Financial Inclusion and Livelihood Transformation: Perspective from Microfinance Institutions in Rural India 9819941407, 9789819941407

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Financial Inclusion and Livelihood Transformation Perspective from Microfinance Institutions in Rural India Srimoyee Datta Tarak Nath Sahu

Financial Inclusion and Livelihood Transformation

Srimoyee Datta · Tarak Nath Sahu

Financial Inclusion and Livelihood Transformation Perspective from Microfinance Institutions in Rural India

Srimoyee Datta Department of Business Administration Sidho-Kanho-Birsha University Purulia, West Bengal, India

Tarak Nath Sahu Department of Business Administration Vidyasagar University Midnapore, West Bengal, India

ISBN 978-981-99-4140-7 ISBN 978-981-99-4141-4 https://doi.org/10.1007/978-981-99-4141-4

(eBook)

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

This book is dedicated to our parents and teachers who constantly strive us for betterment

Preface

Development of any nation generally denotes the economic liberty and free access of financial services of the population. In the globalized era, it is utmost important to be financially inclusive. Our country holds diversity in terms of culture, religion, language, tradition, social structure, kinship, geographic location, etc. This heterogeneity throws challenge for every developmental activity. Financial development is such a field which goes through ups and downs continuously due to general attitude and awareness of the inhabitant of the country. Both government and non-government initiatives have been observed from the very beginning to boost up the formal finance sector of our nation. In this context, introduction of microfinance was introduced by government of India under the guidelines of Reserve Bank of India (RBI). Most microfinance programs operate with a sole objective of poverty minimization by offering various financial services. West Bengal in the map of MFI access is still in moderate positions. Financial illiteracy still dominates a large geographical area on the state. Commercial and regional rural banks could not earn the trust or accessibility in the interior zones. On the contrary, MFIs are flexible, accessible and able to penetrate into the

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interior households. In this study, the role of MFIs has been observed in a systematic manner. Both grounds level and overall observation relating to MFI activities have been done in this study. The primary and supporting initiatives of MFIs have been observed to understand the core objective of the MFI sector. After that, the impact on both the beneficiary and non-beneficiary has been studied. It helps to build a clearer image of the MFI’s influence on the population. Now more in-depth studies have been taken care of. Further observation has been taken care of regarding the income generation possibility from MFIs access. A financially independent borrower can contribute a lot into her household and gradually it is leading towards sustainable development. Here, we have been observed this phenomenon by incorporating primary data survey and relevant statistical tool covering three specific backward districts of West Bengal. On the supply side, the performance of the operating MFIs has also been studied for forecasting the future trend and the growth possibility of the selected districts. In the last phase, an important issue has been addressed through the research work that is women empowerment. This is an issue which is sole responsible for many interlinked phases of society and economy. This research paper attempts to identify and analyze the influencing variables and the levels of empowerment revolving around economic, social and psychological dimension. Financial inclusion is considered as one of the powerful ways to achieve inclusive and balanced economic growth. Microfinance institutions create provision for financial inclusion to poor and low earner by offering credit and credit plus services. Assistance in all possible forms is being generated by the MFIs support the borrowers to manage risk, build assets, increase income and enjoy a better life. Most importantly, Access to MFIs enhance borrowers’ attitude towards formal finance sector and make them financially included. Purulia, India Midnapore, India

Srimoyee Datta Tarak Nath Sahu

Acknowledgements

This book has been kept on track and has been seen through to completion with the support and encouragement of numerous people to whom we are sincerely grateful throughout the journey. It always remains difficult for us to express their contribution merely by using a few words. It is a ritual to acknowledge all well-wishers at the end but for us, we are thankful to each and every one from the very first day that made this work possible and makes it an experience for lifetime. Not only that, it is our absolute pleasure to express our gratitude to all those who contributed in many ways to the success of this book and made it happen for us. We would like to convey our heartfelt thanks to all our teachers in different phases of our academic life. We would like to remember all those teachers who have offered us with the basics for learning and development in this area and thus have grown our academic pursuance and interests. Their professionalism, knowledge and skill helped us a lot in the academic development over the years.

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Acknowledgements

We would like to express our honest regards to our beloved parents for their unconditional love and support. This mammoth task can never be completed without the endless support of our family. A special thank you for all of them.

Contents

1

Introduction 1.1 Background of the Study 1.2 Microfinance Institution 1.3 Financial Inclusion 1.4 Women Empowerment 1.5 Motivation of the Study 1.6 Objectives of the Study 1.7 Scope of the Study 1.8 Structure of the Book References

2

Financial Inclusion, Microfinance Institutions and Women Empowerment 2.1 Financial Inclusion in India and Abroad 2.1.1 Introduction 2.1.2 Financial Instruments and Institutions: An Overview 2.1.3 Financial Inclusion 2.1.4 Journey of Financial Inclusion in India

1 1 3 6 7 9 10 10 11 13 15 15 15 17 18 23

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2.1.5 Participating Financial Institutions in Financial Inclusion 2.1.6 Policy Initiatives for Financial Inclusion 2.1.7 Committee Recommendations for Financial Inclusion 2.1.8 Financial Inclusion in Different Countries 2.1.9 Literature on the Role of Financial Institutions in Inclusion 2.2 Microfinance Institutions: An Overview in Indian Milieu 2.2.1 Microcredit 2.2.2 Micro Pension 2.2.3 Micro Insurance 2.3 Women Empowerment: A Delineate on Indian Context 2.3.1 Female Empowerment and Sustainable Growth in India 2.3.2 Government Initiatives and Women Empowerment: Indian Perspective 2.3.3 Empowerment and Microfinance 2.4 Interrelationship Between Financial Inclusion, Microfinance and Women Empowerment References 3

Perception of Borrowers and Non-borrowers Towards MFIs 3.1 Introduction 3.2 Literary Overview Related to Perception About MFIs 3.3 Perception of Borrowers and Non-borrowers of MFIs: Empirical Evidences 3.3.1 Research Design 3.3.2 Analysis 3.3.3 Findings References

27 31 33 36 49 61 64 65 65 65 67 67 73 75 77 87 87 88 90 90 95 101 101

Contents

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Credit Utilization Pattern of the Borrowers 4.1 Introduction 4.2 Credit Utilization and MFI Beneficiaries: Literary Analysis 4.3 Observational Evidences Related to Credit Utilization by MFI Beneficiaries 4.3.1 Research Design 4.3.2 Analysis 4.3.3 Findings References

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Microfinance and Employability 5.1 Introduction 5.2 Studies on Employability Through MFIs 5.3 Experiential Analysis of Employability Through MFIs 5.3.1 Research Design 5.3.2 Analysis 5.3.3 Findings References

115 115 116 118 118 119 120 121

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Performance Analysis of the Active MFIs 6.1 Introduction 6.2 Performance Evaluation of MFIs: Literary Review 6.3 Empirical Observation and Analysis of Operating MFIs Performance Evaluation 6.3.1 Research Design 6.3.2 Data Types 6.3.3 Sample Design 6.3.4 Data Collection Techniques 6.3.5 Statistical and Econometric Tests Used in the Study 6.3.6 Analysis 6.3.7 Findings References

123 123 124

104 106 106 108 112 113

126 126 126 126 127 127 128 130 131

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Contents

Role of MFIs Towards Empowering the Women 7.1 Introduction 7.2 Building Up Women Empowerment by the Offerings of MFIs: Bibliographic Review 7.3 In-depth Existential Analysis on Women Empowerment by MFIs Offerings 7.3.1 Research Design 7.3.2 Analysis 7.3.3 Findings References Identification of Determinants Influencing the Economic, Psychological and Social Empowerment of the Female Borrowers 8.1 Introduction 8.2 Economic, Psychological and Social Empowerment of the Female: Literary Study 8.3 Descriptive and Analytical Framework on Beneficiaries’ Economic, Psychological and Social Empowerment 8.3.1 Research Design 8.3.2 Analysis 8.3.3 Findings References Summary and Conclusion 9.1 Summary of the Study 9.2 Conclusion 9.3 Contribution of the Study 9.4 Recommendations and Policy Implications 9.5 Limitations and Direction for Further Studies References

133 133

134 140 140 143 145 146

149 149 150

151 151 154 161 165 167 167 171 172 174 175 177

Bibliography

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Index

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Abbreviations

ATM BC BCC BFs BP BPL BSBD BSY CAR CBS CCR CGAP CP CRISIL CRS DEA DMU DP DRS DWRCA

Automated Teller Machine Business Correspondents Banker–Charnes–Cooper Business Facilitators Branch Penetration Below Poverty Line Basic Savings Bank Deposit Account Balika Samriddhi Yojana Capital Adequacy Ratio Core Banking Solution Charnes–Cooper–Rhodes Consultative Group to Assist the Poor Credit Penetration Credit Rating Information Services of India Limited Constant Return to Scale Data Envelopment Analysis Decision Making Units Deposit Penetration Decreasing Return to Scale Development of Women and Children in Rural Areas

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Abbreviations

FAO FE FI FI-PR-MDG FNB G20 GCC GDP GHI GII GIS GPRS GPS HCR HDI ICDS ICPS ICT IFPRI IPI IPPB IRDP IRS JAM JRY KCC KYC MDGs MFI MFIN MIX NABARD NBFC NBFC-MFI NEFIS NEFT NGO NPA

The Food and Agriculture Organization of the United Nation Financial Exclusion Financial Inclusion Financial Inclusion-Public Relation-Millennium Development Goals Food and Nutrition Board Group of Twenty General Purpose Credit Cards Gross Domestic Product Global Hunger Index Gender Inequality Index Geographical Information System General Packet Radio Services Global Positioning System Head Count Ratio Human Development Index Integrated Child Development Services Integrated Child Protection Scheme Information and Communication Technology International Food Policy Research Institute Index of Financial Inclusion India Post Payment Bank Integrated Rural Development Program Increasing Return to Scale Jan Dhan Aadhar Mobile Jawahar Rozgar Yojana Kisan Credit Card Know Your Customer Millennium Development Goals Microfinance Institutions Microfinance Institutions Network Microfinance Information Exchange National Bank for Agriculture & Rural Development Non-Banking Financial Company Non-Banking Financial Company-Microfinance Institutions Nationwide Electronic Financial Inclusion System National Electronic Fund Transfer Non-Government Organization Non-Performing Asset

Abbreviations

NPAG NPS NRDP NREGA ODCs OECD OTE PACs PAPs PMJDY POT PR PTE RBI RGSEAG RLEGP ROSCA RRBs RTGS SBLP SCGS SD SE SGSY SHGs STEP TE TRYSEM UK UN UNICEF USA VIF VRS WHO

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Nutrition Programme for Adolescent Girls New Pension Scheme National Rural Development Partnership National Rural Employment Guarantee Act Other Depository Organisations The Organisation for Economic Co-operation and Development Overall Technical Efficiency Primary Agricultural Credit Societies Poverty Alleviation Programmes Pradhan Mantri Jan Dhan Yojana Point of Transaction Public Relation Pure Technical Efficiency Reserve Bank of India Rajiv Gandhi Scheme for Empowerment of Adolescent Girls Rural Landless Employment Guarantee Programme Rotating Savings and Credit Association Regional Rural Banks Real Time Gross Settlement Self Help Group Bank Linkage Programme Savings and Credit Groups Standard Deviation Scale Efficiency Swarnajayanti Gram Swarojgar Yojana Self Help Groups Support to Training and Employment Programme Technical Efficiency Training of Rural Youth for Self Employment United Kingdom United Nation The United Nations Children’s Fund United States of America Variance Inflation Factor Variable Returns to Scale World Health Organization

List of Figures

Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 2.4

Fig. 2.5

Fig. 2.6 Fig. 2.7 Fig. 2.8 Fig. 3.1

The different facets of microfinance Growth of financial inclusion accounts (Source Global Findex Report, 2017) Adults saving money in 2017 (Source Global Findex Report, 2017) The effect of Jan Dhan Yojana in India (Source The financial Inclusion Insights with Bill and Melina Gates Foundation Report, 2017) Distribution of households who took credit from various sources (Source NABARD All India Rural Financial Inclusion Survey 2016–17) Average deposit accounts opened under PMJDY scheme (Source Economic Survey Report 2016–17) The outreach of Aadhaar and Jan Dhan Yojana (Source Economic Survey, 2016–17) Linkage between empowerment and microfinance institutions (Source Compiled by Researcher) Age profile of the respondents (Source Calculated by authors)

19 20 21

25

26 31 32 75 96

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Fig. 3.2 Fig. 3.3 Fig. 3.4 Fig. 3.5 Fig. 3.6 Fig. 3.7 Fig. 3.8 Fig. 3.9 Fig. 4.1 Fig. 4.2 Fig. 4.3 Fig. 4.4

List of Figures

Occupation profile of the respondents (Source Calculated by author) Marital status of the respondents (Source Calculated by authors) Literacy levels of the respondents (Source Calculated by authors) Caste profile of the respondents (Source Calculated by authors) Religion of the respondents (Source Calculated by authors) Family type of the respondents (Source Calculated by authors) Area of domicile of the respondents (Source Calculated by authors) Income profile of the respondents (Source Calculated by authors) Credit utilization pattern among the borrowers (Source Calculated by authors) Productive utilization of credit patterns (Source Calculated by authors) Distribution of respondents among various categories of microenterprise (Source Calculated by authors) Average income earned by different categories of microenterprises (Source Calculated by authors)

96 97 97 98 98 99 99 100 109 110 110 111

List of Tables

Table Table Table Table Table Table Table Table Table Table Table Table

2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.10 3.1 3.2

Table 4.1 Table 4.2 Table 4.3 Table 5.1 Table 5.2 Table 6.1

Different indicators on the way to development of India Global Hunger Index score of India Status of health and education in India Different concepts of financial inclusion Adult financial literacy in different countries Evolution of financial inclusion initiatives in India Number of commercial bank branches Different models of microfinance Journey of MFIs in India Different development parameters of India Cronbach’s Alpha score Result of F -test and t-test for perception level of borrowers and non-borrowers Cronbach’s Alpha score Result of F -test and t-test for pre- and post-income Result of F -test and t-test for preand post-consumption level Result of regression analysis Result of coefficients for employability Active MFIs in West Bengal

16 16 17 19 23 25 28 62 64 68 94 101 108 111 112 119 120 127

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List of Tables

Table 6.2 Table 6.3 Table 7.1 Table 7.2 Table 7.3 Table Table Table Table Table Table

8.1 8.2 8.3 8.4 8.5 8.6

Descriptive statistics of selected input and output variables DEA analysis of MFIs under CCR and BCC model Result of F -test and t-test for economic empowerment of the borrowers Result of F -test and t-test for psychological empowerment of the borrowers Result of F -test and t-test for social empowerment of the borrowers Percentage of contribution of the respondents Determinants of economic empowerment Percentage of participation in decision making Determinants of psychological empowerment Percentage of participation in social activities Determinants of social empowerment

129 130 144 144 145 155 156 157 158 159 160

1 Introduction

1.1

Background of the Study

One of the biggest challenges of any developing or underdeveloped economy is the poverty and the related issues arising out of it. Poverty is a multidimensional social incident. The meaning of poverty varies along with the framework of place, situation, society, demography and economy. It may be the need for what is essential for material well-being like food or maybe it is the lack of employment or the basic infrastructure like water, road, health facilities, etc. Whatever the defining criteria are but it can surely lead to numerous consequences like social exclusion, gender discrimination, parallel economy, unemployment, exploitation, malnutrition, etc. in the economy. In a simple sense, poverty needs various resources leading to physical dispossession. The United Nations (UN) organization declared eight goals which have been referred as Millennium Development Goals (MDGs) or Sustainable Development Goals (SDGs) in 2008 where all 191 UN member states have decided to achieve these by 2015. Among these, the first goal was all about the

