banking crises  890 and community banks  339 government regulation  979–80 government subsidies  340 government support after global financial crisis  1002 Australia 1204–6 Europe 1017 New Zealand  1204 for small business lending  455–6 government-issued digital currencies  292–4 government-sponsored enterprises (GSEs)  485–6, 487f, 490, 506, 554 Grameen Bank  406, 414 Grammen Pension Scheme  414 Gramm-Leach-Bliley Act (1999), US  113, 745–6, 984, 986 Great Depression  575, 580, 912, 913–17

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1236   index Great Recession  314–15, 965–70 Greece bail-ins  659, 1024 bailouts 3 banking concentration  1007 banking in pre-modern era  954 and global financial crisis  903–4 savings banks  334 sovereign debt crisis  1003, 1018 Greece, Ireland, Italy, Portugal, Spain (GIIPS)  3, 622, 623, 639 Greek Resolution Fund  659 Greenspan, Alan  592 Greenspan put  592 group lending  406–12 growth, role of banks  52–3 Guarantee Scheme for Large Deposits and Wholesale Funding, see Australian Government Guarantee Scheme guarantees bank liabilities  639 off-balance sheet  648 response to global financial crisis  640t risk-taking 134–5 success of bailouts  653, 654 Guedhami, Omrane  19, 359–99 Guinea 899

H

Hagendorff, Jens  17, 131–48 hard information and bank consolidation  444 and bank size  449–50 and small business lending  432, 435, 436–7, 443–6 Hartmann, Philipp  24, 847–75 Hasan, Iftekhar  27, 1132–50 Hayne, Kenneth Madison  1210 hedge funds  75 Herring, Richard J.  17, 95–129 heuristics decision-making  816, 820–1, 827–30, 838–9 fast and frugal  837–8 high leverage  892–3 high-quality liquid assets (HQLA)  211–12, 564 Hokkaido Takushoku Bank  1060

Home Affordable Modification Program (HAMP) 482–3 Honohan, Patrick  24, 885–906 Hoover, President  917 house price bubble Australia and New Zealand  1194–5, 1200 household assets  492–3, 492f house prices and credit supply  494 and global financial crisis  985 and household assets  492–3, 492f, 493f and mortgages  477–8, 478f, 489 household assets and asset price bubbles  492–3, 492f different economies  40–1, 41f US 980 household durables, and decision-making 816–18 households risk-sharing role  42–4 success of bail-ins  668–9 housing policies  986–7 HSBC  117, 156, 328, 361, 758, 1116 Hughes, Joseph P.  18, 229–56 human capital, and microfinance  405–6, 421–2, 424 Humphrey, David  19, 285–316 Hungary banking nationalism  1141 banking system  1134 barriers to financial exclusion  1148 barriers to financial inclusion  1149 foreign-owned banks  1135 global financial crisis  1139–40 hyperbolic discounting, and decision-making 823–5

I

Iceland bailouts 895 bank failures  899 currency mismatches  901 deposit insurance  697 and global financial crisis  901 LOLR policy  622 Ijara contracts  368, 368t, 369, 371 IKB Deutsche Industriebank  1016–17

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index   1237 illiquidity and contagion  175, 612, 613–14 distinguished from insolvency  609–11, 665, 688, 893, 913–17 Islamic banking  385t incentives, systemic risk  852 income gap, Africa  1092–6, 1094f, 1095f Index of Small Business Optimism  458 India  404, 420 indirect market discipline  739, 763 individual lending, and microfinance  412–15 Indonesia 899 Industrial and Commercial Bank of China 1116 industrial organization new empirical (NEIO)  781–8 traditional 778–81 industries, and bank competition  960–3 IndyMack 606 inflation and benefits of stability  574 and monetary phenomenon  575 targeting 584–6 and unemployment  575–6 influence, market discipline  738–9, 740–2, 749–50 information adverse 78 asymmetric., see asymmetric information and community banks  336–9 costs 936–7 and dynamic regulation  905 hard 337–8 private 169–72 sharing 802–5 soft  67, 337 systemic events  853–4 information disclosure  614–16 information processing  64–70 initial coin offerings (ICOs)  274–5 inside debt  140 insolvency, distinguished from ­illiquidity  609–11, 665, 688, 893, 913–17 insolvency shocks  870 institutional culture  145–6 Institutional Microfinance Fund  413 instrument rules  583–4

insurance deposit., see deposit insurance life 414 liquidity 79 and microfinance  414 microinsurance 1100 rainfall 1100 reinsurance 76–7 state-sponsored 688–9 insurance schemes, state-sponsored  688–9 InterAmerican Development Bank (IADB)  1183, 1184 interbank exposure, and contagion  867–8, 870 interbank linkages, and contagion  50 interbank markets, and systemic risk  858–61 interchange fees  298–9 interconnectedness and systemic risk  314–15, 852–3 too-interconnected-to-fail ­(interconnectedness)  643–4, 663 interest rates and cash  294–6 and decision-making  817–18 East Asia and the Pacific  1167 Latin America  1166–9, 1167t, 1168t, 1179 and LOLR policy  617–18, 619f and monetary policy  580–1 and mortgages  478–9, 479f negative 294–6 and rationality of credit card use  831–2 and risk-taking  591–4 zero-lower-bound problem  580–1, 585–6 Intermediate Holding Company Rule (2014), US 113 International Air Transport Association (IATA) 300 international coordination, increasing integration of banks and financial markets 81–2 International Financial Institutions (IFIs) 1139–40 International Index Company (IIC), iTraxx 167 International Islamic Financial Market (IIFM) 361

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1238   index International Monetary Fund (IMF)  3, 16, 550, 690, 699 international payments  286–7 Internet bubble  492, 492f Internet-based payments  983 Internet-only banks  276 Intesa Sanpaolo bank  660 investment benefits and risks of securitization  522–3 consumer decision-making  816–18, 830 market discipline  741–2, 760 measurement of opportunities  252 investment banks  994t Iran  360, 361, 362 Ireland bailouts  3, 638, 641, 895 bank assets  1002 bank failures  899 deposit insurance  691, 699 and global financial crisis  901 guarantees 1017 LOLR policy  621 sovereign debt crisis  1003, 1025 Islamic banking  359–99 balance sheets  370–2, 371t characteristics  365–72, 367t compared with conventional banks  372–85, 373t, 374t, 378t, 386–9 corporate governance  380 corporate social responsibility (CSR)  382 definition 359 differences with conventional ­banking  367t, 370–2 directions for future research  389–91 and earnings quality  381–2 and economic growth  386–8 efficiency  372–6, 373t and entrepreneurship  388 and financial development  386–8 and financial inclusion  388 financial products  366, 367–9, 368t financial strength  375–6 and global financial crisis  377–80, 378t growth around the world  360–5 lack of standardization  390 liquidity creation  382–3, 384t and market discipline  388–9

market share by country  361, 362f numbers of banks  362, 363f population increase  365, 365f profitability 372–6 and risk  390–1 share of total banking assets  362, 364f stability 376–80 stock liquidity  383, 384, 385t summary of literature  392 total assets  362, 363f Islamic Development Bank (IDB)  360 Islamic Financial Services Board (IFSB)  361, 380 Istisna contracts  368t, 369 Italy bail-ins  659–60, 667, 668 bank failures  923 banking in Roman era  953–4 competition  788, 790–1, 793 credit and debit cards  292 relationship banking  351–2 savings banks  334 sovereign debt crisis  622, 623