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4_1

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reduction of poverty. This shows the significance of the issue. So, post2015, a close observation on the consequence of various activities for the stated eight goals especially on poverty eradication is absolutely necessary. It has been often observed that malfunction of financial sectors to offer affordable credit to the underprivileged is one of the key elements that support the vicious encircle of economic, social and demographic configurations that enhance poverty. Throughout the globe, various proposals have been taken to eliminate or minimize poverty out of the economy and ensure sustainable growth. Among these, financial inclusion is being considered as one of the effective ways to break the existing poverty cycle worldwide (Park & Mercado, 2015). So, it has become a budding global issue nowadays. Complete financial inclusion can only be possible if any wide variety of financial product exists to suit individuals’ needs and conditions (Karmakar et al., 2011). Only after the completion of every dimension, poverty eradication can be possible. To prevent economic crisis, inclusive policy and sustainable growth together can act as one of the most commanding tools for combating the critical situation if any, happens by some economic catastrophes (Ali & Zhuang, 2007). Both from government and non-government side, measures and policies have been instigated and implemented for sustainable growth and development. Our nation is not an exception to it. India is a nation comprising of—“rural, semi-urban and urban zones. Among these, villages dominate the nation geographically. Poverty, illiteracy, unemployment, poor health, etc. are the issues that influence our economy as well”. As per Census (2011), the overall people of India are 121, 01, 93, 422 among this the percentage of poverty is 21.9% (urban—13.7%; rural—25.7%). The literacy rate is only 74.04%. The demographic profile especially income and savings pattern vary significantly from place to place. The rate of employment is also significant. Among all the rural households who receive salaries, 5% earn from government whereas 3.57% only engaged in the private sector. Further, 22.47% of the world unbanked adults (age 15+) belongs to our country (Global Findex Report, 2021). As a result, due to the absence of awareness and illiteracy, the money market is mostly regulated by the unorganized sector until now. As a

1 Introduction

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result, the overall development of our nation hampers. In this scenario, the government of India along with RBI introduced various initiatives to include the excluded mass population into the organized money market. In India, since the late 1960s, many policy initiatives have been undertaken for making banks to serve the mass. But still, a large population is financially excluded. So, finance or credit in a small amount and with easy repayment mode which has been termed as “microcredit or finance” was introduced for this purpose. In the backward region of West Bengal, the districts, namely Purulia, Bankura and Paschim Medinipur, comprise of mostly rural areas with low income-generating people. The habitat of this region is still reluctant to access the banking facility due to financial illiteracy towards the banks. Also, accessibility is one of the major problems due to the interior locations of the villages. So, microfinance institutions (MFIs) can be an easy option to operate and henceforth, it plays a useful role in enabling them socially and financially inclusive in society. In this backdrop, the current study seeks to analyze the role of microfinance institutions towards the generation of employment and livelihood transformation of the poor rural women through providing microcredit.

1.2

Microfinance Institution

Robinson (2002) observes, “Microfinance is small-scale financial services, mainly credit and savings offered to people who are engaged in farming, fishing or work as a shepherd and it leads to all kinds of financial services offered to low-income households and enterprises”. It also can be referred as the provision of savings, lending and other monetary services and products of very little amounts to the needy residents in rural, semi-urban areas for supporting them to lift up their income level and advance their living standards. Microcredit, the most popular offerings of microfinance institutions, is the practice of providing small credits to poor individuals who are not conventionally being served by the commercial bank. MFIs denote formal financial establishments prospering in different corners of the world especially Bolivia, Bangladesh and Indonesia. It was first initiated in Bangladesh during the 70s and 80s

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by Nobel laureate Mohammad Yunus and the institution he established Grameen Bank. “Under the periphery of microfinance institutions, most of the borrowers are funding self-employment actions, and many start off by taking advances as little as $75, repaid over a number of months or a year”, says Morduch (1999). Only a few programs require putting up collateral, enabling prospective entrepreneurs with few assets to getaway positions as poorly paid wage laborers or farmers. The programs direct to creative such as “group-lending” contracts and new approaches about subsidies as the solutions to their achievements. Group-lending agreements productively convert a borrower’s neighbors to co-signers to loans, lessening the problems created by informational asymmetries between lender and credit borrower. Generally, the objective of the microfinance program is to rectify market failure while delivering credit and non-credit services to the rural poor. “Majority of the microfinance program declare that their primary target is to lessen rural poverty by sending financial and non-financial services to the poorest family units; especially to the female in those households”, states Hulme (2000). But later on, microfinance institutions also gain rapid access among the urban poor to cater their credit need and associated issues. Well-designed and operating financial institutions serve various financial purposes to people. The purposes range from credit creation, enhance savings, secure future, risk management, etc. Even with the momentum observed in economic development, many countries suffer from the inequalities affecting the growth adversely (Zhuang & Hasan, 2008). The absence or the least formal organizational arrangements for sustainable financial services is regarded as one of the basic reasons that compel the poor to increasingly turn to and depend upon the informal financial institutions. Though, microfinance is not a new concept. Its history can be traced to early 1700s. But after Dr. Mohammad Yunus’s conquer, the Nobel Prize microfinance concept has got a new dimension and got exposure globally. Since independence, the government of our country has been making uninterrupted efforts in delivering microfinance to the rural poor through cooperative institutions. But it could not achieve remarkable targets. Besides that, no specific provisions were made for credit creation for the urban poor. To achieve the socio-economic objective

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and to make formal banking sector accessible to deprived people even in the remotest part of the country, the Government of India nationalized Commercial Banks (1969, 1980) along with the establishment of Regional Rural Banks in 1975. Social banking became the trend during 1980–90. It was made compulsory to all the banks (nationalized, cooperative and regional rural banks) to supply credit to the priority sector. These institutions were encouraging poverty alleviation programs (PAPs). So, the government has constantly been implemented poverty mitigation program through various institutions like NABARD, Co-operatives, regional rural banks (Sivachithappa, 2013). But regardless of the addition of banking network and implementation of PAPs, a huge part of the inhabitants remained excluded from the coverage of banking services and sustained in poverty for years. To break up the vicious cycle of poverty, generating microcredit and allied services are one of the effective solutions to poverty alleviation program. People, especially with low and limited income, have perceived biases to access the banking services but microfinance institutions are comparatively close to this population. Often microfinance and microcredit have been used to refer to the same meaning but there is a disparity between these two concepts (Sengupta & Aubuchon, 2008). Microcredit stands for sanctioning credit of little amount with easy repayment methods, the offerings are more welcoming among the population of lower-income groups. Whereas, microfinance is one kind of movement that thinks about a place where low-income family units have enduring admission to a variety of high-quality financial services to sponsor income-generating activities, build access, stabilize consumption and risk protection. The microfinance program has an impact in Indian economy for advancing micro-entrepreneurial activities to create productive assets attached with employment generation. All these services are not confined to lending money, but also include savings, insurance and money transfer. In the context of the above discussion, the role of microfinance institutions has been analyzed towards financial inclusion.

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1.3

Financial Inclusion

The explanation of financial inclusion differs along with places and geographies, based on the point of social, economic and financial advancement; the configuration of the financial sector; socio-economic features of the financially excluded sections; and also, the frequency of emphasis given by the system and government on financial inclusion. Financial inclusions have been defined by various dimensions along with time. Rangarajan Committee (2008) report said, “Financial inclusion may be explained as the method of guaranteeing access to financial services timely with ample credit where required by vulnerable clusters such as weaker sections and low earner groups at a reasonable cost” (Sarma, 2008). Murari and Didwania (2010) denotes it as a, “Delivery of financial services at a reasonable cost to the vast sections of the disadvantaged and low-income groups including family, enterprises, small and medium enterprises, traders”. RBI publication on FI (2009) stated that it is the nonexistence of price and non-price obstacles for utilizing financial services. In the literature, financial inclusion has been explained with a larger concern of social inclusion in society. According to Leyshon and Thrift (1995), “Financial exclusion processes are those that serve to put off definite individual and social groups from attainment admission to the formal financial system”. Sinclair (2001) explains, “Financial exclusion as the short of the capability to access essential financial services in the right form. Exclusion can be the consequences due to issues with access, situations, prices, marketing or self-exclusion with reference to negative occurrences or perceptions”. According to Carbo et al. (2005), “Financial exclusion is the inability of some societal groups to use the financial system”. FI can be measured in diverse ways. It may be indicated by Global Financial Inclusion (Global Findex) Database which shows the measurement pattern of saving, borrowing, transactions and risk management of adult persons in 148 economies. According to these statistics, 50% of adults globally have an account at a formal financial institution, but account penetration changes extensively across regions, income groups and individual quality. Further, this report mentions that 22% adults

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have saved at a formal financial institution for the last 12 months, and 9% adults have taken out a new loan from a formal financial organization in the previous year. Even though half of the adults around the globe remain unbanked, at least 35% among them face barriers to use the account and that might be addressed by public policy (Demirgüç-Kunt & Klapper, 2012). In our country, three dimensions have been identified to develop a relative index (CRISIL Inclusix) for measuring the level of financial inclusion. It is India’s initial comprehensive measure of financial inclusion in an index form. This comes together as the critical parameters of fundamental financial services which are (1) Branch penetration (BP)— it has been calculated as the number of bank branches per 0.1 million population, (2) Deposit penetration (DP)—it has been measured as number of saving deposit accounts per 0.1 million population and (3) Credit penetration (CP)—average of three measures, specifically figure of credit accounts per 0.1 million population, figure of small creditors loan accounts per 0.1 million population and quantity of agriculture advances per 0.1 million population which has been used for credit penetration into one single matrix. The different dimensions are interrelated and reinforce each other. So, in line with this thought the accomplished level of financial inclusion has been analyzed by the MFIs in the selected region.

1.4

Women Empowerment

It has been observed that culture and societies that distinguish on the basis of gender, indulge the cost of diverse negative consequences like more poverty, lesser economic growth, weaker governance and a comparative substandard living standard for all people (Walby, 2009). Considering the macro level, it is due to 70% of the poor worldwide who are women. Women in our country are also discriminated and suffered unequally from poverty and socio-economic status compared to men. Majority of the women are occupied in unpaid household responsibilities in the country. Additionally, along with household management

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sometimes, she has to earn money to support the family’s consumption needs. The majority of women, as labor, work in agricultural fields, construction works, housekeeping, factories, etc., and a small number of them are self-employed and occupied in production or incomegenerating activities. The female counterpart of a society has a higher unemployment rate than men in every country and make up the greater portion of the informal sector of most economies (Sarumathi & Mohan, 2011). They represent the financially excluded population who need microfinance services. Supporting women to access microcredit generates a multiplier consequence that helps to enhance the consequence of a microfinance institution’s activities, helping several generations. Microfinance institutions support the “bottom-up” aspects, focus the community, giving concentration to female, and, most essentially aim to help the underserved. One of the important impacts of microfinance activities is empowering the weaker section of the society. Women make up a large percentage of microfinance beneficiaries. Empowerment has been measured as one of the key poverties easing strategy nowadays. It refers to empowerment as the growing poor people’s liberty of choice and act that form their own lives. It classifies four key elements that can change power relations between poor people and powerful actors: access to information, inclusion and participation, social accountability and local organizational capacity (Narayan, 2002). It is one of the major powerful ways to accelerate development and ensure gender equality in society as inequality can hinder development (Sen, 1997). An increasing body of proof points to linkages between empowerment and development effectiveness at both the society-wide level and the grassroots level (Narayan, 2002). Empowerment moves forward good governance that boosts growth prospects. As per CGAP, long-standing microfinance institutions even report a reduction in violence targeted at female since the inauguration of microfinance. Women empowerment is a qualitative measure and therefore difficult to quantify (Mahmud et al., 2012). Sometimes networking, communication and mobility (Swain & Wallentin, 2009) or maybe voting, political involvement, informally participation in community-problem solution (Bardhan & Klasen, 1999; Beteta, 2006) lead to female empowerment. The United Nations revealed eight specific Millennium Development

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Goals commonly known as MDGs or SDGs, expected to be fulfilled by 2015. Gender parity and empowerment of women regarded as the third target of the Millennium Development Goals explaining the magnitude of the issue. Under this backdrop, this study is an endeavor to explore empirically the actual role of microfinance institutions on economic, social and psychological empowerment of the women borrowers from the particular backward districts of West Bengal, India.

1.5

Motivation of the Study

To fight against unorganized money market and dominance of private lenders, both central and state government along with Reserve Bank of India had been initiated banking facilities in the form of commercial banks, cooperative banks and regional rural banks with maximum penetration in urban and rural part as well. But still, people, especially with a less or small income, do not come forward as expected to avail banking services. Though after Pradhan Mantri Jan Dhan Yojana (PMJDY), the number of accounts has been increased nationwide still a larger population uses the bank account only to avail a few selective facilities (Morawczynski et al., 2010). Banks are having certain features like sufficient formality, rigidity in their rules and regulations, rigid business procedure, formal communications issues, queuing time, physical distance to bank, fixed banking hours, etc., which prohibit the unbanked population especially the rural people. The rural people generally are less educated, try to avoid pen and paperwork, lack in formal communication technique and comfortable in informal settings, etc. In this juncture, MFIs acceptance was high as it come with high flexibility, greater informality and friendly business nature. Microfinance institutions have been designed with certain objectives like rural credit disbursement, rural penetration, sustainable growth and financial inclusion, empowerment of the feminine section of the society with economic, social and psychological dimensions. So, in this context, it is very much essential to have a grassroot-level picture involving face-to-face interaction with the beneficiaries and directly observing the impact on them. This was the principal

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drive to conduct the study covering three districts (Purulia, Bankura and Paschim Medinipur) of West Bengal. Upon the basic-level study, more effective future policies can be designed in the future in a better manner.

1.6

Objectives of the Study

Given the background, the principal objective of the study is to analyze the role of MFIs in financial inclusion along with women empowerment in the districts of Purulia, Bankura and Paschim Medinipur. The principal objective is further decomposed into the following specific objectives: . To observe the initiatives of MFIs in promoting financial inclusion. . To track down about the perception about MFIs among the people in the proposed area. . To analyze the utilization of credit by the borrowers towards generating income. . To find out the impact of microcredit on the rural dwellers or BPL cardholders in terms of employment. . To examine the performance of active MFIs operated in the districts of Purulia, Bankura and Paschim Medinipur. . To find out the role of MFIs on economic, psychological and social empowerment of the women borrowers. . To identify the determinants that influence the economic, psychological and social empowerment of the female borrowers.

1.7

Scope of the Study

Financial inclusion is a dynamic issue which needs more focus and coverage to enhance the sustainable growth of the economy. For more effective policies and measures, detail studies are needed covering more areas along with a focus to the bottom of the pyramid studies related to it. This study is supposed to provide the ground reality regarding the

1 Introduction

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actual involvement of the MFIs operating in the selected regions of the state towards the attainment of different aspects of financial inclusion and the consequent development of the individual as well as households considering their economic, psychological and social aspects of life. The study had covered a direct interaction with both beneficiaries and non-beneficiaries of the selected three backward districts of West Bengal accompanied by a careful examination of the financial and operational data (country-wise) of selected MFIs to fulfill the stated objectives. The present study can give inputs for further studies in the future applicable in other parts of our country too. However, the findings of the study and the further possible recommendations may lose validity with the changing time period and revising government policies.

1.8

Structure of the Book

The book consists of nine chapters containing several sections and subsections. In this chapter, a brief introduction has been given briefing the background of the study followed by the research problem and objective of the study. The chapter also states the scope of the study. Chapter 2 describes a thorough theoretical background covering the issues of financial inclusion, microfinance and women empowerment. The chapter deals with the journey of financial inclusion in our country and beyond. A fine detailing has been incorporated here about the different instruments, institutions, policies and committees inside our country that accelerate the outreach of financial inclusiveness. For more comprehensive understanding, the progress of financial inclusion passage in different countries, all-encompassing of developed, developing and backward has been mapped in this chapter. Also, this chapter covers the concepts from a different point of view, the role, implications and the necessity of these three areas in detail. It also emphasizes the interlinkage between these three areas and how they influence each other. Chapter 3 outlines a detailed study in search of the true perception tracking among the people (both borrowers and non-borrowers) in the specified zone. The chapter stands on the context of earlier studies followed by empirical findings with detail analysis and findings.

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Chapter 4 provides the analysis and findings supported by the empirical findings of the investigation. This chapter gives a detailed emphasis on the influence of credit utilization patterns of the respondents. This chapter also integrates the earlier studies, details about the research design, analysis and findings. Chapter 5 elaborates the linkage between microfinance and employability of the respondents. Backed by the empirical evidences, the chapter critically analyzes the possibilities of employment generation of the beneficiaries over time for her household as well as to others. Chapter 6 depicts about the performance-level analysis of the active MFIs in the selected study areas. The details about the methodology, analysis and key findings have been discussed in this chapter. Chapter 7 discusses about the role of MFIs towards empowerment in the selected area. This chapter synchronizes the earlier studies, research design, analysis and findings towards a comprehensive understanding. The empowerment comprises of three dimensions—economic, psychological and social empowerment for the selected sample in the specified region. Chapter 8 is a detailed study that has also been incorporated about the identification of determinants that influence the Economic, Psychological and Social Empowerment of the Female Borrowers. The description of different variables used, along with methodology, the analysis of the outcome and findings help to have a clear idea about the influencing variables towards empowerment. Chapter 9 finally provides a summary and conclusion along with the contribution of the study. The chapter also discusses recommendation and policy implications along with the limitation and indicating the direction for future study relating to the study. At the end of the study, bibliographic references have been given and arranged alphabetically according to the surname of the author.

1 Introduction

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References Books, Journal, Research Paper, Working Papers, Reports, etc. Ali, I., & Zhuang, J. (2007). Inclusive Growth toward a Prosperous Asia: Policy Implications (Working Paper Series No. 97). Economics and Research Development. Bardhan, K., & Klasen, S. (1999). UNDP’s Gender-Related Indices: A Critical Review. World Development, 27 (6), 985–1010. Betata, H. C. (2006). What Is Missing in Measures of Women Empowerment? Journal of Human Development and Capabilities, 7 (2), 221–241. Carbó, S., Gardner, E., & Molyneux, P. (2005). Financial Exclusion. Springer. Demirguc-Kunt, A., & Klapper, L. (2012). Measuring Financial Inclusion: The Global Findex Database. The World Bank. Hulme, D. (2000). Impact Assessment Methodologies for Microfinance: Theory, Experience and Better Practice. World Development, 28(1), 79–98. Karmakar, K. G., Banerjee, G. D., & Mohapatra, N. P. (2011). Towards Financial Inclusion in India. SAGE Publications India. Leyshon, A., & Thrift, N. (1995). Geographies of Financial Exclusion: Financial Abandonment in Britain and the United States. Transactions of the Institute of British Geographers, 312–341. Mahmud, S., Shah, N. M., & Becker, S. (2012). Measurement of Women’s Empowerment in Rural Bangladesh. World Development, 40 (3), 610–619. Morawczynski, O., Hutchful, D., Cutrell, E., & Rangaswamy, N. (2010). The Bank Account is Not Enough: Examining Strategies for Financial Inclusion in India. In Proceedings of the 4th ACM/IEEE International Conference on Information and Communication Technologies and Development (p. 24). ACM. Morduch, J. (1999). The Microfinance Promise. Journal of Economic Literature, 37 (4), 1569–1614. Murari, K., & Didwania, M. (2010). Poverty Alleviation through Financial Inclusion: An Analytical Study with Special Reference to India. Revelation, 3(2), 60–72. Narayan, D. 2002. Empowerment and Poverty Reduction: A Sourcebook. World Bank. Accessed on October 5, 2017. Retrieved from http//openknowledge. worlfdbank.org/handle/10986/15239

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Park, C. Y., & Mercado, R. (2015). Financial Inclusion, Poverty, and Income Inequality in Developing Asia (Working Paper Series No. 426). Asian Development Bank Economics. Rangarajan Committee Report on Financial Inclusion. (2008). Ministry of Finance, Government of India. RBI Report on Currency and Finance 2009–12, Report on Currency and Finance, V (3), RBI. Accessed on August 9, 2016. Retrieved from https:/ /rbi.org.in/Scripts/AnnualPublications.aspx?head=Report%20on%20Curr ency%20and%20Finance Robinson, M. (2002). The Microfinance Revolution: Sustainable Finance for the Poor. World Bank. Sarma, M. (2008). Index of Financial Inclusion (Working Paper No. 215). Indian Council for Research on International Economics Relations. Sarumathi, S., & Mohan, K. (2011). Role of Micro Finance in Women’s Empowerment: An Empirical study in Pondicherry Region Rural SHG’s. Journal of Management and Science, 1(1), 1–10. Sen, A. K. (1997). From Income Inequality to Economic Inequality. Southern Economic Journal, 64 (2), 384–401. Sengupta, R., & Aubuchon, C. P. (2008, January/February). The Microfinance Revolution: An overview. Federal Reserve Bank of St. Louis Review, 90. Sinclair, S. P. (2001). Financial Exclusion: An introductory Survey. Edinburgh College of Art/Heriot Watt University. Sivachithappa, K. (2013). Impact of Micro Finance on Income Generation and Livelihood of Members of Self-Help Groups—A Case Study of Mandya District, India. Procedia-Social and Behavioral Sciences, 91, 228–240. Swain, R. B., & Wallentin, F. Y. (2009). Does Microfinance Empower Women? Evidence from Self-Help Groups in India. International Review of Applied Economics, 23 (5), 541–556. Walby, S. (2009). Gender and the Financial Crisis. Lancaster University. Zhuang, J., & Hasan, R. (2008). Framework of Inclusive Growth Indicators Key Indicators for Asia and the Pacific 2011 Special Supplement. Asian Development Bank.

Websites and Reports The Global Findex Report. (2021). Accessed on January 23, 2022. Retrieved from http://www.worldbank.org/en/publication/globalfindex/Data

2 Financial Inclusion, Microfinance Institutions and Women Empowerment

2.1

Financial Inclusion in India and Abroad

2.1.1 Introduction India is a developing country. Certain elements like the enhancement of national income, level of employment, government policies, human resources, natural resources, capital formation and technological advancement, etc. accelerate the progress of any economic advancement. In spite of various measures taken, many countries still suffer from deprivation and backwardness which acts as an obstacle in the path of growth and development (Zhuang & Hasan, 2008). Our country also has the exact scenario. A few elements can justify this statement. World Bank has been introduced Head Count Ratio (HCR), a measurement which reflects the total population in a country or region that exists, or survives, below the poverty line and GINI index as the measurement of inequality and our country has the following scenario along with urban slum dwellers in the below mentioned time frames (Table 2.1). Moreover, a good number of residents live below the poverty line and are deprived of various primary opportunities like education, health, © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4_2

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Table 2.1 Different indicators on the way to development of India Elements

Value

Year

Head Count Ratio (HCR)

29.89% ($1.99 per day) 35.71% 24%

2016

GINI Index Urban population living in slums

2011 2014

Source World Bank Data Note* = Data are available on different years for different elements

Table 2.2 Global Hunger Index score of India Total no. of countries rank

India’s rank

Year wise GHI score of India

119

100

1992

2000

2008

2017

46.2

38.2

35.6

31.4

Source Global Hunger Index 2017 Report published by NITI Aayog

nutrition, housing, employment opportunities, etc. for a healthy and decent lifestyle till date. IFPRI (International Food Policy Research Institute) computes the Global Hunger Index (GHI) to reflect the comprehensive measurement of hunger and indicates the need of nutrition wherever needed by including data from the “Food and Agriculture Organisation of the United Nation (FAO), World Health Organisation (WHO), the United Nations Children’s Fund (UNICEF) and World Bank”. According to this report, the position of our country is mentioned in Table 2.2. Apart from that, the scenario related to health (mortality rate) and education (literacy rate) have to be mentioned for a better understanding of India’s current position. So, corrective measures need to be followed to improve the current status of our nation (Table 2.3). Access to money by the poor and employment generation are the preconditions for poverty diminution and sustainable economic condition. Betterment of the monetary sector and developing access to funding may accelerate sustainable improved economic scenario by dropping income disparity and poverty.

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Table 2.3 Status of health and education in India Elements

Figures

Health

Value (Per 1000 lives) 23 29 28 52

Mortality rate

Education Socio-economic

Literacy Rate Fertility Rate (total birth per women)

Early neo-natal Neo-natal Peri-natal Under 5 64.8% 2.3 (2015)

Source Census data, 2011

2.1.2 Financial Instruments and Institutions: An Overview As a field of study, finance is dealing with the provision of both assets and liabilities over space and time, often with conditions of uncertainty. In the simplest form, finance stands for fund management. The financial system consents the replace of funds between investors, lenders and borrowers at both national and worldwide levels. It is one of the important measurements of sustainability of the nation. A contemporary financial system covers “financial institutions, financial instruments, financial markets and financial services”. Financial market and financial institutions play a crucial role in this system. Financial market helps to assist the exchanges of financial instruments and securities whereas financial institutions engaged in the business of money transaction and both altogether contribute to the organized money market of the country. These financial institutions are composed of both banking and non-banking sectors altogether. Within the configuration of the underdeveloped financial system, the scope of credit access is restricted; people and firms are controlled by the accessibility of their own funds or alternatively, have to way out to more expensive informal foundations. It results in lesser economic activities that finally lead to lesser economic growth. On the contrary, in developed economies where a large portion of the population is financially

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included, it becomes ever more difficult for the minority excluded people to incorporate with the society.

2.1.3 Financial Inclusion Financial Inclusion (FI) is an expanse which have prodigious significance and bearing. The paricipant in the financial inclusion arrangement are able to initiate and expand their business in a better way and also able to invest in various area like lifestyle, health and education for themselves and their households. Along with that they also able to handle the risks for investment and income generation in a more successful way. Financial inclusion, in a broader spectrum, epitomizes access to the formal financial segment for marginalized and financially excluded. The concept has appeared to the forefront of public discussion in recent times (Hon’ble Prime Minister’s address on 6th November 2015 at Delhi Economics Conclave). It is regarded to be a powerful tool for sustainable development worldwide (Bagli & Dutta, 2012; Joseph & Varghese, 2014). Over the episode of time financial inclusion/exclusion can be explained by different resource persons that have been mentioned below (Table 2.4). Financial inclusion in true manner would necessitate going beyond mere introductory of bank accounts and also support to operate more functional access points, availability of multiple finance related services ahead of savings accounts, availability of credit, insurance, and remittances, and above all seeing that the services are ‘demand driven’ and ‘accountable’. The different facets of financial inclusion have been mentioned in Fig. 2.1. The goal of financial inclusion program can be mentioned as: . Economic independence: It concerns with the bottom of the pyramid population and able to impart income, employment and savings. . Mobility of savings: It generates savings to the economically weaker segment of the society which can be further utilized for better life cycle.

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Table 2.4 Different concepts of financial inclusion Author/ Institutions Kempson and Whyley (1999)

Leeladhar (2006) Sarma and Pais (2008) Murari and Didwania (2010)

Definitions Exclusion as a dynamic process with many households moving in or out of using financial services and sometimes lacked access to it and it mostly depending on their income levels and other personal and social characteristics Delivery of “banking services” at reasonable price to the huge sections of disadvantaged and low-income groups The process that ensures the ease of access, availability and usage of the formal financial system for all members of an economy Delivery of financial services at a reasonable cost to the vast sections of the disadvantaged and low-income groups inclusive of households, ventures, Small and Medium-sized Enterprises, merchants etc.

Source Compiled by Researcher

Credit Bank Accounts

Saving Financial Inclusion

Financial Advice Insurance

Payment and Remittance

Fig. 2.1 The different facets of microfinance

. Poverty eradication: To eradicate the vicious cycle of poverty, financial inclusion’s role is vital. It helps to build confidence, awareness, enhance employment generation, savings and so on. . Sustainable lifestyle: A better lifestyle includes health, education, awareness, savings and income and all are interdependent in nature. To be an ingredient of the financial inclusion cycle, one can have a more decent and sustainable lifestyle throughout. . Empowerment: Through the journey of FI, the borrowers can enrich themselves with the qualitative features like confidence, leadership,

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teamwork and so on which eventually turn them psychologically, socially, politically and economically strong. The level of FI varies extensively in different economies. The Global Findex database is the most comprehensive database of World Bank reflecting the behavior of adults towards finance. The level of financial inclusion here is measured by possessing an account either in any financial institutions or in any mobile money accounts. The progress scenario of Global Findex is (Fig. 2.2). There have been Government policies, legislation, voluntary charters as “codes of practice” towards recuperating financial inclusion globally. A lot of organizations are working towards the accomplishment of financial inclusion all the way through the length and breadth of the globe. Due to the initiative offered by the United Nations Year of Micro Credit 2005, policymakers paid closer attention to uplift financial inclusion worldwide. Hence, financial inclusion assists people to access vital formal financial services at an affordable cost, accelerates the circulation of money,

Fig. 2.2 Growth of financial inclusion accounts (Source Global Findex Report, 2017)

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increases gross domestic product (GDP) and enhances faster growth. Various institutions are executing their role to include more and more areas which are still financially excluded. The threat lies still where majority of the areas prefer unorganized credit sources in a time of credit need (Fig. 2.3). The report of World Bank confirms that about four-fifths of adults in our nation have opened bank accounts by the year 2017 and 36 of account holders are already utilizing their accounts to make or receive digital transactions. So, for sustainable progress in the long run, inclusive and broad-based strategy across all the sectors and sections of the economy is needed (George, 2011). Inclusive policy nurtures the diverse facets towards a better state of the economy, household and lifestyle. In this framework, initiatives like financial inclusion can enhance and mobilize the forces which cause an obstacle in the economic growth of our country. The obstruction towards financial inclusion can be classified into three categories: societal, supply and demand factors (European Commission, 44) and the reasons behind exclusion are complex and it could not be placed into isolation. Along with that, the reasons vary along with place, time, demography, economy, etc. Impact of financial exclusion on societies is analyzed and reviewed by many observers. Due to its widespread

Fig. 2.3 Adults saving money in 2017 (Source Global Findex Report, 2017)

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consequences on societies, especially considering the issue of poverty, financial exclusion has expanded more importance from policymakers in present times worldwide. So, financial exclusion is all about the betterment of marginal sections of the society and adds to a much wider issue of social exclusion. Initially “Financial Exclusion” has been used by geographers considering about bank branches closure in the USA and the UK due to recession in the early 1990s and maturing the issue of economic development in financially excluded areas (European Commission 9). In the beginning, the concept has been restricted to geographical access to services specifically to banking outlets. But gradually, it seemed to use in a broader perspective covering individuals who had inhibited to access to mainstream financial services due to income and social causes (Kempson & Whyley, 1999). Since then, the aspect of financial exclusion or inclusion has been redefined (Mohan, 2006). Various factors may be accountable for financial exclusion globally. However, Blue Book of the United Nations states that personal and cultural features, location, the impact of national financial developments as well as magnetism of the products all this control the span of financial exclusion in any financial system. In this connection, the term financial literacy recently caught a lot of attention in terms of influencing financial inclusion or exclusion. It is regarded as to be a multifaceted phenomenon, made up of a blending of knowledge, attitudes and behaviors. Based upon the sum of these three components, the financial literacy of G20 countries have been given thereafter (Table 2.5). The effect of financial exclusion can be generally divided by financial (loss of business opportunities, creation of high-cost alternative sources of credit) and social (lack of self-esteem, self-isolation, lack of confidence) outputs (Gloukoviezoff, 2007; Kempson et al., 2004). RBI also mentions the loss of business opportunities for banks as a consequence of Financial Exclusion (RBI Report on Currency and Finance 2009– 12). Another significant consequence of exclusion is acknowledged as the creation of high-cost alternate providers of financial services (Kempson et al., 2004). Among the most basic issues in the developing countries, financial exclusion has been considered as a crucial one. This matter has

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Table 2.5 Adult financial literacy in different countries Countries

Financial literacy scores out of 21 (Financial knowledge+attitudes+behavior)

France Norway Canada China Korea Germany Netherlands Indonesia United Kingdom Turkey Russian Federation Mexico Brazil India Argentina Italy Saudi Arabia

14.9 14.6 14.6 14.1 13.9 13.8 13.4 13.4 13.1 12.5 12.2 12.1 12.1 11.9 11.4 11.0 9.6

Source OECD info report on adult financial literacy in G20 countries, 2017

been on the national agenda since 2004–2005, after the annual policy review of Reserve Bank of India (RBI).