J

JA Bank (Japan Agriculture Bank)  1045 Jacklin and Bhattacharya (1988) model  44–5 Japan 1033–66 bank assets  1034, 1191 bank failures  1059–60 bank types  1040–6, 1042t, 1049t cash use  291 city banks  1040–1 commercial versus universal  1052 competition 1046–7 cooperatives 1045 corporate assets and liabilities  1034, 1037f, 1040f credit cooperatives  1044–5 credit crunch  1061–2, 1063–5, 1065f efficiency  1047–8, 1052 evergreening 1065–6 financial assets  1034, 1035t, 1039, 1040f financing structure  40–1, 40f foreign banks  1044 funding sources  1196–7 global financial crisis  904, 1062–3, 1064f

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index   1239 government assets and liabilities  1034, 1037f, 1040f government guarantee lending programs 1057–8 household assets and liabilities  40–1, 41f, 1034, 1037f, 1039, 1040f importance of banking  1034–9 Japanese banking crisis  1058–62 keiretsu 1053–5 lending attitude  1065f lending technologies  1056–8 loans outstanding of private banks  1041f long-term credit banks  1044 lost decades  1063–6 main bank system  53–4, 1053–5 market structure  1046–7 monitoring role of banks  53–4 non-financial corporations  41, 41f other financial institutions  1045 overview of banking system  1034–53 payment structure  288 post-crisis 1062–6 private banks  1041f profits and losses for ordinary banks  1064f public banks  1045–6 regional and second regional banks  1041, 1044, 1047 regulation 1053 relationship banking  1053–6 risk-sharing 43 role of collateral  1056–7 segmentation 1039–47 Shinkin banks  1044–5, 1047 small business credit scoring (SBCS)  1057 trust banks  1044 universal versus commercial  1052 Japan Bank for International Cooperation (JBIC) 1046 Japan Finance Corporation (JFC)  1046 Small and Medium Enterprise Unit  1058 Japan Housing Finance Agency  1046 Japan Post Bank  1045–6 Japan Post Holdings  1045 Japanese banking crisis  1058–62 Jay, Pierre  332 joint liability lending and adverse selection  407–9

and microfinance  406–12 and moral hazard  409–10 and welfare  414–15 joint stock banks  322b, 325 JPMorgan Chase  145, 182n, 439, 636, 758, 986 RiskMetrics  158, 159–60 judgement lending  440

K

Kahneman, Daniel  820–2, 828 Kazakhstan 1137 Kenya agent banking  1098 ATMs 1097 branching 1097 financial inclusion  1086, 1088–9, 1091–2, 1097–8 household access to finance  1091–2 mobile banking  1101, 1103 mobile money accounts  1092 savings and investment  1099 Key Attributes of Effective Resolution Regimes for Financial Institutions (KA), FSB, G20  97, 119–23, 128 Keynes, John Maynard  575 Kim, Dasol  19, 321–54 Klapper, Leora  27, 1113–29 Kosovo 582 Kuwait  361, 362 Kuwait Finance House  360

L

labor force gap, Africa  1092–6, 1094f, 1095f Laiki Bank (Cyprus Popular Bank)  659 Laplanche, Renaud  439 large-scale asset purchases (LSAPs)  12, 587, 618 Latin America  1152–85 agent banking  1098 allocation of credit  1177–9 ATMs 1166 bank consolidation  1154–7, 1162–3, 1177–9 bank performance  1169–71 bank solvency and asset quality  1181t bank stability  1173, 1174t banking concentration  1155, 1156t, 1172–7 branching 1166 capital  1173, 1174t

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1240   index Latin America (cont.) and China  1153, 1155 competition 1172–3 cost structure  1175t credit 1163–4 credit costs  1167 cross-border entry  1176–8 debt crisis  708–9 deposits 1164 development banks  1181–4 effects of bank consolidation  1169–71 efficiency  1170–2, 1175–7, 1175t evolution of financial policy  1157 financial depth and credit indicators  1165t financial inclusion  1092f, 1164, 1166 financial liberalization  1158–60 financial penetration  1163–9 foreign direct investment (FDI)  1155 foreign-owned banks  1154–7, 1156t, 1169–71 global financial crisis  1153, 1162–3, 1180 interest margins  1167 interest rates  1166–9, 1167t, 1168t, 1179 leverage ratios  1173, 1174t liberal reforms  1152–3 liquidity  1167, 1168t market structure  1169 mergers and acquisitions  1157 non-performing loans  1180, 1181t political factors  1182 privatization  1154, 1161–2, 1169–71, 1178–9 profitability  1173, 1174t ratios 1173 regulatory developments  1179–81 universal banking  1160–2 Latvia  1144, 1148 lazy bank hypothesis  1061 leasing, and technology  437 legislation, see regulation Lehman Brothers  51, 96, 98–9, 122, 903, 986, 993 Lehnert, Andreas  20, 470–97 lender of last resort (LOLR)  602–26 and bank failures  603 and banking crises  898–900 and deposit insurance  687 distinguishing between insolvent and illiquid banks  609–11

effects of liquidity injection  623–5 Eurozone  620, 621–3 function of central banks  589–90 hedge funds as  75 lending penalties  625 and liquidity  185 and liquidity provision  79–80 and liquidity requirements  215 and liquidity shocks  605–9 and monetary policy  618–20 new background for policy  617–18 open market operations  625 policy 617–25 role 602–5 role in global financial crisis  625–6 role of liquidity creation  619–20 and systemic crises and contagion  611–17 lending asset-based 437 automation of decisions  349 and capital market funding  70–3 discount window., see discount windows financial statement  437 FinTech  354, 438–9, 442–3 fixed-asset 437 funding 71 group 406–12 individual 412–15 intertemporal smoothing of rates  66 joint liability  407–10, 414–15 origination 71–2 P2P 63 poverty 425 relationship., see relationship lending residential., see mortgages risk processing  71 and securitization  71–2 servicing 71 small business., see small business lending soft-budget-constraint problem  67 subprime  191, 269–72 technology 435–43 timely intervention  67–8, 70, 75 transaction 69 transition countries  1144–5, 1146t US 73