2.1.4 Journey of Financial Inclusion in India Financial inclusion apparently turned into a policy compulsion for the sake of sustainable growth and development. Certain factors both from supply and demand side influence the extent of financial inclusion. In 1904, the financial inclusion activities were matured with the initiation of the Co-operative system in our country. The topic got momentum in 1969 during the nationalization of major commercial banks and introduction of Lead Bank Scheme thereafter in the mid-1970. Multiple numbers of bank branches were inaugurated throughout the country including remote and previously neglected areas. But still, a large section of the population was financially excluded from the mainstream (Chattopadhyay, 2011). The journey of growing access to the payments systems for the financially excluded individuals began to be highlighted

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from 2005. In 2005, RBI initiated a financial inclusion movement where banks promote the involvement of every household at the district level via saving accounts for the “unbanked” citizens (Ramasubbian & Duraiswamy, 2012; Ramji, 2009). In the initial stage, 24 banks were recommended by the RBI to open basic no-frill accounts along with simplification of “know your customer (KYC) norms”. Also, banks were persuaded to provide revolving overdraft facilities without claim on collateral, think about the use of the MFIs and non-government organizations (NGOs) to afford financial services as banks were perceived as the foremost channel to enlarge outreach of financial services in our country though the Indian postal system has a bigger network of branches and also offers financial services. But with outdated technology and poor customer service, it failed to be accepted in the mindset of the beneficiaries or the credit seekers. However, later on, India post went through various advancements towards ensuring financial services. In addition to that underneath the chairmanship of Rangarajan, a committee on Financial Inclusion was formulated by the Government to boost up the financial inclusion drive nationwide. Also, in 2014 initiative like “Pradhan Mantri Jan Dhan Yojana” has been introduced to cover more areas under the inclusive financial network of India. The key initiatives about the journey of FI in our country can be presented like below (Table 2.6). A good number of financial institutions operate to promote financial inclusion. Financial institutions like commercial banks, regional rural banks, cooperative banks, NBFCs, mutual funds, NGOs, etc. endlessly work towards attaining further inclusion. Initiatives like Pradhan Mantri Jan Dhan Yojana (2014) and Jan Dhan Aadhaar Mobile (JAM) boost up the inclusion activities beyond the traditional limitations (Kaur & Singh, 2015). Backward areas and female population, who are still relying on unorganized money market mostly, have been targeted by the financial inclusion program by providing them employment opportunity and empowerment. Realizing the requirement of inclusive growth, the Government of our country has given major drive on “inclusive growth” in 11th five-year plan. The report of World Bank confirms that about four-fifths of adults in our country have opened bank accounts by the year 2017 and 36% of account holders are already utilizing their

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Table 2.6 Evolution of financial inclusion initiatives in India Time frame

Highlights

1960s–1970s

. Focusing on the need for lending to the bottom of the pyramid of the society . Nationalization of banks . Initiative and enhancement for the rural banking ecosystem including Regional Rural Banks . Lead Bank Scheme for rural lending . Establishment of National Bank for Agriculture and Rural Development (NABARD) to provide refinance to banks providing credit specifically to agriculture . NABARD launched Self Help Group (SHG) Bank linkage program . Introduction of the term “Financial inclusion” in RBI’s Annual Policy Statement 2005–06 . Launching of “no frills account” . Simplification of Know Your Customer (KYC) norms . Concept of Banking Correspondent (BC) and Banking Facilitator established . 100% financial inclusion drive commenced . Electronic Bank Transfer Scheme introduced . Introduction of Pradhan Mantri Jan Dhan Yojana

1980s–1990s

2000 onwards…

Source Compiled by Researcher

accounts to make or receive digital transactions. Jan Dhan Yojana project contributes a lot for this upliftment (Fig. 2.4). But India till date could not achieve the aim of the expected level of financial inclusion. Beyond the initiatives and programs towards FI drive,

Active Registered Bank Account 2014

Registered Bank Account

2015 2016

Access to Bank Account

2017 0%

20%

40%

60%

80%

100%

Fig. 2.4 The effect of Jan Dhan Yojana in India (Source The financial Inclusion Insights with Bill and Melina Gates Foundation Report, 2017)

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a percentage of the population is still financially excluded. According to NABARD report on financial inclusion, a certain percentage of rural agricultural household rely on non-institutional (informal sources) for their credit need till date (Fig. 2.5). Indian growth process has been gone along with by increasing inter-regional, intra-regional and inter-personal disparity in wealth and income (Ghosh, 2006). Meanwhile, questions have been raised regarding the actual progress of the bank’s financial inclusion drive as merely opening a bank account does not cater to the need (Ramji, 2009; Srinivasan, 2013). In many cases, no-frill accounts have been opened just to fulfill the target of the branch giving no further instruction for account handling or sometime by doing false promise as a form of letting subsidies in future or as payments gateway for the “Mahatma Gandhi National Rural Employment Guarantee Act (NREGA)” (Kochhar, 2009). RBI had insisted the banks to take necessary steps for more substantive financial inclusion (RBI circular dated January 22, 2009). The attributes of Indian economy comprise of high population, availability of profuse workforce, low mortality rate and lack of employment. In this context, the role of group lending model is worth to be mentioned. During 1999 where nationwide the number of banks SHGs linked was 81,780, it gradually grows up to 18,32,323 in 2015–16. In

Fig. 2.5 Distribution of households who took credit from various sources (Source NABARD All India Rural Financial Inclusion Survey 2016–17)

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recent times, Microfinance Institutions Network (MFIN) member organizations composed of 51 leading NBFCMFIs and they are liable for over 90 percent of the nation’s microfinance sector’s business (except SHGs). Active across the country’s length and breadth, the outreach of MFIN member institutions is present in 562 of the 664 districts in India, including 32 States and union territories. All these initiatives help to enhance financial literacy, people will be more aware of the available credit sources, repayment method which leads them to take more effective decision making, etc. Apart from that the skill enhancement programs of financial institutions, betterment reflects in terms of empowerment of females. Empowerment, defined from various dimensions, can create a big difference for the upcoming time. It leads to awareness about the significance of child education, family planning, health and hygiene issues which are the foundation for development (Malhotra & Schuler, 2005). Financial inclusion becomes a precondition behind the economic constancy of society (Bhaskar, 2013). So, to include into organized money market, MFIs work wonderfully in the remote areas where access is a big issue till date. According to the Handbook of Statistics on Indian Economy, published by RBI in September 2015, the level of financial inclusion is high in the southern states of our country. Now considering our state, till the year 2011, 22.52% rural people are lying below the poverty line having monthly income not more than | 783. On the contrary, urban people lying below the poverty line consist of 14.66%. Again, the acceleration of financial inclusion in West Bengal is worth to be mentioned. The state was at 19th position at the end of the fiscal year 2013 as per CRISIL (Credit Rating Information Services of India Limited) Inclusix report, 2015.

2.1.5 Participating Financial Institutions in Financial Inclusion The association between poverty and finance has been communicated by Indian policymakers since 1954 (The RBI report on the All-India Rural Credit Survey 1951–52 (RBI, 1955)) where the Government continued

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Table 2.7 Number of commercial bank branches Year March March March March March March March March March March

Number of branches 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009

149,236 146,470 140,810 131,786 123,001 111,382 103,252 95,014 88,984 83,286

Source Reserve Bank of India, Commercial Bank Branch Statistics, 2017

to highlight the necessity of financial access for the poor, specifically for rural dwellers. Keeping in mind, multiple financial institutions are active in imparting the services of financial inclusion nationwide.

2.1.5.1 Commercial Banks Commercial Banking has grown diverse since the nationalization in1969. They act as the key players in the financial drive of the country. They enhance the interaction between the services of the banking sector with the financially excluded population. Beyond that, they try to inculcate the rural population towards formal credit structure. The expansion of the commercial banks gives an indication of the huge penetration in the length and breadth of our surroundings (Table 2.7).

2.1.5.2 Regional Rural Banks (RRBs) For the duration of the 1970s, the establishment of regional rural banks (RRBs) was taken place for the rural poor. It has been primarily targeted towards rural client base. The foundation of RRBs helps to improve the rural credit history in India. They have successfully executed a larger number of “no frill accounts” in the journey towards financial inclusion. But due to various reasons like political obligations, targeting wrong

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beneficiaries and absence of careful financial practices, RRBs accumulated huge losses (Chakrabarti, 2004). After analyzing the causes of this failure, 34 RRBs were redesigned in the late 1990s resulting in financial turnaround by different committees like Kelkar Committee, 1984; Sardesai Committee, 2005 (Mishra, 2006). But at present, there is still debate going on concerning the best way for RRBs to balance viability and outreach to the rural poor.

2.1.5.3 National Bank for Agriculture and Rural Development (NABARD) It is an apex development bank established in 1982 by the Government of India to ensure credit lending specifically for the advancement of agricultural, cottage and rural sector. It provides long-, mediumand short-term credit to schedule commercial banks, land development banks, regional rural banks and approved financial institutions. Another important attempt for credit lending was the Government sponsored “Integrated Rural Development Program (IRDP)” in 1980. It was one of the world’s biggest microcredit initiatives involving the provision of 56 million loans and supports the rural poor to acquire income-generating assets. But due to lack of technical training, poor linkages with the market, not able to reach the real poor, etc. resulted into high default rate (Dreze & Sen, 1991; Meyer, 2002; Mahajan, 2007). Ultimately, the majority of the loans were written off. Later on, in 1982, NABARD was founded to promote practical rural prosperity all the way through credit and other initiatives. It was built up as an apex establishment for agriculture credit lending and other economic activities in rural regions. Various schemes like Kisan (Farmer’s) Credit Card (KCC) Scheme, self-help group (SHG) bank linkage program (SBLP), etc. were managed by NABARD to speed up the flow of credit to low-income groups.

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2.1.5.4 Post Offices The Indian post office is regarded as having one of the largest networks covering urban, semi-urban and rural India. There are a variety of services accessible to foster the growth of financial inclusion. With the launch of India Post Payment Bank (IPPB), it is able to offer current and savings account facility at 650 post offices and 3250 access points nationwide.

2.1.5.5 Microfinance Institutions A microfinance institution could be a non-government organization (NGO), a credit co-operative or a nonbanking financial company (NBFC). MFIs differ in size, exposure, legal statute, strategy and financial capability. But the common aspire is to motivate monetary activities among the poor and financially excluded people. The microfinance structure is exclusive in nature as it runs on honesty and social collaterals.

2.1.5.6 SHGs Bank Linkage Programme The self-help group-bank linkage model is one of the prominent channels involving commercial banks and self-help group together. It has been regarded as one of the most successful steps towards financial inclusion. Since its launch in 1992, it has become a common vehicle along with microfinance institutions in the financial inclusion movement. There are generally two kinds of SBLP: Bank-SHG members (bank itself performing as self-help group promoting institution) and another one is Bank-NGO-SHG-members (with the help of other facilitating organization banks promote SHG movement).

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2.1.6 Policy Initiatives for Financial Inclusion 2.1.6.1 Pradhan Mantri Jan Dhan Yojana (PMJDY) and Jan Dhan, Aadhaar, and Mobile Phone (JAM) In this connection, the role of Pradhan Mantri Jan Dhan Yojana (PMJDY) is worth to be mentioned. With the introduction of PMJDY in 2014, the feminine section of the society got a big boost towards formal financial and credit sector. The number of Basic Savings Bank Deposit Account (BSBD) being the basic savings account product rose to 51.50 crores as on December 2016 of which 26.20 crore accounts were under PMJDY. Financial inclusion revolves always around the gender issue. As of March 2017, 14.49 crore accounts opened by women under PMJDY, out of a total of 43.65 crore women’s accounts. Along with that amount of deposit and the number of zero balance account under PMJDY has also got changed over time (Fig. 2.6). The most significant change that will provide the backbone for financial access is the implementation of the JAM trinity (Jan Dhan, Aadhaar and mobile phone) positioned itself as the identity of an Indian. The coverage of 1,020 million people and act as a base for other financial

Fig. 2.6 Average deposit accounts opened under PMJDY scheme (Source Economic Survey Report 2016–17)

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Fig. 2.7 The outreach of Aadhaar and Jan Dhan Yojana (Source Economic Survey, 2016–17)

services JAM has been treated as a useful tool for assessing financial inclusion (Mishra, 2016). Its potential has been realized through the opening of Jan Dhan Accounts, adoption of Know Your Customer (KYC) by MFIs, linking details to the cooking gas connection and also the recent move by few MFIs to use biometric-based authentication of Aadhaar (Fig. 2.7).

2.1.6.2 No-Frill Accounts This has been specially designed for the financially included population and to make them enable towards accessing saving accounts. This initiative includes the introduction of zero balance accounts in the banks so that anyone can avail banking service initially free of cost. In 2012, as per RBI guidelines, no-frill accounts reformed as basic savings bank deposit accounts (BSBDAs) with multiple facilities like debit card, cheque book, internet banking, overdraft limits, etc. at nominal charges.

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2.1.6.3 General Purpose Credit Cards (GCC) Reserve Bank of India in 2005 has introduced General Purpose Credit Cards (GCC) via banks to offer credit up to | 25,000 without any collateral for semi-urban and rural residents as per their income level and requirement. The major objective is to motivate entrepreneurship among the population for betterment.

2.1.6.4 Business Correspondents (BC)/Business Facilitators (BFs) This structure is based on information and communication technology (ICT). BC/BFs are technologically empowered by the banks under the guidelines of RBI to provide the delivery of financial products or services. They act as a link between the banks and the service seekers and are considered as a practical solution to extend basic banking services in the underprivileged areas.

2.1.6.5 Technology-Based Approaches Technologies like credit and debit cards, automatic teller machines (ATMs), telephone and Internet banking and biometric point of transaction (POT) terminals have been vital to impart financial services. They enable remote access to financial services and enhance security for associated transactions. This has extended and accelerated the financial inclusion drive.

2.1.7 Committee Recommendations for Financial Inclusion 2.1.7.1 A C Shah Committee The A C Shah Committee formed for NBFCs and recommended that General Insurance Corporation (GIC) and Deposit Insurance and Credit Guarantee Corporation (DICGC) provide the risk cover. The Dr Shah

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Committee was formed by the ALFS and ELA under the chairmanship of Dr A C Shah, former chairman, Bank of Baroda. With a view to regain the confidence of the small investor, the committee has recommended that only deposits upto | 20,000 to | 30,000 be provided insurance. Moreover, the facility would be given to register NBFCs on the basis of their compliance with prudential norms and their credit rating.

2.1.7.2 Ghosh Committee This high-level committee formed under the chairmanship of Shri. A. Ghosh, Deputy Governor of RBI. The objective of this committee is to prevent frauds and malpractices in banks. It has detail recommendations on internal inspection and audit. The Reserve Bank of India had constituted this Committee, to enquire into the various aspects of internal audit machinery, periodicity, coverage, revenue audit, credit portfolio audit, compliance with the norms, etc.

2.1.7.3 B. Sivaraman Committee The Committee was established on 30 March 1979, under the Chairmanship of Shri B. Sivaraman, former member of Planning Commission, Government of India. The basic objective of this committee was to look after the set up for institutional credit for agriculture and rural development. On the basis of the recommendation of this committee, the formation of NABARD was approved through Act 61 of 1981.

2.1.7.4 Narasimham Committee This committee was formed under former RBI Governor M. Narasimham in August 1991. The basic objective of this set up was to look after different aspects of financial system like Statutory Liquidity Ratio (SLR) and Cash Reserve Ratio (CRR), deregulation of interest rates, redefining the priority sector, etc.

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2.1.7.5 Malhotra Committee It was set up in 1993 under the chairmanship of R.N. Malhotra, former Governor of the Reserve Bank of India, to introduce the concept of “professionalization” in the insurance sector to make a strong base for the foundation for foreign capital. On the basis of committee recommendation establishment of the Insurance Regulatory and Development Authority (IRDA) has taken place.