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index   1241 lending booms  864, 873–4 lending rates, intertemporal smoothing of  66 lending technologies, Japan  1056–8 LendingClub  277–8, 438, 439 Lensink, Robert  19, 404–25 Lerner Index  783–4, 804 less significant institutions (LSIs)  326 Level 3 assets  128n leverage and corporate governance  134–5 and industries  135f leverage cycles and macroprudential supervision  591 and shadow banking  548 leverage ratios  726–8, 727t, 1173, 1174t leverage risk  643, 662–3 liabilities covered by deposit insurance  691, 691f financial business  537–9, 538f market discipline  742–4 life insurance  414 Liikanen Report, EU  3, 84, 1011–14, 1020 liquidity 181–216 adverse selection-driven dry-ups  610–11 and contagion  861 injection  617, 621–3, 623–5, 639, 640t, 653 Latin America  1167, 1168t research studies  9 shortages  687–8, 861 and systemic risk  850–2 liquidity coverage ratio (LCR)  210–13, 563–4, 751–2, 756, 987 liquidity creation, see also maturity transformation and bailouts  649 and banking crises  892–3 by banks  183–96 and capital requirements  190–6, 207–10 and cash reserve requirements  190–3 empirical evidence  188–9 by the Federal Reserve  621t in Islamic banking  382–3, 384t regulation  182–3, 189–90, 201–15 role of banks  77–86 role of LOLR  619–20 theories  181–2, 183–8 liquidity insurance  79

liquidity provision and financial stability policy  589–90 by fragile banks  78–80 liquidity requirements and capital requirements  214–15 purpose and effect  213 regulation 210–15 liquidity risk Islamic banking  376–7 liquidity creation  182 shadow banking  1123 SIVs 154–5 structured leverage finance  561n and systemic risk  865 wholesale payments  310–11 liquidity shocks and adverse selection  610–11 and contagion  48–9, 607–9, 859, 870 and liquidity-triggered systemic risk  607–9 and LOLR policy  605–9 and maturities transformation risk  605–7 and systemic risk  863 unidentifiable 609–10 liquidity-savings mechanisms  311–12 Lithuania 1143 living wills  111, 116, 123–5, 126t, 753, 857 Lloyds  328, 673, 903 loan certificates  614 loan markets  788–91 loans Australia  1199, 1199t automobile  270, 437, 981 bad  661, 1132, 1136, 1141 commercial 647–8 commitments 187–9 credit card  270 New Zealand  1199, 1199t pricing 66 and securitization  349, 981 loan-to-value (LTV)  457, 472–3 local banks and competition  788–90, 791–2 and small business lending  450–1 local government financing vehicles (LGFVs)  1121, 1123–4 local government funding  1121, 1123–4 locality, and small business lending  450–1

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1242   index Long Term Credit Bank of Japan  1060 long-term credit banks  1044 long-term finance  1104–6 long-term refinancing operations (LTROs)  622–3, 1019 LTCM hedge fund  614 Lucius Caecilius Jucundus  953, 970 Lula da Silva, President  1182, 1184

M

Maastricht Treaty (1993)  1000 machine learning  268–9 macroeconomic factors, and cross-border entry 938–9 macroeconomic models, and systemic risk 866 macroprudential supervision  494–6, 590–1, 593–4, 854–5 Madoff, Bernard  888 main bank system, Japan  1053–6 main refinancing operations (MROs)  622, 1019 Malawi 1099 Malaysia  360, 361, 889, 1100 malpractice and misconduct  145, 1210–11 management, and banking crises  887–90 marginal expected shortfall (MES)  869 market discipline  736–66 and bank failures  912–13 concept 738–44 direct  739, 740 effects of recent reforms  751–6 evolution 744–50 ex ante  738 ex post  738 forecasting 747–8 impact of reforms  754–6 increasing integration of banks and financial markets  82–5 indirect  739, 763 influence  738–9, 749–50 influence induced by investors’ quantity changes, runs  741–2 influence induced by security price changes 740–1 Islamic banking  388–9 logical discipliners  742–4

monitoring  738–40, 745–7, 748–9 and Pillar 3  756–9, 759t potential impediments  760–6 pre-depression era  922 market environments  838–9 market risk  155 Basel regulations  718–19 Islamic banking  377, 379 measurement 160–2 market structure  788–94 Japan 1046–7 Latin America  1169 and regulation  795–6 market values bank customers  650–1 success of bailouts  650 market-based finance difference to shadow banking  540–4 structural characteristics  540–2, 541t marketplace lenders  276–8, 438 Markit credit index data service  167 Markowitz, Harry, theory of portfolio risk measurement 157 Martin, Alex  20, 470–97 Massachusetts Credit Union Act (1909), US 332 MasterCard 301 maturity transformation, see also liquidity creation and bank runs  692 and banking crises  892–3 economic benefits  686 and risk  605–7 and systemic risk  850–2 Mauritania 360 Mauritius  1077, 1079, 1092 Maysar (excessive risk-taking)  359 McFadden Act (1927), US  327, 339, 979–80, 983 McKillop, Donal  19, 321–54 mental accounting  822–3 mergers and acquisitions after deregulation  983, 985f, 1005 bank acquisitions  930f, 933f banking globalization  928–9 Brazil 1157 community banks  344–6, 345f

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

index   1243 and corporate complexity  115 cross-border acquisitions  929–34, 931f, 932t cross-border acquisitions determinants 935–40 Europe  1007, 1011 Latin America  1157 numbers in US  985f Meridien BIAQ  888 Merrill Lynch  156, 159, 636, 993 Mester, Loretta J.  18, 229–56 Metro Bank  328 Mexican Tequila crisis (1994–5)  888, 1161, 1169 Mexico ATMs 1166 bank stability  1175 banking concentration  1155 credit 1164 cross-border entry  1176–7, 1178 deposit insurance  696, 697–8 deposits 1164 efficiency 1173 financial inclusion  1166 financial liberalization  1159 foreign-owned banks  1155, 1156, 1161–2, 1169–70 interest rates  1166 privatization 1169 profitability 1169 Tequila crisis  888, 1161, 1169 textiles industry  964 microfinance 404–25 antecedents 406–7 commercialization 412–15 group lending and joint liability  406–12 individual lending  412–15 microfinance institutions (MFIs)  405–6, 412–15, 416–17, 421–4, 422f microfinance-plus strategy  421–4 product design  419–20 skills enhancement  420–4 subsidization 424–5 success 416–19 Microfinance Information Exchange (MixMarket) 416 Microfinance Summit Campaign  416 microinsurance 1100

microprudential supervision  590, 855 Microsoft 300 Middle East  1092f Ministry of Finance (MOF), Japan  1053 misconduct  145, 1210–11 Mishkin, Frederic  21, 573–95 Mitsubishi-Tokyo-UFJ (MUFJ)  103, 1040 Mitsui-Sumitomo (SMBC)  1040 Mizuho 1040 mobile banking Africa  1101, 1102t, 1103–4 China  1127, 1128 Kenya 1103 mobile money accounts  1092 Modigliani-Miller theory  711 Molyneux, Philip  1–28, 1000–26 Monaco 582 monetary policy, see also lender of last resort (LOLR) commitment to a nominal variable  578–9 and credit bubbles  593–4 effect of electronic payments  303 exchange rate pegs  582–3 and financial crises management  623–5 and financial intermediaries  966–70 and financial stability policy  591–5 forward guidance  587–9 importance of central bank independence 579 inflation targeting  584–6 instrument rules  583–4 interest rates  580–1 large-scale asset purchases  587 and LOLR policy  618–20 nominal anchors  582–9 nominal-GDP targeting  586 non-conventional 586–9 price-level targeting  586 research studies  12 response to global financial crisis  637 role of expectations  576–7 and systemic risk  855–6, 864–5, 874 time-inconsistency problem  577–8 monetary targeting  583–4 money laundering  300–1 money market deposit accounts (MMDAs) 983

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1244   index money market funds (MMFs)  550–1, 551f, 558 money market mutual funds (MMMFs)  622, 980 monitoring deposit insurance  698, 701–2 equity prices  748–9 market discipline  738–40, 745–7, 748–9 role of banks  42, 53–4, 55, 75–6 role of private equity firms  74–5 monoliners 76–7 monopolistic competition  782 Moody’s 439 moral hazard and deposit insurance  688, 694–8, 699 increasing integration of banks and financial markets  81–2 and joint liability lending  409–10 LOLR policy  623 and regulation  182, 189 and shadow banking  1124 and systemic risk  856–7, 865 Morales-Acevedo, Paola  23, 776–805 Morgan Stanley  111, 636, 986 mortgage-backed securities (MBS) evolution 506–7 as financial assets  493–4 financial innovation  981 and global financial crisis  900–2 holders of debt  487f for holding mortgages  476, 484–8 issuance and outstanding  486f, 507, 508t, 553f, 555f primary-secondary mortgage market spread 488f subprime crisis  504–5 mortgages 470–97 Africa 1083 amortization 479–80 Australia 1197–200 cash-out refinancing  481 and community banks  349–50 and credit risk  489–90 and credit scores  473f and credit supply  494 and credit-extension decision  471–3 defaults 480–1 as financial assets  483–8, 491–2

and financial stability  491–6 and FinTech  278 foreclosure  473–5, 474f, 475, 481–3 holders of debt  487f and house prices  477–8, 478f, 489 household decision-making  477–83 industrial organization of the market  476, 487 interest rates  478–9, 479f lenders 349 macroprudential policies  494–6 market share  349 modification programs  481–3 New Zealand  1197–200 payments 471 penalties 480 refinance or default decisions  480–1 refinancing incentive  484, 485f regulation  488–90, 494–6 securitization  476, 484–8, 981 servicing 475–6 subprime  153–6, 270–2 and success of bailouts  647 US 980 valuing 484 Moshirian, Fariborz  28, 1190–211 M-Pesa  1101, 1103 M-Shwari 1103 Mudaraba (silent partnership) contracts  367, 368t, 371, 376 multi-market banks competition  790–1, 792–4 small business lending  450–1 multinational banking  935–6 multiple-bank relationships  55 Murabaha (cost-plus-profit) contracts  367, 368, 368t, 369, 371 Musharaka (joint partnership) contracts  367, 368t, 369, 376 mutual banks  321, 322b, 325, 337–8, 979 mutual funds  977–9 mutual savings banks  333, 335

N

narrow banking  892–3 National Australia Bank (NAB)  1192 National Bank of Commerce  1107

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

index   1245 National Bank of Greece  659 National Banking Acts (1863 and 1864), US  190, 537, 964 National Credit Union Administration (NCUA)  350, 353 National Credit Union Share Insurance Fund 341 National Development Bank  1162 National Economic and Social Development Bank (BNDES)  1182–4 National Microfinance Bank  1107 National Savings Bank  1162 Nationally Recognized Statistical Rating Organization (NRSRO)  77 NCUA, see National Credit Union Administration (NCUA) negative equity  481 negative interest rate policy (NIRP)  12 net cash outflows (NCOF)  211 net stable funding ratio (NFSR)  211–13, 987 Netherlands bailouts  639, 641 corporate governance  132 payment costs  296 recapitalizations 1017 network theory  49–50, 859 New Zealand  1190–211 authorized deposit-taking Institutions (ADIs) 1195 bank assets  1191, 1192t, 1197–9, 1198f banking concentration  1192–5, 1193t capital requirements  1207–8, 1207t competition 1192–5 debt funding  1196–7 deposits 1195–6 efficiency 1200–4 funding sources  1195–7, 1196t funding uses  1197–200 global financial crisis  1204–6 government support  1204 house price bubble  1194–5, 1200 loans 1199 mortgages 1197–200 profitability 1200–4 regulatory reforms  1208–11 resilience of the banking system  1207–11

sector concentration of loans  1199t size and significance of banking  1191–2, 1192t Niger 1103–4 Nigeria 1106 Nippon Credit Bank  1059, 1060 non-bank credit intermediation (NBCI)  549–50, 554, 556–9, 556f non-bank firms financial inclusion  304–5 mortgage market share  349 mortgages 476 shadow banking  533f, 534f and systemic risk  314–15 non-financial corporations  41, 116–18 non-financial services  421–4 non-local banks  450–1 non-mortgage securitization  506 non-performing loans (NPLs) China 1117–18 Eastern Europe  889 Europe 1025 Islamic banking  377, 380 Italy  377, 380 Japan 1060–1 Latin America  1180, 1181t performance 244–5 transition countries  1141 non-structural approach to performance measurement  233–4, 236, 241–3, 252–5 Norges Bank  588 Northern Rock  44, 155, 606, 626, 901, 1017 Norway 297 Novo Banco  660, 1024 NPLs, see non-performing loans (NPLs)

O

off-balance sheet guarantees  648 Office of the Comptroller of the Currency (OCC) 327 Oman  361, 369 OnDeck Capital platform  439 Ongena, Steven  23, 776–805 online banking China  1127, 1129 and community banks  352 growth 983 use of  272, 273–4

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1246   index open market operations  624 operational risk  156, 161, 377, 390, 719, 720 options 164–5 orderly liquidation authority (OLA)  632, 657, 664–5, 666, 674, 753, 997–8 orderly liquidation fund (OLF)  657 organizational forms  246–7 organizational innovation  275–8 originate-to-distribute (OTD) model  198–201, 199f, 504, 607, 981, 988–9, see also transaction banks originate-to-hold (OTH) model  197–8, 199f, 201, 504, 988f, 989, see also relationship banking origination in securitization  71–2, 518–20 OTP bank  1141 output floor  720 outright monetary transactions (OMT)  6, 622–3, 1018, 1019 over-the-counter (OTC) contracts  166–7, 550 ownership structure and bank performance  246–7 and relationship to bank value  254–5