2.1.7.6 RV. Gupta Committee In 1997, RBI established a one-man committee of Shri. R.V. Gupta, Deputy Governor to suggest measures for the elimination of the constraints faced by the Commercial Banks in increasing credit flow to agriculture. The few major recommendation of this committee was simplification of procedure, delegation of power to the branch manager, discouraging additional collateral, separate team for loan recovery, etc.

2.1.7.7 Usha Thorat Panel RBI has established a panel under the former Deputy Governor, Usha Thorat, to look after policy measures for financial inclusion. This panel studies the reasons behind offshore rupee market, recommends measure to incentive generation for non-residents to assess the domestic market, etc.

2.1.7.8 Rangarajan Committee In 2006, a committee has been shaped under the chairmanship of former Governor of RBI, C. Rangarajan, for strategy designing and suggestion towards financial inclusion in the nation. According to this, a nationallevel plan has been recommended for financial inclusion with a detailed study. Moreover, this committee suggested setting up Financial Inclusion

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Promotion and Development Fund and the Financial Inclusion Technology fund for financial inclusion and considering the potential role of the SBLP as well as MFIs with appropriate regulation.

2.1.7.9 Deepak Mohanty Committee It is a 14-member committee and has been established by RBI in July, 2015 under the headship of Deepak Mohanty, Executive Director. This committee examines the current policy related to financial inclusion and also recommends plan regarding savings, deposits, pension, insurance, etc.

2.1.8 Financial Inclusion in Different Countries 2.1.8.1 Introduction Financial inclusion is a key element towards positive changes in the economy. Today, financial inclusion is very much in public policy. World Bank from the very beginning has taken initiatives to continue the movement of financial inclusion globally. It always plays a critical role to impart financial awareness, support to SMEs and agriculture, involving technology in the financial inclusion process and so on or simply it has been linked to the financial well-being of individuals as well as to the economic growth and stability of nations (Demirgüç-Kunt & Levine, 2008). Some of the different actions taken by World Bank towards FI are Identity for Development Initiative (ID4D), The Women Entrepreneurs Finance Initiative (We-Fi), the Digital Economy for Africa (DE4A), Universal Financial Access (UFA), Financial Sector Assessment Programmes (FSAPs) and so on. Post MDGs or SDGs, introspection is being done to understand the trends of financial inclusion worldwide especially with the backward countries. So UFA 2020 has been considered for updates of FI status among the targeted countries.

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2.1.8.2 UFA 2020: The World Bank Initiative The UFA 2020 initiative idealizes about a phenomenon where irrespective of both adults’ men and women worldwide will be able to have access to a formal set up with transaction account or an electronic instrument to store money, payments and receives deposits as a basic structure to look after their financial lives. This program has been initiated in 2013 with a target of financial access to 1 billion adults worldwide. This phenomenon targets 25 countries with approximately 70% financially excluded residents.

2.1.8.3 Target Countries and FI Movement The gradual progress of target countries differs in terms of location, socio-economic profile, and demographic set up of the residents, the participating financial institutions, and their business structure and so on. There is a wide range of parameters to analyze the current status and the so-called progress in terms of financial inclusion. But here we consider few one to have a glimpse on the current scenario. The different parameters considered here are: . Total adults Vs unbanked adults: Here total adults denote the number of adults (15+) resides in the specified country and unbanked adults denote the number of million f adults (15+) who report not possessing an account (by themselves or with someone else) at any financial institutions or personally using a mobile money service in the past 12 months. . Percentage of adult having own transact account: Here transact account resembles any accounts held with banks or with any authorized or regulated service providers and can be used as deposit transaction account or e-money accounts for saving and payments. . Percentage of adults transact electronically: The number of adults (15+) who used electronic medium inclusive of ATMs, mobile money, wallet money, etc.

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. Percentage of female own a transact account: Number of females who possess an account at a bank or in any kind of financial institutions or personally using mobile money services in the past 12 months. . Percentage of male own a transact account: Number of males who possess an account at a bank or in any kind of financial institutions or personally using mobile money services in the past 12 months. The detailed progress of every country has been discussed thereafter.

Bangladesh To start with one of the leading countries in the map of financial inclusion and microfinance, Bangladesh witnessed a lot of changes in due course of time. As per World Bank data (2017), there are total 111.8 million adults reside in this country. Among them, 77.1 million adults are unbanked. With the UFA vision 2020, the Percentage of total adults having a transaction account has been increased from 40% (2011) to 50% (2017). Among the account holders, huge progress can be observed in terms of electronic transaction from 2011 (5%) to 2017 (34%). Most interestingly, the Percentage of female population having own account is not comparatively high (35%, 2011 to 36%, 2017) than its male counterpart (44%, 2011 to 65%, 2017). So, more improvement can be observed in case of male account holders than female from 2011 to 2017. The reasons are likely to be the aggressive role of government with the utmost focus on financial inclusion for rural belt. Also access to credit enhances women empowerment which results in autonomy and decision-making ability in the periphery of household (Schuler & Hashemi, 1998). But as the credit amount lent by the females are mostly utilized by others or head of the family so women became the channel of economic flow to the family enterprise (Goetz & Gupta, 1996). Bangladesh has greater microfinance networks so more penetration of active account holders will ensure better financial inclusion of the country in the future.

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Brazil This country belongs to Latin America and included in the UFA 2020 initiative. The total adults are 154.3 million with 49.2 million unbanked one. During the course of time from 2011 to 2017, the Percentage of adult that owns a transaction account increase from 56 to 70%. A positive trend can be observed in the Percentage of electronic transaction from 2011 (47%) to 2017 (58%). The Percentage of female adult having a transact account increase from 51% (2011) to 68% (2017) whereas the Percentage of male increase from 61% (2011) to 73% (2017). Brazil is one of the most populous countries in South America and contributes a decent percentage of GDP. This nation comes up with new industrializations and start-ups so this country has a huge scope for further advancement in financial inclusion drive.

China Being one of the fastest-growing economies, China has also witnessed changes in the financial inclusion journey. The total adults as per 2017 World Bank data is 1141.5 million with 240.6 million unbanked adults. The Percentages of adult that own a transaction account increase a comparatively huge leap from 64 to 80% from 2011 to 2017. Also, a positive trend can be observed in the Percentage of electronic transaction from 2011 (43%) to 2017 (68%). The changes of female Percentage (60–76%) that own a transaction account along with male (68–84%) took place at similar pace from 2011 to 2017. The progress of financial inclusion can be visible in China from 2005 onwards with the help of access to financial services, financial viability, diversified financial offerings, industrial standards and effective management, etc. (Peng et al., 2014). Moreover, the Chinese Government in their 2016–2020 policy (State Council Plan for Promoting the development of Financial Inclusion) aggressively encourages digital platform to introduce financial inclusion journey. This phenomenon has been termed as Fintech revolution.

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Colombia Colombia is a country where the proportion of unbanked adults (21.7 million) with comparison to total number of adults (35.6 million) is quite higher according to World Bank Data, 2017. The Percentage of adults that own a transact account increase from 30% (2011) to 46% (2017). In 2011, 27% adults transact electronically whereas, in 2017, a total of 37% adults engage in electronic transactions. The proportion of female Percentage who owns her active account increases from 25% (2011) to 42% (2017). On the other side, the total Percentage of male increases from 36% (2011) to 49% (2017). Among the several measures taken, lowering constraints on collateral promises, lowering the financial participation cost, spreading formal banking system, digital payment system (Karpowicz, 2014), Conditional Cash Transfer Programme (CCT) (Maldonado & Tejerina, 2010), etc. play a vital role for the development of financial inclusion in Colombia.

Cote d’Ivoire As a country of sub-Saharan Africa, Cote d’Ivoire caters 8 million unbanked adults (2017) out of a total population of 12.2 million (2017). The Percentage of adults who own his/her transaction account is 41% as of 2017 World Bank data. The total Percentage of adults who practice electronic transaction is 38% in 2017. The proportion of male (47%) who own active account is comparatively higher than the Percentage of female (36%) as of the year 2017. The outreach and progress of microfinance institutions are at high pace in the sub-Saharan countries (Lafourcade et al., 2005). But in terms of formal financing, most of the individual and institutional set up still rely on informal sources due to its social structure, economic system, poor awareness level, illiteracy, lack of financial institutions management, etc. (Demirguc-Kunt & Klapper, 2012).

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DRC This country consists of a total of 17.5 million unbanked adults (2014) out of total 37.1 million. The Percentage of active account holder rises from 9% (2011) to 17.1% (2014) and 14.3% (2014) adults use digital platforms for transactions. The transition of female account holders is from 6.8% (2011) to 15% (2014) whereas male account holders’ changers from 11.3% (2011) to 19.2% (2014).

Egypt Egypt showcases a comparatively higher number of unbanked adults (49.4 million) relating to its total population (57.5 million) as of 2017. The progress of active account holders can be observed from 10% (2011) to 33% (2017). The changes in the electronic transaction can also be seen from 7% (2011) to 23% (2017). The changes in Percentage of female active account holders are 7% (2011) to 27% (2017) whereas the changes in male active account holders are 13% (2011) to 39% (2017), respectively. The progress of financial inclusion especially for MENA region (The Middle East and North Africa region) depends on positive attitude of Government, supportive regulatory practices, digitalization and the microfinancial companies (Pearce, 2011).

Ethiopia The total unbanked adults of Ethiopia are 43.7 million out of total of 55.9 million. Among them, only 35% (2017) hold his/her accounts. In terms of electronic transaction, only 12% of adults are using electronic transaction which is nominal in this time of digitalization. The male Percentage having his own active account is comparatively higher (49%) than female counterpart (29%) as of 2017 data. The advancement of financial inclusion in Ethiopia is comparatively low. The reasons can be marked behind this are lack of access towards offerings, conservative lending policy, low coverage of financial services, etc. (Zwedu, 2014).

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India India is a home for approximately 47% of total unbanked adults (423.2 million) out of the total adult population (903.1 million) as of 2017 world bank data. The progress of account holders are quite impressive from 2011 (35 Percent) to 2017 (80 Percent) in this country. The progress of electronic transaction can be observed as double in due course of time from 13% (2011) to 29% (2017). The Percentage of female active account holders is having a high proportion from 26% (2011) to 77% (2017). On the contrary, the advancement of active male account holders is from 44% (2011) to 83% (2017). India is witnessing gradual progress in the field of FI. Among the various initiatives taken, the role of Government, RBI, banking policy, digital India movement, aggressive role of financial institutions, role of business correspondents (BC), financial literacy programs, SHG movement, etc. is few to mention in this context (Singh et al., 2014).

Indonesia Indonesia composes of 115.7 million unbanked adults out of 180.9 million (2017). In 2011, there were only 20% of adults having their own accounts which rose up to 49% in 2017. The Percentage of electronic transaction holders’ changes from 12% (2011) to 35% (2017). The Percentage of female account holders are higher (51%, 2017) than male (46%, 2017). Indonesia is one of the leading countries in microfinance activities but the attitude of commercial banks towards small and medium enterprises somehow degrades the progress of financial inclusion (Rosengard & Prasetyantoko, 2011). Progressive regulatory policy is needed for the betterment of the situation.

Kenya The situation of Kenya is comparatively better with 6.7 million unbanked adults out of a total of 26.4 million (2017). Almost 82% (2017) of adults possess their own accounts. The Percentage of electronic

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transaction is also quite better (79%, 2017). The progress of female account holders is noted as 39% (2011) to 78% (2017) and in the case of male, it is 46% (2011) to 86% (2017). Kenya is a progressive country in terms of financial inclusion with its mobile money transaction system, financial education system and so on (Hannig & Jansen, 2010). Financial inclusion initiatives targeted at small entrepreneurs also influence the progress of financial inclusion in this country (Kalunda, 2014).

Mexico Mexico is composed of 54.3 million unbanked adults out of 89.2 million (2017). Among them, 37% (2017) hold their own active accounts, and a higher Percentage (32% in 2017) engage in the electronic mode for transactions. The progress of female account holders is comparatively better (22%, 2011 to 33%, 2017) than male (33%, 2011 to 41%, 2017). The different models of offering financial services, financial literacy, development of private sectors, etc. influence the degree of financial inclusion in countries including Mexico (Chibba, 2009).

Morocco In Morocco, 39.1% (2011) of adults are having their own accounts. Out of them, 27.3% (2011) use digital platforms for transactions. The Percentage of female account holders is 26.7% (2011) and 52% (2011) male possess their own accounts. Certain initiatives like supportive regulatory policies, supervision, removal of interest rate caps on microloans, mobile technology, etc. can add up to the financial inclusion drive of the country (Pearce, 2011).

Mozambique A total of 39.9 Percent (2011) adults are having their own accounts whereas 39.5 Percent (2011) use an electronic gateway for transactions. The Percentage of female active account holders is 35.5% (2011) and the

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male Percentage is 45% (2011). The ICT (Information, Communication and Technology) contributes a lot to the extent of financial inclusion in various countries including Mozambique (Kpodar & Andriannaivo, 2011).

Myanmar Myanmar is the home of almost 77% of unbanked adults (31.3 million out of 40.5 million). Only 26% of adults are having their own accounts and Percentage of adults using digital platforms for transactions are 8% as of 2017 World Bank data. Both the Percentage of male and female active account holders are 26% (2017). There are numerous reasons for the poor status of Myanmar’s financial inclusion. Some of them are the country’s economy, lack of banking reform policies, agricultural finance, weak financial regulations, high inflation rates, etc. (IMF Country Report, 2021).

Nigeria Nigeria is having 55.1 million unbanked adults out of total 99.3 million as 2017 report. The total Percentage of active account holders is 40% (2017) though the progress of electronic transactions among the adults is nominal (26%, 2011 to 30%, 2017). The female active account holders change from 26% (2011) to 27% (2017) whereas the male active account holders change from 33% (2011) to 51% (2017). Introduction of cashless economy, financial awareness, consumer value proposition, infrastructure, etc. have significant impact on financial inclusion advancement (Bayero, 2015). But financial crisis due to oil resulted in economic demotion which eventually affects the financial inclusion adversely (Adeola & Evans, 2017).

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Pakistan Pakistan composed of 107.4 million unbanked adults out of 123.5 million. The changes in terms of account holding are seen from 10% (2011) to 21% (2017). The Percentage of electronic transaction holders are only 18% (2017). A huge gap can be observed between female and male account holders (Female-7%; Male-35%) as of 2017. Religion and cultural barriers play a major role in the case of female mobility. Moreover, poor health, illiteracy, less wealth, decision-making inability of the feminine section of the society influences the scenario to date (Ashe et al., 2011).

Peru Peru consists of 15.7 million unbanked adults with a total of 22 million (2017). In 2017, only 29% adults are having their active accounts and 29% engage in electronic transactions. In 2011, female active account holders are 18% (2011) which increased up to 22% (2017) and in case of male, the number changes from 23% (2011) to 36% (2017). In case of Peru, the penetration of financial inclusion movement is comparatively less among households due to regional differences, socio-economic structure of the populations, etc. (Izquierdo & Tuesta, 2015).

Philippines Philippines is the home for 45.5 million unbanked adults with total of 66.3 million (2017). The Percentage of adults having his/her own account changed from 27% (2011) to 31% (2017). Total 27% (2014) of adults use digital platforms for transactions. The Percentage of female active account holders increased from 34% (2011) to 39% (2017) wherein the case of male the Percentage improved from 19% (2011) to 30% (2017). In this country, there is low access to formal financial institutions, micro setups also suffer from limited access to formal credit though after the mandatory law (provision of 8% of bank loan portfolio for MSME) things are improving gradually (Hannig & Jansen, 2010).

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Rwanda Rwanda is having more than 50% of unbanked adults (4.1 million out of 7 million) as of 2017 data. A total of 50% (2017) of adults are having their own transact accounts and only 39% (2017) of them use digital platform for transactions. The gradual progress of female account holders is 28% (2011) and 45% (2017), respectively, whereas in case of male it is 38% (2011) and 56% (2017). Unlike other African countries, Rwanda has high poverty, malnutrition and mortality rates, which hamper the economic condition of the society and the level of financial inclusion as well (Alter, 2015).