P

P2P (Peer-to-Peer) lending  63, 438 Pakistan 304 Panama 582 Panellinia Bank  659 Paraguay bank stability  1175 efficiency 1176 financial intermediation  1164 interest rates  1166, 1179 private credit  1164 Parigi, Bruno M.  21–2, 602–26 Paula, Luiz Fernando de  27, 1152–85 pay, executive., see executive pay Payment Services Directive 2 (PSD2)  269, 300 payments and payment systems  285–316 availability of data  304–5 card security  301 and competition  299–300 and contagion  861 Continuous Linked Settlement (CLS) Bank 312–13 costs 296–7

current policy issues on wholesale payments 314 daylight overdrafts  309–10 differences in structure  287–9 direct versus indirect pricing  297–8 effect on monetary policy  303 fast payments 24/7  302–3 fees 287–8 and financial inclusion  303–4 and financial innovation  272–4, 982 and financial stability  314–15 and FinTech  996 government-issued digital currencies 292–4 Internet-based 983 and liquidity and other risks  310–11 and liquidity-savings mechanisms  311–12 money laundering  300–1 mortgage 471 negative interest rates  294–6 overview 285–9 payment cards  298–9 payment theory  287 pricing 297–8 record-keeping 301–2 retail payments  289–305, 289t securities settlement systems  313–14 wholesale payments  305–15 PayNet 438 PBoC, see People’s Bank of China (PBoC) penalties  480, 625 pension schemes  40–1, 414 People’s Bank of China (PBoC)  1119, 1121 performance, see bank performance performance measurement  233–6, see also bank performance non-structural approach  233–4, 236, 241–3 specifying capital structure  243–4 specifying output quality  244–5 specifying outputs and inputs  243 structural approach  234, 236–41 and technology  255–6 Pería, María Soledad Martínez  27, 1113–29 personal contact  445–6 personal cultural views  146–7 personal identification  301, 1100

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index   1247 Peru ATMs 1166 bank stability  1175 deposits 1164 development banks  1184 financial inclusion  1166 financial intermediation  1164 foreign direct investment (FDI)  1155 interest rates  1166, 1179 Phillips curve  575–6, 577, 579 Piacentino, G., see Donaldson, Piacentino and Thakor model Pigou tax  857 Pinochet, General Augusto  1158 Piraeus Bank  659 Poland banking nationalism  1141 banking system  1134–5 credit unions  333 financial intermediaries  1142 foreign-owned banks  1135 policy responses and implications after global financial crisis  2, 637 corporate governance  147–8 financial stability  589–95 fiscal  294, 575–6, 856 LOLR 617–25 monetary., see monetary policy shadow banking  555–65 systemic risk  854–7 Ponzi schemes  888 portfolio risk  157, 489–90, 642–3, 646, 661–2 Portugal bail-ins  660–1, 667, 670 bailouts 3 deposit insurance  697 liquidity 9–10 sovereign debt crisis  1003 Postal Services Agency  1045 poverty and Islamic banking  387, 388 and microfinance  404, 405, 417, 418–22, 424–5 pre-payment cards  300–1 price stability  574, 578–9 prime brokerage  563–4 private credit bureaus  802–5

private equity firms  63, 74–5 private information and risk management  169–72 and small business lending  440–1 privatization Africa  1089, 1106–7 Argentina 1161 China 1117 Japan 1046 Latin America  1154, 1161–2, 1169–71, 1178–9 transition countries  1135–8, 1143 process innovation  265–9 product innovation  269–75 profit elasticity  784–5 profitability Africa 1082–3 Australia 1200–4 Europe  1011–14, 1015t global 1203t Islamic banking  372–6 Latin America  1173, 1174t New Zealand  1200–4 prompt corrective action (PCA)  590, 898, 905, 1024 prospect theory  821–2 Prosper Marketplace  438, 439 Provision of Trust Business by Financial Institutions Act (1943), Japan  1044 Prudential Regulatory Authority (PRA), UK 564 PSD2, see Payment Services Directive 2 (PSD2) psychology, and economic behavior  815–30 public banks, Japan  1045–6 public sector purchase program (PSPP)  1019

Q

Qatar 361 qualitative asset transformation  64–8 qualitative data  436 quantitative data  436 quantitative easing (QE)  12, 587, 637, 1019, 1066 quiet life hypothesis  1172

R

Rabobank 1107 Raiffeisen, Friedrich Wilhelm  329, 332

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1248   index rainfall insurance  1100 rating triggers  76 rational expectations revolution  576–7 RBS, see Royal Bank of Scotland real economy  953–71 and banking deregulation  956–7 and banking in Roman era  953–4 causality debate and portance of banks 954–6 and dynamics in product markets  960–5 effects of banks  4–7 importance of banks  39–41, 956–8 role of bank competition  959–60 role of banks  64–8 success of bail-ins  669 success of bailouts  649–50, 653 unintended consequences of the Great Recession 965–70 real estate markets  874 real estate mortgage investment conduits (REMICs) 506 Real Plan (Brazil)  1161 real-time gross settlement (RTGS) networks  285, 305, 310–12 Real-Time Payments transfers  302, 308–9 recapitalizations  639, 640t, 653–4 Reconstruction Finance Corporation (RFC) 917 Recovery and Resolution Directive (2014), EU 1020 regime changes  888–9 regional banks Brazil 1155 Colombia 1154–5 Japan  1041, 1044, 1047 regulation, see also deregulation during and after global financial crisis 456–7 after global financial crisis  1, 737, 1012, 1019–25 and bank strategy  796–7 and banking competition  794–801 capital 84 capital requirements  202–10 community banks  339, 350 and conduct  796 and corporate complexity  113 and credit rating agencies  552

cross-border entry  937–8 deposit insurance  701–2 Europe 1019–25 financial stability  797–801 firm financing  801 and global financial crisis  904–5 Japan 1053 Latin America  1179–81 and liquidity creation  182–3, 189–90, 201–15 and liquidity requirements  210–15 and market structure  795–6 and moral hazard  182, 189 mortgages  488–90, 494–6, 979–80 prudential 795 re-regulation 987–8 retail banking  1020 risk-taking 230–1 and securitization  524–6, 552 shadow banking  549–55 small business lending  432–3, 456–7 US  979–80, 987–8 wealth management products (WMPs) 1125 Regulation Q  980, 983 regulatory arbitrage China 558 shadow banking  539–40, 544–5, 554 regulatory constraints, China  1119–21 regulatory reforms Africa 1107–8 after global financial crisis  3–4 Australia 1208–11 EU 753–4 New Zealand  1208–11 suggestions 82–6 US 753 regulatory structure and financial integration  80–2 and reform suggestions  82–6 reinsurance 76–7 relationship banking, see also originate-tohold (OTH) model business strategies following global financial crisis  988f, 989–91, 990t capital market funding  73 community banks  337–8, 351–2 and competition  68–70