South Africa A country with an average of upper-middle income, South Africa is having 11.1 million unbanked adults out of 37.5 million. The Percentage of own account holders are 69% (2017) and out of them, 60% (2017) access the electronic gateway for transactions. The Percentage of female account holders are comparatively more (70% as of 2017) than its male counterparts (68% as of 2017). The advancement of South Africa is influenced by certain factors like policy for financial inclusion, monetary policy, cross-border banking, etc. (Beck et al., 2014).

Vietnam Vietnam composes of 49.5 million unbanked adults with a total population of 71.7 million. In 2011, 21% adults had own their own transact accounts which increased in 2017 to 31%. The total electronic transaction participants are 23% in 2017. The female active account holders are 30% (2017) from 19% (2011), whereas male active account holders are 31% (2017) from 24% (2011). The financial progress of Vietnam is hugely influenced by the political instability, transit economy, cultural barrier, geographical locations, etc. (Tsang et al., 2004).

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Tanzania Tanzania is mostly composed of low-income group country with 16.9 million unbanked adults out of 28 million. In 2011, 17% adults owned their own transact accounts whereas in 2017, the Percentage increased to 47%. Electronic transaction gradually gains acceptance and 43% (2017) adults participate in this process. The Percentage of female account holders changed from 14% (2011) to 42% (2017) and male account holders changed from 21% (2011) to 52% (2017). Mobile banking acts as one of the major influences in terms of spreading financial inclusion movement in African countries including Tanzania (De Koker & Jentzsch, 2013).

Turkey Turkey is possessing 24.5 million unbanked adults out of 56.6 million as of 2017 World Bank data. 69% (2017) adults are having their own accounts out of which 64% (2017) use digital platform for transactions. The advancement of female account holders is better from 33% (2011) to 54% (2017) than male from 82% (2011) to 83% (2017). The role of participation banks (PBs) is worth to be mentioned for the outreach and progress of financial inclusion in Turkey (Aysan et al., 2013). Due to religious sensitivity, conventional banks are not gaining access to the financially excluded population but PBs with its governance and flexible structure are able to win the trust of the people.

Zambia Zambia is another sub-Saharan country which has 5.2 million unbanked adults out of a total 8 million adults. In 2011, 21% adults had their own accounts which increased in 2017 to 46%. In terms of digital transaction, the Percentage changes from 17% (2011) to 39% (2017). The proportion of male active account holders are greater (52% in 2017) than the females (40% in 2017). Mobile financial services (both mobile savings and mobile banking) play vital roles in certain African countries. It helps

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to promote savings, access to formal financial services especially in the poor and low-income groups (Ouma et al., 2017).

2.1.8.4 Comparative Study Between Developed Countries and Targeting Countries Financial inclusion is a drive towards sustainable positive advancement. It not only improves economic conditions but also held responsible for the social betterment of the population. Globally, 69% of adults are having their own accounts (The Global Findex Database, 2017); it means a lot of people are still left with the options of financial exclusion. In highincome economies, 94% adults access their own accounts which means they practice the saving behavior at safe places and open the avenues for further involvement into organized money market. Also with the introduction of mobile money, many backward countries in Africa are able to enhance the saving behavior along with hassle-free transactions, overseas money receive or transfer to relatives or family, etc. of the financially excluded especially among the female populations. If we compare the gender gap in relations to account holding pattern, the scenario from 2011 onwards, the developed economies after 2014 almost erase out the gaps but in case of developing economy, the gap still exists worldwide (Global Findex Database, 2017). The reasons are commonly marked as low educational qualifications, unemployment, distance, lack of financial awareness, lack of documentation, religion barriers (in case of Islamic countries), etc. Saving behavior is one of the key indications of financial inclusion. In developed countries almost 71% adults engage in savings, whereas in developing countries the Percentage is almost half (43%) according to World Bank Data. This is due to saving behavior pattern of the developing or backward economies because people rely on semiformal methods for savings like cash at home, saving club, saving in assets, etc. The saving behavior also deviates with gender and income across the developed and targeted countries. There are a lot of initiatives that need to convey financial inclusion movement both in developed, developing and backward economies.

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Digitalization can play a vital role in it as dependency on technology is getting at a higher pace in every corner of the globe. Moreover, it ensures convenience, speed and security at the same pace. Also high-speed internet and advanced mobile technology boost up the process as well. Beyond technological tools, traditional ways like awareness programs, more outreach of the financial institutions, mobility, visibility, constant supervision and positive regulatory policy also add up to the financial inclusion flow to the economies.

2.1.9 Literature on the Role of Financial Institutions in Inclusion The basic question comes into mind while reviewing any literature is that what should be the primary foundation or concept that needs to act as the starting point for a systematic and thematic understanding of the previous literature. Now, most of the economies suffer from the issue of poverty. It is also evident that there are various negative consequences of poverty (Deaton & Dreze, 2002; Satterthwaite, 1995). So, to fight out this basic problem lot of tools, policies and techniques have been designed and implemented from time to time. Among them, one of such movement is called financial inclusion. In this study, the primary base is focusing on this most influential and powerful tool for betterment. The journey starts with the motives behind financial inclusion. Poverty plays a key role in initiating the task of development as well as establishes the need for imparting financial inclusion programs in the surroundings. There are a good number of literatures that maintained the fact that poverty and development have a linkage within themselves (Ahluwalia, 1976). In his paper, Ahluwalua (1976) observes that income inequality improves the need for development. In his work, he does a cross-country analysis engaging 60 countries, 40 developing countries, 14 developed countries and 6 socialist countries. He observes that with the betterment of income inequality, there occur inter-sectoral changes in the production structure, attainment of education and labor’s skill level and reduction in the population growth. These changes reflect some kind of improvement in income distribution and poverty in the later stage. According to Park

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and Mercado (2015), poverty and income inequality remain an inflexible challenge in Asia. They design financial inclusion pointer by engaging five elements: number of ATMs, commercial bank branches, number of borrowers from commercial banks, depositors with commercial banks per thousand adults and domestic credit to GDP ratio to assess various macroeconomic and nation-specific factors that affect the financial inclusion level for selected 37 budding Asian economies. Applying regression on secondary data from World Development Indicators, Global Financial Database and World Governance Indicators of the World Bank, they have found that, regulation of law, per capita income and demographic features significantly influence financial inclusion in developing Asia. In this context, higher age dependency ratio reduces the intensity of financial inclusion. They have also established that financial inclusion drastically reduces poverty and inequality of income and suggests provisions for old-age and young inhabitants and the more powerful rule of law, with the enforcement of fiscal contracts and financial regulatory oversight, will expand the scale of financial inclusion. In line with that Chibba (2009) states that traditional mode towards handling poverty and other Millennium Development Goals (MDGs) are needed but are not satisfactory enough to address the condition. Financial Inclusion (FI) proposes incremental and corresponding solutions to undertake poverty, to encourage inclusive advancement and to deal with the MDGs. Financial inclusion is an all-encompassing development and public relation (PR) strategy which manifests itself as part of the promising FI-PR-MDG (Financial inclusion-Public RelationMillennium Development Goals) nexus. In the paper, he proposed tackling four key supports: private (monetary and non-monetary) sector development, microfinance and public sector support, financial literacy to reinforce the FI-PR-MDG nexus for sustainable development. To further support these four pillars, FI explanatory models have been incorporated which are formal financial sector consensus, public sector leadership, development of the private sector, civil society/NGOs and the catalytic model. Further, Allen et al. (2014) propose a detailed study of financial developments and financial inclusion gaps. He studies Africa as his sample area. In his work, he compares the financial development and gaps in financial inclusion in Africa and compares it with other countries

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using the same parameter. This study expresses the thought that population density is one of the most significant reasons behind the betterment of any country. Moreover, other factors like financial services, mobile banking, etc. also helped to overcome the developmental issues along with financial improvement. Financial institutions work largely to impart financial inclusiveness in the society. The public sector bank is no exception to that. In India, Pradhan Mantri Jan Dhan Yojana (PMJDY) has an inordinate impact in the inclusion journey. By applying DEA analysis, Maity and Sahu (2020) measure the efficiency of public sector banks towards financial inclusion covering pre-post PMJDY scheme in India. They find that during postphase of PMJDY, overall average efficiency towards financial inclusion increases significantly. The intervention of financial institutions causes significant contribution into the well-being of the society as well as financial inclusion. A study by Babajide et al. (2020) explore this interesting fact by comparing two states, i.e., Lagos and Ekiti of Nigeria. They have engaged survey and logit regression and find remarkable differences in the financial inclusion penetration in two sample areas. The different parameters associated with banking services have a direct linkage with the level of financial inclusion. Moreover, Hannig and Jansen (2010) discuss the financial crisis worldwide and showed the fact that financial inclusion can bring financial stability to the economy. By considering secondary data on specific financial inclusion variable from World Bank data, they come up with some interesting insights like evidence recommends that low-income savers and creditors tend to maintain firm financial behavior all the way through financial crises, keeping deposits in a protected place and paying back their credits. Along with that improved customer service and diversified financial system help to minimize the risks of financial institutions and thus bring financial stability. This paper shows that inculcation of savings behavior indulges important outcomes like crisis management of the household; accelerates better lifestyle, growth and poverty reduction. All these elements bring stability in terms of the financial situation of any economy. Further, according to Lederle (2009), there is a link between advanced financial inclusion and the extensive dynamic process of social inclusion. He considers qualitative data collected by

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semi-structured interviews with open-ended answers along with group discussions, one-to-one interview, etc. There are twofold results: firstly, the paper analyzes respondents past experience of financial exclusion and related issues. Secondly, it analyzes the changes that were perceived in individuals’ life after financial inclusion and how it changes things for them. The longitudinal approach of this research enabled to explore the persistence of the various factors as the indicator of financial exclusion. In order to identify the supporting element towards financial inclusion, Atkinson and Messy (2013) focus on the necessity of financial education to help the individual to be financially inclusive. This paper sheds lights on the issue that poor levels of financial inclusion are allied with lower levels of financial literacy in G20 member countries. So, policymakers design financial education tactics and consumer protection measures to stimulate financial inclusion. Now after comprehending the requirement of financial inclusion, it is very much needed to measure the level of it for further policy formulation (Chakravarty & Pal, 2013; Gupte et al., 2012; Sarma & Pais, 2008). In this circumstance, Sarma and Pais (2008) observe a crosscountry analysis towards tracking the rapport between financial inclusion and development. Using the Index of Financial inclusion (IFI) along with Human Development Index (HDI), they have found the factors related to financial inclusion. They have collected data from 49 countries to measure financial inclusion and development due to it. Among socio-economic factors, besides income inequality, literacy and urbanization are positively correlated with the degree of financial inclusion. Moreover, physical infrastructure for the usage of connectivity and information are two developmental elements that are also related to financial inclusion. Further, NPA and CAR (banking sector), government or foreign ownership bank, interest rates are all not significantly relayed to financial inclusion. Supporting this, Chakravarty and Pal (2010) also observe the degree of financial inclusion by engaging both cross-country and national-level data. They have followed the axiomatic approach in their paper for measuring the level of FI. This measurement enables to recognize the dimensions of inclusion which are more/less vulnerable to inclusion and hence it is helpful from a policy standpoint. In the context

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of cross-country analysis, variables such as geographic branch penetration, demographic branch penetration, geographic and demographic ATM penetration, credit accounts and deposit accounts per capita have been considered covering 21 countries. By applying principal component analysis, a wide variation in financial inclusion has been observed country-wise. This is due to the presence of more similar income group as it leads to less financial inclusion. Further, in case of financial inclusion index, three variables—the number of deposit accounts per capita, demographic penetration of bank branches and the ratio of the size of deposit—plus credit to GDP have been considered. In this case, the standard deviation of the percentage contribution of the attributes increased along with the decrease in overall achievement. Banking services data of 1991, 2001 and 2007 have been incorporated in this study to comprehend national level scenario. It involves variables which are demographic penetration (defined as the number of bank branches per 1 million people), geographic penetration (defined as the number of bank branches per 1000 square- kilometer land area), number of deposit accounts per 1000 people, number of credit accounts per 1000 people, depositsincome ratio and credit-income ratio. They use data on the selected features for 24 states and it has been found that all these variables are positively correlated and significant and the scale of financial inclusion varies abruptly. Financial inclusion proposals focus on the efforts undertaken by the financial system or any component to bring into the specific sections of the economy that have been prohibited from access to reasonable credit and other financial services. So, it is obvious to know the intensity of financial inclusion for policymaking. For measuring the FI, Gupte et al. (2012) observe the determinants to compute the extent of FI and focuses on the computation of an index that would systematically confine the impact of multi-dimensional variables from CGAP of World Bank data covering two years referring India. In this paper, they have identified all the previous studies and the dimensions which are present in one study but absent in another. They have collected all the variables and measure the FI index so that the measurement should be more indicative. In order to calculate the behavior and determinants of financial inclusion in our country, Kumar (2013) uses state-wise panel data from 1995 to 2008

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for analysis. Here he uses two dependent variables i.e. number of deposit accounts per thousand of population and number of credit accounts per thousand of the population to measure financial inclusion. The various explanatory variables are population density, average population per bank branch, Income, credit deposit ratio and employment status. By applying panel data analysis and regression, it has been observed that both positive and negative impact has been found in relation to different variables. Population density has a negative impact on deposit penetration. It is due to a mismatch between growth rate and population increase. But, in case of credit penetration, the linkage is not as clear. Moreover, the average people per branch is having a negative pressure on deposit penetration which leads to the beneficial impact of betterment of branch network on financial inclusion drive, which takes place due to superior convenience and accessibility. Economic condition is a fundamental determinant of financial inclusion efforts here as the income level is having a positive outcome on penetration proportions. The outcome teams up the incidence of higher usage and requirement for financial services with improvements in the standard of living. Both the number of factories and employees to inhabitants are having a noteworthy and positive influence on deposit penetration. It entails that the region’s structural and environmental setup has a role in determining the deposit penetration. An optimistic coefficient for the employee percentage indicates that employed persons seem to be more aware, active, interested with regard to banking activities related to both credit and deposit activities. Using test for convergence, it is observed that the states be likely to keep their respective level of banking actions vis-à-vis the rest. This has an important implication for the regions performing low in terms of financial inclusion. It seems that due to definite inherent structural characteristics, low performing states are unable to close the gap. Further, a lot of literature also develop a different index for measuring the extent of financial inclusion in certain regions (Bagli & Dutta, 2012; Camara & Tuesta, 2014; Chattopadhayay, 2011; Mialou et al., 2017). In the paper of Bagli and Dutta (2012), state-wise financial inclusion assessment has been taken place. By applying rotated principal component analysis, RBI and Economic Survey data have been analyzed with

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selective ten indicators in connection with financial inclusion. Moreover, to examine the degree of association between financial inclusion and human development of the states, Pearson’s correlation coefficient has been applied to the Human Development Index (HDI). Due to unavailability of data, while calculating the value of HDI in case of north-eastern states of India, Assam has been excluded. To study the nature of financial inclusion of the states, secondary cross-section data for the year 2009 from RBI and Economy Survey data of 2010–11, Census report 2011 and data of SHGs for status of microfinance 2009–10 of NABARD have been considered. This study reveals a composite index of financial inclusion for an individual state. The result denotes that the level of financial inclusion with reference to each state is not satisfactory. Among all the states, Goa occupies the top position in terms of FI. It has been observed that the marginalized sections are basically deprived of the outreach of financial inclusion. So, financial literacy and awareness creation among them is the need of the hour to reach the target level of FI. Further, Amidzic et al. (2014) in their study also propose a new composite index of financial inclusion. The variables used for the computation of the index are the number of ATMs and branches of Other Depository Corporations (ODCs) per 1,000 square kilometers, the total number of resident household depositors with ODCs per 1,000 adults and the total number of resident household borrowers with ODCs per 1,000 adults. This index uses factor analysis to find the level of financial inclusion and accordingly ranking of countries in terms of inclusion are prepared. In his paper using this composite index, three countries namely Maldives, Thailand and Brunei Darussalam occupy the highest position in terms of financial inclusion. In order to measure the degree of financial inclusion, Camara and Tuesta (2014) rely on both supply- and demand-side factors and develop a composite index to check the degree of financial inclusion among eighty-two (82) countries worldwide. They have measured financial inclusion from three dimensions namely usage, difficulties and way into financial inclusion and discovered that on one hand maximization of usage and access to formal financial services and minimization of obstacles on the other hand, are causing involuntary exclusion. Demand-side information to consider the usage and barriers

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measurements is the key to shaping the extent of financial inclusion. According to the work of Chattopadhayay (2011), financial inclusion needs a long way to go despite banking outreach in West Bengal. He develops a financial inclusion index depending on data of three dimensions of financial inclusion. This study observes area-wise imbalances of financial inclusion in West Bengal. He emphasizes on both demand- and supply-side improvement for better financial inclusion in the state. There are numerous financial institutions which work actively for attaining financial inclusion countrywide. In their analytical study about the relevance of financial inclusion especially for the developing nation by Sarma and Kukreja (2013) conclude that only opening no-frill accounts never guarantee financial inclusion. It is the liability of the financial institutions to earn the trust of the poor and help them to be financially included. This study has been backed by secondary data collected from different sources. India is in the phase of sustainable growth. The average income of both urban and rural population and economic activities has been increased than before. This phenomenon demanded the need for financial services (Gomathy, 2015; Mohan, 2006). According to Mohan (2006) the position of our nation is comparatively low than other Asian countries, But in our country average deposit and credit transaction is getting better slowly. But the development seeks more penetration of formal financial services. According to him, the commercial bank needs to be more anxious about their risk management mechanism and support the budding entrepreneurs. He stressed out on the diverse role of commercial banks to spread its deposit wings as well as credit services. It will gradually ensure the sustainable financial inclusion structure in the country. Following this, Gomathy (2015) observes financial inclusion through banks considering both primary and secondary sources in the Thiruvallur district of Tamilnadu. She finds out that financial inclusion is a central part of the development and it needs support from all possible dimensions. So banks should take various initiatives like usage of regional language, no-frill accounts, financial inclusion campaign, engaging business correspondents, enhancement of financial literacy, etc. along with the support from the Government’s end to set up the future platform for better financially included society.

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Talking about recent times, mobile services become part and parcel of our life. In terms of financial inclusion also, it has an equal role to play. According to Kumbhar (2011), mobile banking (m banking) can efficiently and effectively contribute towards financial services for a financially excluded population of our country. By involving both primary and secondary data both m banking users and non-users, he observed that m banking is needed to increase the coverage and penetration of financial inclusion but certain problems like life security, network coverage, cost-effectiveness, etc. need to be taken care of for the prosperity of m banking and financial inclusion thereafter. In line with that, Bansal (2014) supports the facts about the impact of technology in financial inclusion. According to him, in order to expand financial services in backward areas, emphasis should be given to contemporary Information and Communication Technology (ICT). The Intrusion of technology facilitates cost minimization, customer penetration, risk management, etc. in the rural belt. He mentions specific services in his paper which enhance the financial inclusion movement like introduction of ATM services, online banking transactions for SMEs, rural internet kiosks, engaging Business Correspondents (BCs), Nationwide Electronic Financial Inclusion System (NEFIS), Geographical Information System (GIS), Global Positioning System (GPS), GPRS (General Packet Radio Services), Core Banking Solutions (CBS), National Electronic Fund Transfer (NEFT) and Real-Time Gross Settlement (RTGS), etc. Apart from that, financial literacy is equally important for promoting financial inclusion and financial stability. The “Project financial literacy” of RBI constantly operates with the objective of publicizing the banking services information to the different target groups specifically for rural and urban poor. He also mentioned about different initiatives by RBI and NABARD for financial literacy. Further, Gabor and Brooks (2017) observe the growing significance of digital-based financial inclusion. The digitalized revolution helps to expand the financial inclusion program legibly and leading new findings of behavioral economics. Beyond the banking sector and technological advancement, another kind of financial institution also made its footprint quite well in the domain of financial inclusion. With its positive structural design, flexibility and easy access, microfinance institutions play a vital role in the

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movement of financial inclusion. In this context, Vallabh and Chatrath (2006) focus on the rural financial institution for sustainable growth and income. Regardless of the setup of a commercial bank, rural penetration of it is almost zero. So banks delegate their offerings to the MFIs and MFIs also gain a variety of financial products to offer with a fee income in the above-mentioned areas. Beyond traditional banking services towards imparting financial inclusion, Bi and Pandey (2011) make a comparative study to analyze the performance of the microfinancial institution and commercial banks. By collecting primary data from 24 MFIs, they observe that for the last few years the growth rate of MFIs increases significantly but government regulation, regulation of credit supply, alternative funding, etc. issues need to be reviewed for better operations of MFIs in our country from time to time. Christabell and Raj (2012) consider secondary data and referred that the SHG movement brings out the vast transformation in rural areas. The MFIs facilitates financial inclusion among the rural people. Bringing financial services to rural borrowers is the biggest challenge in the movement of financial inclusion. Distance, poor infrastructure and telecommunications, heavy branch regulation, etc. are the causes that restrict the geographical expansion of bank branch networks. Nonbank financial institutions like microfinance institutions help to fill this gap. Even though in India, the microfinance model offers credit and savings to the poor, the challenges faced by the industry has to be set right in due course for the effective working of the model. In line with that, Khandker (2003) conducts a survey in two phases in the selected areas of Bangladesh. By applying Regression on the selective panel data, he finds that there is strong evidence of reduction in poverty of microfinance program participants and MFIs continuously work to reduce poverty among poor borrowers. In the two phases of the survey, the impact of MFIs on poverty reduction was lower in the second phase due to diminishing returns to additional borrowing. Interestingly, MFI intervene is beneficial for the non-participant too because of the development of the local economy. Following this, Dev (2006) observes that financial inclusion is very essential for different vulnerable group and self-help group movement and microfinance has a greater role in it. But it can be successful only if the productivity of the borrowers is sustained

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with viable economic activities. That can be generated by the credit plus services and rural financial institution should be restructured to complement the credit in the entire farm and non-farm sector. Further, Gaiha and Thapa (2006) assess a broader framework referring macroeconomic scenario, nature and execution of credit marketplaces in rural areas, the extent of poverty, etc. to observe the impact of microfinance projects in Asia. They use Probit model to check out the probability of participation in microfinance activities. This paper involves both qualitative and quantitative data to consider the microfinance market scenario, women empowerment in both pre- and postloan phase. They observed that even in small samples if cautiously designed and analyzed could give in rich and important insights into the possibilities of microfinance for empowerment and economic safety. In another study, Adhikary and Bagli (2012) discuss the common problems of rural dwellers for borrowing credits. To fight against these problems SHGs are working in the rural areas among the feminine section of the society. They have collected primary data from 964 rural households of Bankura in West Bengal, to assess the impact of the participation in SHG on access to formal credit and on borrowing cost along with the status checking on whether the SHGs serve the disadvantaged section of people or not. Applying the Logit and Probit model, it has been observed that participation in self-help group activities speed up the access to formal credit sources and reduces the borrowing cost for the disadvantaged section of people. Considering the urban zone, a report of RBI has been published by Rupambara (2007). There he stresses out about the various models like 8 P’s marketing strategy, application of ICT, designing the financial product as per need, etc. to make the urban poor more financially inclusive through MFIs. Also, he refers that all the initiatives of banks/MFIs should not be taken as a mere corporate social responsibility. In line with that, Swami (2012) observes the nature and credit need of the urban poor exploring their socio-economic profile and the urban SHGs activities promoted by both government and nongovernment using structured questionnaire from 340 respondents. His study reveals that non-government SHGs are performing better in loan repayment. The loan repayment rate is quite higher, it is almost upto 100 percent. But transparency is a vital issue in case of this kind of

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SHGs. The economic impact of SHG is almost insignificant but the social impact is notable among the participants. The study also highlights the flaws of government schemes for poverty alleviation. Majority of the non-governmental SHGs fail to produce a standardized product and assured market for business which causes most of the banks in doubt to provide financial support to the Thane dwellers. The transition of borrowers inclusive of credit and credit plus services has been followed for better analysis. Shetty (2008) examines the task of microfinance in the inclusion of poor in Karnataka. This paper uses primary data collected from 318 member households of 106 women SHGs. The study compares between pre- and post-microfinance scenario and reveals that microfinance plus services have a positive correlation with the improvement in household expenditure, income, assets and employment. The microfinance plus services have tried to bring out women specifically to fight against poverty. Mere penetrating both in urban and rural areas could not fulfill the objective of financial inclusion drive by various MFIs. Balasubramaniam et al. (2012) discuss the need for the regulatory mechanism of active microfinance institutions and protecting customers’ interests in India. They propose various regulatory model and mechanism both for MFIs and the clients in the light of MF bill 2012. Taiwo (2012) observes the impact of microfinance in the small and micro-entrepreneurs and check whether it can help in the standard of living in Nigeria. Both primary data (321 respondents) and secondary data have been used and further analyzed by using regression and ordinal least square (OLS) method. He finds that microfinance influences various dimensions of the borrowers’ life from enhancing savings habit, employability, income generation and the growth of microenterprises and so on. It has been reflected in the literature that, FI contributes a lot towards social betterment. But is has certain influencing factors too which barred the overall growth of the society or economy. Mia and Chandran (2016) adopt Malmquist total factor productivity technique with a balanced panel dataset of 162 microfinance institutions which are active in Bangladesh from 2007 to 2012. They have found that the MFI sector in Bangladesh reflects marginal overall productivity progress. Further, considering the financial and social outreach, this study observed the

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reflection of the same scenario in the selected area. Even though, depth of social outreach efficiency recorded following the progress for the duration of the study period, the span of social outreach productivity enhanced little because of the lack of innovative savings products. Results conclude from the five best performing MFIs that the concerned authorities should follow the practices to enhance growth. So it has been observed that for the sake of growth and improvement, financial inclusion is absolutely needed. Different financial institutions both from the government and the non-government sectors influence the process of financial inclusion movement. Depending on the need, area of domicile and poverty, microfinance institutions are coming forward to rectify the scenario.

2.2

Microfinance Institutions: An Overview in Indian Milieu

Financial institutions like microfinance institutions play a key role to cater to the need of poor who are still financially excluded. Microfinance has been explained as a development approach which provides financial as well as social mediation (Ledgerwood, 1999; Robinson, 2002). It has been referred by the Asian Development Bank that the major business of any MFIs is ensuring the provision of microfinance services. It helps to provide sustainable financial assistance to the poor (Yeboah, 2010). Microfinance, a social activity, is regarded as one of the most influencing poverty eradicating tools (Copestake et al., 2005). The term microfinance stands for the provision of collateral-free financial offerings to financially eliminated, economically backward and not empowered people, specifically to female. The various services of MFIs are microcredit, insurance, savings and pension. But among them, microcredit gains the highest acceptability. Microcredit means a program which provides loans for self-employment and various other financial business services (including saving and technical assistance) to the needy persons (Microcredit Summit, 1997) (Table 2.8). The escalation of MFIs evolves from 1991 in the light of financial sector reforms and global emphasis on commercialization. It has got the

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Table 2.8 Different models of microfinance Name of the models

Salient features

Association model

The target group forms an association with youth, men, and women targeted socio-religious-cultural issues that carry out various microfinance activities and also known as group model Initiated and capacitated by NGOs and other organizations that engaged in capacity building of the community members and help them to be an expert in performing various banking financial activities An autonomous association with cooperative members who come together voluntarily to meet their socio-economic-cultural needs. These have self-generating capital, self-governed, middle- and lower-income group clients with financial services Formed by a particular group, institution or organization for saving their money together and rented to members with a democratically predetermined rate of interest Straightforward credit lending model where microloans are given directly to the borrower Taken from Grameen bank of Bangladesh. Here the bank with field manager covers villages to develop acquaintance for working in a group. Lending rotates among the group members after every successful repayment process Under this model, groups of 10–20 members are formed from the same gender or caste to encourage saving among members and use the pooled resources to meet the needs of their members. These are either supported by the government, NGOs, MFIs or other formal and informal agencies

Community banking model

Co-operative model

Credit union model

Individual banking model Grameen joint liability group models

SHG model

(continued)

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Table 2.8 (continued) Name of the models

Salient features

Village banking model

Developed by FINCA International. These banks are by the low-income women’s from villages. The basic motives of these institutions are to improve the socio-economic and living standard of the members through self-employment activities It is created by 5–50 members for making a regular cyclical contribution to a common fund

Rotating savings and credit association (ROSCA) Kisan credit card model

It was launched in by NABARD to provide microfinance facility to poor farmers for agriculture purpose

Source Compiled by Researcher

highest buzz when Md. Yunus got Nobel Prize (2006) for his revolutionary Grameen Bank model practiced in Bangladesh. The interest in microfinance has burgeoned during the last two decades. Gaining popularity from Bangladesh, Md. Yunus describes it as a human right. The delivery mechanism of the MFI is varied from economy to economy. The Grameen Bank model of Bangladesh is one of the most admired. Beyond that, the Bolivian banking model and the rotating savings and credit association (ROSCA) model of South America are also followed in various parts of the globe. In India, various models like self-help groups (SHGs) and joint liability groups are widely followed (Biswas & Sana, 2015). In our country, microfinance has come across different stages towards the attainment of financial inclusion (Table 2.9). India has multiple numbers of microfinance models, both contemporary and original and each has succeeded in its own way, the models vary from SHGs and co-operatives to adapted models like the Grameen Bank method and for-profit corporate (Sa-Dhan Report, 2003). So, to have a better idea about the outreach and penetration of MFIs, the understanding and perception towards microfinance carry a lot of meaning. People should have proper awareness and idea about MFIs and its activities, then only MFIs will be able to contribute more effectively in the map of financial inclusion of India. For a couple of years, microfinance

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Table 2.9 Journey of MFIs in India Stages

Description

Introduction of Social Banking (1960–1990)

. . . .

Approaches towards Financial System (1990–2000)

Financial Inclusion (2000 onwards)

. . . . .

Nationalization of Commercial Banks Expansion of rural banking network Widespread disbursement of credit Establishment of NGO-based microfinance institutions SBLP initiated and quickly replicated Creative credit lending mechanisms focused on “peer pressure” and “moral collateral” Commercialization of Microfinance Establishment and advance of NBFCs Evolving of customer-centric microfinance

Source Compiled by Researcher

institutions are playing an eye-catching role in financial inclusion and growth of rural dwellers of West Bengal especially through the branch and credit penetration (CRISIL Inclusix, 2015). Aside from credit, financial inclusion cover-ups different financial services like savings, insurance, payments and remittance facilities by the formal financial system (Dev, 2006). The different services provided by the microfinance institutions are:

2.2.1 Microcredit It is one of the basic and most probably the most popular services of any microfinance institutions. It can make a positive change in the economic cycle of a borrower. It generates power to the borrower for generating income, employment and so on. The average microcredit amount is lesser than corporate or personal loans. The key features of microcredit are social collateral, forced savings, small initial loan size, frequent payments, standardized loan disbursal and repayment structure, etc. The founder of Grameen bank has just been awarded the 2006 Noble prize but it has also been a topic of interest to researchers since its inception in the early 1970s. One very interesting observation about the microcredit programs is that they do not distinguish between clients; rather, they provide loans to everyone. It has been a general view among the key resource persons that microcredit is vital in reducing poverty though the empirical evidence provides a mixed response.

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2.2.2 Micro Pension To safeguard the lives of people who specifically work in the informal sector and barred from the conventional pension scheme, micro pension act as a savior for them. Government schemes like the New Pension Scheme (NPS) launched in 2003 is gaining enrollment from the informal labor segment gradually. For an effective micro pension, the balance between economic feasibility, generation of ample returns and customized features for the participants is needed. As low-income groups prefer lower-value and frequent deposits, convenient services should be accompanied accordingly.

2.2.3 Micro Insurance It is specially designed for the security of low-income people, with reasonable insurance to cover from common risks. It is a key constituent in the MFI services for the bottom of the pyramid population. Uninsured hazard departs poor family units vulnerable to severe losses from negative shocks. It also compels them to follow expensive strategies to manage their incomes and savings. In true sense, it can provide economic and psychological safety towards multiple risks.