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

index   1249 and information processing  65–70 Japan 1053–6 OTH model  197–8 and private information  169–72 theoretical studies  54–6 relationship lending empirical studies  440–1 and financial crises  454–5 and small business lending  446 and soft information  439–40 relative market power (RMP) hypothesis  434 relative profit differences, and banking competition 784 Remuneration Code (2009), UK  14, 132, 138, 1022 repurchase agreements (Repos)  154–5 required stable funding (RSF)  211–12 Reserve Bank of Australia  590, 1200, 1205 Reserve Bank of New Zealand  113 residential mortgages, see mortgages residential real estate lending  437 residual saving  819 Resolution and Collection Bank  1059 resolution authorities  119–25 Resona bank  1040–1, 1047 retail markets integration  860–1 retail payments  289–305, 289t cash and negative interest rates  294–6 and competition  299–300 credit and debit cards  298–9 direct versus indirect pricing  297–8 government-issued digital currencies 292–4 money laundering  300–1 payment costs  296–7 retail runs  44 Rhineland 1016 Riba (receipts of interest)  359, 365–6 Riegle-Neal Interstate Banking and Branching Efficiency Act (1994), US  253, 327, 983, 986 Ripple payment system  302 risk and bank assets  8 credit  155–6, 160–1 effects of cross-border entry  942–4 Europe 1014–16 financial intermediaries  530–1

increasing integration of banks and financial markets  63, 81–2 Islamic banking  390–1 liquidity  154–5, 156 market  155, 160–2 and maturities transformation  605–7 neglected in shadow banking  545–7 operational  156, 161 performance measurement  234–7 processing 71 shadow banking  1123–5 systemic 607–9 time-gap 312–13 wholesale payments  310–11 withdrawal  184, 186 risk management  153–7, 162–9, 169–72, 173–7 risk measurement  156, 157–62 risk sharing and contagion  859 and financial markets  80 Islamic banking  371–2 role of banks  42–4 risk transformation  535–6, 537, 540–1 risk-based pricing  269, 698–701, 700f risk-taking and bank culture  85–6 and conflicting incentives  231–3 and deposit insurance  694–8 and derivatives  162–9 and diversification of scale  232–5, 232f and executive pay  135–40 and financial leverage  134–5 and guarantees  134–5 and low interest rates  591–4 and monetary policy  591–4 regulation 230–1 risk-weighted assets (RWA)  708–9, 714, 717–22, 718t, 719t, 727–8, 730f, 732f role of banks  39–57 asset transformation  64–8 corporate governance  53–4 economic 64–8 growth 52–3 information processing  64–70 liquidity creation  77–86, 183–96 monitoring  42, 53–4, 55, 75–6 in pre-modern era  953–4 risk sharing  42–4

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1250   index rollover risk, see liquidity risk Roman, Raluca A.  22, 630–76 Romania  1141, 1143 rotating savings and credit associations (ROSCAS) 406 Royal Bank of Scotland  103, 328, 758, 903, 1012 Royal Banking Commission, Australia  1208 Royal Commission into Misconduct in the Banking, Superannuation, and Financial Services Industry, UK  1210 Russia bank lending  1145 banking concentration  1144 banking sector structure  1143 banking system  1137 deposit insurance  693 dollarization 1144 foreign-owned banks  1137, 1143 global financial crisis  1140 two-tier banking system  1135 Rwanda  424, 1103

S

Safaricom  1101, 1103 Saitama Resona bank  1040–1, 1047 Salam contracts  368t, 369 Salomon Brothers  159 Santander  103, 661 Sarkisyan, Anna  20, 503–26 Saudi Arabia  360, 361, 362, 582 Saunders, Anthony  17, 153–77 savings and decision-making  818–19, 825, 835 and financial inclusion  1147–50 Savings and Loans crisis (1980s)  609 savings and loans (S&Ls)  334, 335 savings banks  333–5, see also community banks composition by size  343t defining features  322b, 333 and deregulation and industry consolidation 341–6 entry and exits  346–7, 347f, 349–50 historical origins  333–4 historical trends  341–4, 342f

mortgages 349–50 numbers  977, 993f today 334–5 scale economies, see economies of scale Schulze-Delitzsch, Hermann  329, 332 Schwartz, A.J.  913–15, 918 Second Banking Directive (89/646/EEC) (1989)  964, 1001–2, 1011 sectoral capital requirements (SCRs)  496 securities market discipline  740–1, 761–2 settlement systems  313–14 Securities and Exchange Commission (SEC), US  456, 552 Securities and Exchange Law (1948), Japan 1052 securities financing transactions (SFTs)  550, 554 Securities Market Programme, ECB  1018, 1019 securities settlement systems  313–14 securitization 503–26 and adverse selection  512–13 and asset selection  511–13 asset-backed securities  154–5, 503, 517–18 and banking crises  46–7 benefits and risks  518–24 cash flow allocation  518 creation of an SPV  514 and credit booms  493–4, 872 and credit enhancements  515–16, 517f economic importance  504–5 evolution  505–11, 549 financial innovation  981 and global financial crisis  900–2 growth  503–4, 552 increasing importance  71–2 and interest retention  515–16 issuance 508t, 510f issuance of asset-backed securities  517–18 lending operations  349 as ‘market for lemons’  511–12 mechanics 511–18 mortgages  476, 484–8 OTD model  198–200 outstanding volume  506f, 511

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

index   1251 regulatory reforms  524–6, 552 and risk retention  516, 525 and shadow banking  199f, 1123 simple, transparent, and comparable (STC) securitization 505 and ‘skin in the game’  515–16, 525, 552 structuring the transaction  514–16 subprime mortgages  271 vs.traditional banking  199f transaction 512f transfer of assets  514 security price changes, market discipline 740–1 Senegal 1098 SEPA, see Single Euro Payments Area (SEPA) SES, see systemic expected shortfall (SES) settlement systems securities 313–14 and systemic risk  852, 861 shadow banking  530–65 agency problems  549–50 capital requirements  210 China  1118–25, 1119f concerns 544–9 credit enhancements  541 credit guarantees  542 credit intermediation chain  536f definition 62n, 63n, 531–2, 1118 difference to market-based finance  46–7, 199f, 540–4 emergence 62–3 financial stability  542–4 funding fragilities  547 growth 531 importance 75 innovation in composition of money 537–9 leverage cycles  548 liabilities  537–9, 538f measurement 532–4 monitoring 549–55 neglected risks  545–7 OTD model  200–1 policy challenges  555–65 reasons 534–40 regulation 549–55

and regulatory arbitrage  539–40, 544–5, 554 securitization 199f, 493–4 SIVs 154–5 size 533 specialization 534–7 structural characteristics  540–2, 541t supervision 549–55 and systemic risk  851 shareholders corporate governance  141–2 risk-taking 134 Sharia law  359, 360, 365–6 Sharia supervisory board (SSB)  380 Sharpe, Bill  157 Shawbrook Bank  328 Shinginko Tokyo bank  1057 Shinkin banks  1044–5, 1047 shocks aggregate 862–3 credit 5–7 insolvency 870 liquidity  48–9, 605–11, 850, 859, 863 Shoko Chukin Bank  1046 Sierra Leone  1077 significant institutions (SIs)  326 simple, transparent, and comparable (STC) securitization  505, 520 Singapore 691 Single Euro Payments Area (SEPA)  291, 297, 298 Single Market (EU)  328, 1000, 1002 single point of entry (SPOE) strategy  123–4, 657, 997 Single Resolution Fund (SRF), EU  658, 754, 1023 Single Resolution Mechanism (SRM), EU  658, 753–4, 1014, 1026 Single Supervisory Mechanism (SSM), EU  1022, 1026 single-market banks  450–1 SKS microfinance  413 Slovakia  1142, 1143, 1148 Small Business Administration (SBA)  455–6 small business credit scoring (SBCS)  266–7, 437–9, 441–2, 444, 1057

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

1252   index Small Business Jobs Act (2010), US  455–6 small business lending  431–59 and bailouts  648 and bank competition  433–4, 451–3 and bank consolidation  69, 433, 446–51 and bank funding  431–2 and bank locality  450–1 and bank market  450–1 and bank size  447–50 changes in distance over time  445–6 and FinTech  438–9 and foreign-owned banks  451 and global financial crisis  434, 453–8 government support  455–6 and hard information  432, 435, 436–7, 443–6 market share  431 markets 450–1 and personal contact  445–6 recovery 457–8 regulation  432–3, 456–7 and soft information  432, 435, 436–7, 444 technological innovation  432, 433, 435–43 Small Business Lending Fund (SBLF)  637 SMP, see Securities Market Programme, ECB SNS bank  413 social costs and benefits of bail-ins  663–4, 669, 673 of bailouts  631, 644, 652, 655, 663–4, 674 of bankruptcy  674–5 of decline in community banks  350–3 of microfinance  413 social services offered by MFIs  421, 422f stored value cards for  301 Société Générale  888 soft information and bank market  450 and bank size  449 in relationship lending  439–40 in small business lending  432, 435, 436–7, 444 Solanko, Laura  27, 1132–50 solvency shocks, unidentifiable  609–10 South Africa  1077, 1079, 1091 South America  361 South Sudan  1077, 1079

Southern Europe  1132–50 sovereign debt  1024–5 sovereign debt crisis (2009–11) Eurozone  2–3, 626, 639, 1003–4, 1018 and global financial crisis  902–3 LOLR policy  620–3 research studies  6–7 Soviet Union  1132–50 Spain bail-ins 661 bailouts  3, 639, 641 bank assets  1002 capital requirements  208 credit supply  6 deposit insurance  691 dynamic loan-loss provisioning  496 low interest rates  592 savings banks  334 sovereign debt crisis (2009–11)  1003, 1025 special purpose vehicles (SPVs)  114, 154, 198, 503, 511, 514, 851 SRISK (systemic risk measure)  11, 173–4, 617, 645, 653, 869 St George Bank  1195 Standard Bank  1089, 1106–7 Standard Chartered  103, 117, 1116 state intervention  687, 890 State Street Corporation  636 state-owned banks  797 state-owned commercial banks (SOCBs)  1134–6, 1137 state-owned enterprises (SOEs)  1136 stock and bond prices  740–1 stock liquidity  383, 384, 385t stored value cards  301 strategic defaulting  410 stress tests  3, 615–16, 637–8, 641, 728–9 structural demand models  787–8 structure-conduct-performance (SCP) hypothesis  434, 777, 778–80, 779t structured investment vehicles (SIVs)  153–6, 509 structured leverage finance  559–61, 559f, 560f subordinated bank debt (subordinated notes and debentures (SNDs))  744–7 subprime crisis (2007), US  72, 76, 153–6, 191, 210, 270–2, 504–5, 584, 606–7, 618–19

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

index   1253 subprime mortgages  153–6, 269–72, 489–90, 489f, 552 Sudan  360, 362 sunspot phenomena  44, 46, 184n supervision  549–55, 590–1, 694, 701, 897–8 supervisory capital assessment program (SCAP)  456, 637–8 swaps 165–9, see also credit default swaps (CDSs) Sweden  292–3, 1193 SWIFT payment transfer  286–7 Swiss Interbank Clearing  584 Swiss National Bank  582, 583, 584 Switzerland  186, 291 syndicated lending  981 systemic crises  611–17, 850 systemic events  850, 853–4, 867–8 systemic expected shortfall (SES)  11, 173–4, 616–17, 645, 869 systemic risk after the global financial crisis  847–75 and aggregate shocks  862–3 and bail-ins  663, 669–70 and bailouts  633, 641–2, 643–4, 645–7, 649–50 and Co-Cos  672 concept 849–57 and contagion  858–62 efficient versus self-fulfilling events  853–4 empirical evidence  867–74 financial fragility hypothesis  850–2 Great Recession  314–15 and G-SIBs  175–6 horizontal 849 and interconnectedness  314–15 liquidity-triggered 607–9 measurement  616–17, 645–6 public policy  854–7 regulation 85 risk management  173–7 and settlement systems  313–14, 852, 861 SRISK measure  11, 173–4, 617, 645, 663, 869 and systemic events and crises  849–50 theoretical models  11, 858–66 vertical 849 wholesale payments  306–9

T

tail risk  46, 545–7, 608 Tanzania 1107 Target 2 payment transfer  286, 306 targeted investment program (TIP)  636 targeted longer-term refinancing operations (TLTROs) 1019 Tawarruq instruments  369 tax evasion  291 tax havens  114 tax policies  545 Tax Reform Act (1986), US  506 tax subsidies  340 taxation  10–11, 113–14 Taylor rule, US  583–4, 617, 966 technological innovation Africa 1101–4 community banks  348–50 and efficiency  1012–13 and financial innovation  262–79 impact on banking  1005 performance measurement  255–6 in small business lending  432, 433, 435–43 temporary liquidity guarantee program (TLGP) 637 Tequila crisis  1161, 1169 term auction facility (TAF)  10, 637 term discount window program, see discount windows textiles industry  963–4 Thailand 417–18 Thakor, Anjan V.  17, 62–87, see also ­Boot-Thakor model; Donaldson, Piacentino and Thakor model 3-6-3 banking  980 time-gap risk  312–13 timely intervention  67–8, 70, 75, 84 Tokyo Kyowa  1059 too big to save  902 too-big-to-fail (TBTF)  81–2, 626, 643–4, 663, 698 too-interconnected-to-fail (­interconnectedness)  643–4, 663 too-many-to-fail  624, 626, 643–4, 663 total loss-absorbing capacity (TLAC)  727–8, 752–3, 754–5, see also bail-ins

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

1254   index traditional banking  540–2, 541t, 1115 vs. securitization  199f transaction banks  69, 989–91, 990t, see also originate-to-distribute (OTD) model transition countries  1132–50 after global financial crisis  1140–2 bad loans  1136, 1141 bank performance  1145 banking concentration  1137, 1144 banking crises  889 banking history  1133–42 banking nationalism  1141 banking sector  1142, 1143–4 banking systems  1134–7 credit 1138 current state of banking  1142–5 deposit funding  1143, 1144t, 1146t dollarization 1144 euroization 1144–5 European banking union  1141 financial inclusion  1145, 1147–50 financial intermediaries  1142–3 financial restructuring  1136 first decades of transition  1134–8 foreign-owned banks  1135–9, 1143, 1144–5 gender gap  1147–8 global financial crisis  1138–40 legislation 1137–8 lending  1144–5, 1146t Treaty of Lisbon (2009)  1001 Treaty of Rome (1957)  1000 troubled assets relief program (TARP) and bailouts  631 and capital injections  636f effects 638 and global financial crisis  986 purpose 611 research studies  4–5 and small business lending  456 success  633, 645–52 Trump, Donald  457 trust banks  1044 trust preferred securities (TruPs)  746 Turkey 793 Tversky, Amos  820–2, 828 24/7 payments  302–3

U

UBS 156 Uchida, Hirofumi  26, 1033–67 Udell, Gregory  26, 1033–67 Uganda  1087–8, 1087t, 1099 Uganda Commercial Bank (UCB)  1106–7 UK bailouts  639, 641 bank assets  1002, 1007, 1191 banks and growth  52 branching  1006, 1166 Brexit 1025 building societies  340 capital requirements  208, 1207t checks (cheques)  292 competition 803 corporate governance  132 credit and debit cards  292 employment in banking  1006 financial services  1191 financing structure  39–41, 40f funding sources  1197 global financial crisis  901, 903 G-SIBs 122 guarantees 1017 household assets  40–1, 41f joint stock banks  328 non-financial corporations  41, 41f pension schemes  40 recapitalizations 1017 regulation 1020 retail banking  1020 risk-sharing 43 savings banks  334 tax subsidies  340 Ukraine  1140, 1144, 1148, 1149 unconventional monetary policies (UMPs)  12 Undertakings for Collective Investment in Transferable Securities (UCITS industry) 562–3 unemployment 575–6 Unibanco 1157 Unicredit  104, 117 Union Bank of Switzerland  1012 United Arab Emirates  361 universal banking  1001, 1052, 1160–2

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

index   1255 Upstart 438 Uruguay  1155, 1166, 1175 US 977–98 asset distribution  977–9 bail-ins  632, 657, 666 bailouts  631, 635–8, 645–52 bank assets  341, 345 bank consolidation  991–4, 994t bank failures  897, 915–17, 919–21 bank lending and capital market funding 73 bank ratios  984f, 990t bank runs  918–19 banking crises  712 banking panics  911–12, 920–1 bankruptcy code  123, 674 board diversity  144 boards of directors  141 branching 1166 business strategies following global financial crisis  988–91, 988f capital ratios  194f, 713f capital requirements  190–6, 203, 205, 208, 209, 714, 1207t cash in circulation  303 cash reserve requirements  190–3, 192f cash use  290, 291, 294 checks (cheques)  288, 291 clearing houses  688 commercial banks  326–8, 341–2, 344–7, 349–50, 447, 979–80, 982f, 984f, 985f, 991–4, 992f, 993f, 994t community banks  337, 339, 340–53, 342f competition  788, 789, 790, 798, 799–800, 803 contagion 918–19 corporate governance  132 credit and debit cards  273, 292 credit scores  995 credit unions  332, 341–2, 344, 345–6, 346–7, 350, 991–2, 993f deposit insurance  688–9, 691, 696, 699 deregulation  5, 983–4 discount brokerage  995–6 economies of scale  249–50 evolution of banking  979–88

evolution of capital  712 evolution of securitization  505–6 financial innovation and change  980–3 financial services  1191 financing structure  39–41, 40f FinTech  13, 995–7 funding sources  1196–7 future of banking  995–8 global financial crisis  453–4, 900–1, 984–7 G-SIBs  111, 112, 113, 122, 123–5, 126t, 724, 725–6, 725t House of Representatives  123 house prices  478f, 491, 985 household assets  40–1, 41f, 492, 492f, 980 housing policies  986–7 importance of banks  956–7 Internet-only banks  275–6 interstate banking  983 large banks  994t, 997–8 leverage  134, 135 leverage ratios  726, 727t liquidity creation  79, 620 liquidity requirements  212 living wills  123–5, 126t loans 981 market discipline  755–6 marketplace lenders  276–7 MMFs  551, 981 mortgage rates  479f mortgage-backed securities (MBS)  981 mortgages  471–2, 475, 478f, 980 mutual savings banks  335 non-financial corporations  41, 41f number of banks  342f, 343t, 991, 993f online banking  983 payment services  286, 982 private information  170 regulation  456–7, 997–8 regulatory reforms  753 re-regulation 987–8 restrictive government regulations  979–80 risk measurement  158–9 risk-sharing 43 savings and loans (S&Ls)  334, 335, 336 savings banks  334, 335, 338, 341–2, 344, 346–7, 349–50, 993f

OUP CORRECTED PROOF – FINAL, 08/29/2019, SPi

1256   index US (cont.) securitization  505–6, 506f, 508t, 511, 549, 981 shadow-banking  62, 533 small business lending  431, 453–4, 455–6, 458 state-sponsored insurance schemes  688–9 stress tests  728–9 structured leverage finance  559–61, 559f, 560f subprime lending  269–70 syndicated lending  981–2 tax subsidies  340 textiles industry  963–4 tier 1 capital  715 Treasury  635–7, 986, 998 Uzbekistan 1149

V

Valenzuela, Patricio  27, 1076–109 Value at Risk (VaR) model  11, 156, 158–62, 173, 315, 616, 868–9 Van Der Weide, Mark E.  22, 707–33 Van Rompuy plan, EU  1018 vault cash  191, 192f Veneto Banca  660 Venezuela  887–8, 1166 Vickers Commission (Independent Commission on Banking), UK  1020 Vickers Report, UK  84 Vienna Initiative (VI)  1139 Vietnam  423–4, 423t Visa 301 Volker rule, US  3

W

Wachovia 993 Wachtel, Paul  27, 1132–50 Wakefield, Priscilla  334 Walker, Sir David  132 Wall, Larry  18, 262–79

warehouse banking  182 Washington Mutual  606, 657n, 993 wealth management products (WMPs)  155, 1118–20, 1119f, 1121, 1123, 1125 welfare 414–15 Wells Fargo  103, 300, 438, 636, 758, 996 Westpac  1192, 1195 White, Lawrence J.  18, 262–79 wholesale funding  852, 866 wholesale payments  305–15 wholesale runs  44 Wicker, E.  914–15 Williams, Jonathan  27, 1152–85 Wilson, John O.S.  1–28, 1000–26 withdrawal risk  184, 186 withdrawals 686–7 women Africa 1092–6 China  1126, 1127–9 and microfinance  412, 416, 417, 418–19, 420–1 World Bank  690 Global Financial Inclusion Database  16 Wu, Eliza  28, 1190–211

X

Xian Gu  16, 39–57 Xinming Li  19, 359–99

Y

Yu ’E Bao MMF  558 Yugoslavia 1134

Z

Zambia 1079 Zap m-system  1104 zero lower bound (ZLB)  12 zero risk entails zero return  366 Zhang, Jeffery Y.  22, 707–33 Zia, Bilal  27, 1113–29 Zimbabwe  582, 1090