2.3

Women Empowerment: A Delineate on Indian Context

If we consider the issues which can be positioned as most chaotic and problematic, highlighted and impactful throughout the globe, we may probably have gender discrimination as one of them. The common areas where girls or women faced continuous and rigorous exploitation are education, mobility, ability or giving power to make decisions, health and hygiene issues, formal employment, pay structure, etc. As an outcome they feel suffocated, voiceless and sometimes they don’t even feel to talk about these issues. It hinders their organic growth and act as an impediment towards empowerment.

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According to the World Bank report (2018) on gender issues, it has been observed that among all the regions in the world, South Asian countries have the least gender Development Index (0.822, 2015). As an important element of financial inclusion, a wide range of initiatives has been taken for female equality. One of such proposals has been taken by microfinance institutions to present their services for those who are financially left out and economically backward and not empowered, particularly women. Among the various purposes of microfinance institutions, empowering female is one of the most fundamental one. Empowerment reflects superior involvement in decision making and through this people feel themselves to be competent of making decisions and the right to do so. Empowerment can reinforce good governance, which enhances growth prospects. Empowerment becomes an obligation not simply an option for growth and development. It can be comprehended through various dimensions. Out of them, the well-being of the female population is one sensitive area to consider. As equal opportunity irrespective of gender is compulsory for that, empowerment for the backward part of society (women empowerment) came into the picture. In order to have a better world, the United Nations announced the Millennium Development Goals with eight specific targets to be achieved by 2015. Gender equality along with female empowerment regarded as the third one in the formulated Millennium Development Goals. So the relevance of the issue can be easily understood. Kabeer (2005) mentioned empowerment as adding up in people’s capability to plan strategic life choices in a situation where this ability was previously denied to them. Women empowerment is a versatile concept and a constant process, and defining it is itself a challenging task. Further, women empowerment is not directly visible and that’s why difficult to measure. Now on this backdrop, we further tested the role of microfinance institutions in financial inclusion along with empowerment of the feminine society empirically.

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2.3.1 Female Empowerment and Sustainable Growth in India Women empowerment seeks global concerns because it is absolutely essential for other areas to grow and sustain like inclusive and sustainable growth, minimization of poverty, security of food, equality on gender basis and likewise. But it is really challenging to define empowerment in definite words. Resources are needed when we think about empowerment, enrichment, tactful decision making and so on. From the early historical backdrop, women have been kept as dependent, powerless and few steps backward while considering the ways to advancement like education, property, credit, etc. Resource accessibility alone could not turn around the whole scenario, but it can pave the way towards positive changes in surroundings. In fact, in order to unlock the female’s credentials, empowerment is much needed. Empowerment leads to improve different areas which in turn make sustainable growth and development a reality. One such area is the Gender Inequality Index (GII). It reflects the level of gender inequality composed of three basic elements—health (calculated by maternal mortality ratio and adolescent birth rates), empowerment (expressed by proportion of parliamentary seats taken by females and proportions of adults aged 25 and more) and labour market (denotes labour force participation, aged 15 and more, irrespective of gender). The GII value ranges from 0 to 1 and higher value indicates higher inequality and so on. Our country in terms of GII stands in a moderate position. It means a lot of scopes are still there to improve the scenario towards development (Table 2.10).

2.3.2 Government Initiatives and Women Empowerment: Indian Perspective The Government has initiated aggressive initiatives to assure issues of concern (equality, female empowerment, etc.). From the beginning, every five-year plan of our government ensures provisions for socioeconomic development of women, girl child basic education, health and

127 (2017)

0.524 (2017)

174 (2015)

Source UNDP Report, 2017

Rank

Maternal Mortality Ratio (Deaths per 1,00,000 live births) 23.1 (2015–20)

Adolescent Birth Rate (Births per 1000 women ages 15–19)

Different development parameters of India

Gender Inequality Index (GII)

Table 2.10

11.6 (2017)

Share of seats in Parliament (% held by women)

Female: 39.0 Male: 63.5 (2010–17)

Population with at least some secondary education (% ages 25 or older)

Female: 27.2 Male: 78.8 (2017)

Labour force participation rate (% ages 15 & older)

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hygiene awareness, child care, maternity health care, economic freedom, social recognition, etc. In fact, from Eight-year plan (1992–97) onwards empowerment issues are taken care of rather than mere development of women. Further programs like the Integrated Rural Development Programme (IRDP), Development of Women and Children in Rural Areas (DWRCA), Training of Rural Youth for Self Employment (TRYSEM), National Rural Development Partnership (NRDP), Rural Landless Employment Guarantee Programme (RLEGP), Jawahar Rozgar Yojana (JRY), etc. also contribute to the journey of empowerment. But in reality, these programs could not help much. In this context, SHG was introduced under SGSY in 1999 for the advancement of socio-economic circumstances of female in general and empowerment in particular. Apart from that, the following schemes are active for generating and ensuring sustainable empowerment of the feminine gender into our country: . Support to Training and Employment Programme (STEP ) Since 1986–87, the central government promoted this scheme with an objective of inculcating skills needed for employability for women and support them towards entrepreneurship. . Rajiv Gandhi Scheme for Empowerment of Adolescent Girls, SABLA This scheme is popularly known as SABLA. It is a scheme to empower adolescent girl (age 11–18) only. It also focuses on the school dropout girls regarding their health and nutrition status. . Swabalamban It is a co-contributory Pension Scheme to motivate people from the unorganized sector to voluntarily put away money for their retirement and overcome unavoidable circumstances.

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. Construction/Expansion of Hostel Building for Working Women with a Day Care Center (WWH) For inspiring women in employment and technical training, inexpensive and safe hostel facility has been provided with a day care center. . Balika Samriddhi Yojana (BSY) Since its inception in 1997, this scheme is working continuously to change the negative attitude towards girls’ child among different communities. . National Program for Adolescent Girls (Kishori Shakti Yojana) With aiming towards adolescent girl, the purposes of this proposal are to advance the nutritional, health and development status, create awareness of hygiene, health, nutrition and family care, connect them to chances for learning life skills, get them back to school, help them to have a better understanding of their society and initiate them to be a productive member of the society. . Shishu Greha Scheme Ministry of women and child development introduced his scheme in order to provide child adoption throughout the nation. In our country, everyday a good number of orphans forced to live a distressed life. So this scheme ensures to prevent this situation and prior to adoption, complete child care has been taken care of. . Integrated Scheme for Street Children Launched in 2009–10, this program targeted at those children who reside on the street. Various issues like health, nutrition, education, recreation facilities, etc. have been taken care of relating to the street children.

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. Scheme for Welfare of Working Children in Need of Care and Protection The basic purpose of this program is to uphold the rights to education for working children in the structure of vocational training and nonformal education. Through this program, an attempt has been made to introduce the children into the formal education system for a better future. . Prevention and Control of Juvenile Maladjustment This scheme mainly focuses on the betterment of excellence in the juvenile justice system. An effective connection will be established with community-based welfare institutions, whether to execute by a voluntary organization or organize under the general child welfare, by means of licensing or certification. Greater stress will be there on individualized handling of the juvenile through the activities of study and diagnosis, appropriate placement, corrective education, vocational training and social re-assimilation. . Integrated Child Protection Scheme (ICPS) It aimed at ensuring a protective environment for children in difficult situations, as well as other vulnerable children. It is a joint effort of Government and civil society partnership. It maintains a child protection database which helps to formulate and implement effective programs from time to time for safeguarding the child from various circumstances. . Conditional Cash Transfer Scheme for the Girl Child with Insurance Cover This program has been designed specifically, aimed at girl child on fulfilling certain specific situation.

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. General Grant-in-Aid for Voluntary Organizations in the Field of Women and Child Development This is a support to innovative voluntary projects for female and children. This scheme has been launched by the Ministry of Women and Child Development. . National Mission of Empowerment of Women Holistic empowerment of females has been taken care of by the funder of this scheme. The basic focus areas here are economic and social empowerment, restrict violence against women, gender equality, awareness creation, etc. . Scheme for Leadership Development of Minority Women This scheme has been operated under the Ministry of Minority Affairs. The major focus of this scheme is to enhance leadership quality among minority women and empower them with confidence building, financial literacy and awareness creation. . Education Scheme, Food and Nutrition Board (FNB) This wing provides technical support under the child development bureau of the ministry to oversee the progress of recommended dietary allowances (RDAs) on a continuous basis. . Ujjawala, Scheme for Combating Trafficking The Ministry of Women and Child Development was implementing Ujjawala in 2007 to combat the human trafficking movement which is in an alarming situation till date. Further, under this scheme rescue, rehabilitation, reintegration and repatriation of trafficking victims’ commercial sexual exploitation have been taken care of.

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. Nutrition Programme for Adolescent Girls (NPAG) It was launched in 2002–03 serving the nutrition need of adolescent girls, lactating mother and pregnant women. The food has been distributed through the public distribution system free of cost to the families identified specifically for this project. . Wheat-Based Nutrition Program This program has been implemented with the collaboration of ICDS. Here, ICDS beneficiaries have been generated with food grain to supplement their nutritional needs. . Anganwadi Karyakati Bima Yojana The Anganwadi Workers and Anganwadi Helpers are having insurance coverage under this scheme. This has been operated with premium contributions of Government of India, Life Insurance Corporation of India and the beneficiaries.

2.3.3 Empowerment and Microfinance A large number of literature mentioned that empowerment is directly proportionate with development. It inspires good governance and accelerates the growth prospect from the very grassroot level of society. The institutional presence or absence can create incentives for action or inaction in this process. As the environmental context varies from time to time and place to place, that’s why institutions’ activity and role also adopts as per the situation. At this point, microfinance adopt itself nicely and able to penetrate into the poor and excluded household to bring the desired change. With all other predetermined objectives, microfinance institutions are working towards attaining of gender equality for sustainable growth and advancement of the society. Conventionally, females have been treated as insignificant worldwide. They are rarely financially independent and often they have been referred as the most vulnerable members of society.

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A modern and developed society needs both its male and female counterpart for further progression. For that, females need to be socially and financially aware, self-dependent, confident and able to access all the avenues of development like the male counterpart of the society. This reflects the true spirit of women empowerment. It is not only a tool towards progression, but it is a philosophy which should be reflected in terms of mobility, decision making, employment generation, better credit utilizations, formal finance access, etc. More precisely, assessment of women’s empowerment included questions on their part in decision making; their status and well-being; social capital arising from membership of savings and credit groups (SCGs); and what work they considered suitable for women. In India, the history of rural credit, poverty alleviation, empowerment and microfinance are inextricably interwoven. It even may ensure gender equality in all respects in the society. The autonomy of the female counterpart ensures the improvement of health, social and political status of the women and that helps to build a transparent administration and sustainable betterment in all aspects of life. In this context, microfinance institution helps to access desired information which motivates more participation in formal lending, social activities, decision making, uplifting the economic and social background and so on, on behalf of the female populations. The influence of the financial institutions especially incorporating the microfinance institutions can be observed in a systematic manner. The impact of microfinance on women empowerment can be represented in a diagrammatic structure (Fig. 2.8).

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Women empowerment Gender relation

Women status Changes occur within household

Decision making ability

Independent income

Household income

Access to Microfinance institutions

Fig. 2.8 Linkage between empowerment and microfinance institutions (Source Compiled by Researcher)

2.4

Interrelationship Between Financial Inclusion, Microfinance and Women Empowerment

Financial freedom is one of the major and critical indicators of independence—be it economic or in a spiritual context. It comes with the inclusion of access, mobility, income, savings, empowerment, participation, etc. In this journey of earning financial independence, financial inclusion is considered to be one of the most pioneer ways to accomplish it. Financial inclusion helps to overcome economic hardships, breaking the vicious cycle of poverty, creating resources, engender and indoctrinate entrepreneurship. Numerous institutions including microfinance organizations embrace this path and add momentum to the affluence of financial inclusion. The digitalization of these institutions also helps financial inclusion initiatives into a reality. In a country like India where moneylenders do exist and operate in full swing, microfinance organizations operate quite impressively with comparative lower rates to lend microcredit to the bottom of the pyramid or to those whoever needs credit for various purposes (Banerjee, 2013). Being the bankers of the poor as well as for the unbanked population, MFIs constantly strive on to incorporate the targeted population to be financially erudite and inclusive. Globally, MFIs have been considered as a credit-based poverty

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alleviation and financial inclusion tool (Chavan & Birajdar, 2009). It is able to break down various obstacles towards attaining financial inclusion (Datta & Sahu, 2021). Gender is an important factor in terms of development, growth, equality and sustainability. Though most of the studies revolve around the female and inclusion issues, both genders have the equal rights to be financially included. A well-inclusive society can prosper and sustain and even crave for betterment in the long run. But in most of the countries, be it developed or developing or backward due to demographic, socio-graphic and economic structure, female stays behind and lack lots of opportunities towards prosperity. Gender gap is a burning issue even with the countries of high financial inclusion (Fanta & Mutsonziwa, 2021). So, financial inclusion has much more deeper meaning for the women. MFIs and financial inclusion are linked by long-run relationships (Adeola & Evans, 2017). MFIs become a veritable institutional mechanism for enhancing credit access for low-income groups especially for the feminine sections of the society. Women are the change agents for their household as well as for the society. A financially inclusive woman can handle noteworthy issues of household like health, hygiene, education, domestic violence, male alcohol abuse, wealth creation, etc. in a better way. Most importantly, females have the trait of upholding relations and household, sustenance and endurance, etc. in their nature, which transforms them into being more reliable for loan repayment issues compared to men. This is the reason why MFIs tend to generally target the female population and upkeep them to be financially inclusive and empowered. Women empowerment is vital for the growth of the nation (Gupta, 2021). The reason behind this is the level of women empowerment in household backdrop influences women’s attitude, ability and skill to handle different matters in a better way within and beyond the household. The microcredit and its effective utilization thrust the female borrower towards improved decision making, risk taking and bearing, enhance communication skills, confidence building, wealth creation, employment generation and so on, i.e., make them empowered. Microfinance helps the female borrowers to be more self-aware with increased degree of self-esteem and self-efficacy. Access to capital or microcredit

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could not alone make a woman independent and empowered (Khursheed et al., 2021), but the creation of awareness, constant support and interactions of the MFIs transform the borrowers into empowered state. Microfinance enhances the entrepreneurial ability among the female borrowers (Mia, 2021) and advances their capacity to overcome the indecisive, challenging, and incapacitating blockage exists in her life. Generally family norms, financial issues and social obstacles hinder the development of females as business owner or entrepreneur. Most of the women-centric set up loiters around traditional local products like tailoring, food, clothing, etc. But an empowered woman can actually think beyond that and can venture into any field of her preference. It enhances the personal growth and behavioral effects of an individual. The burgeoning of entrepreneurial outcome is subject to different sensitive conditioning but MFIs intervention definitely takes a positive role in it.

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3 Perception of Borrowers and Non-borrowers Towards MFIs

3.1

Introduction

The increasing complexity of the financial services scenario has pushed the beneficiaries to access the resources, build awareness, analyze the pros and cons of any offerings, etc. Financial decision making has always been influenced by time. A person can avail a wrong path regarding financial services under the time constraint and stress. So, correct perception about the available resources is essential towards a stable lifestyle. According to Nguyen et al. (2019), risky-asset allocation has been directly influenced by risk tolerance and indirectly over risk perception. So, this finding can assume that females who are generally vulnerable in decision making, a correct decision backed by right perception can push then towards investment decision, risk initiation, creativity acceleration for sustaining, productive utilization of credit and return on investment. There are different psychological factors which affect investment and borrowing decision of the creditors. Perception towards availability, offerings and repayment methods, potential pros and cons, etc. impact a lot while one is searching for credit. Not only that, a clear perception about the credit sources builds up confidence among the beneficiaries, and they © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4_3

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are able to recommend the right path to the others regarding borrowing, investment and repayment. Microfinance services are always famous for its flexibility and at doorstep services. The staff from the MFIs always interact with the current and potential borrowers, discuss in detail about the loanstructure and repayment options, benefits and all the related issues regarding it. Beyond that, MFIs also organize periodical awareness camp, counseling and discussion forums, training arrangements, etc. which contribute towards the correct perception building for MFI services.

3.2

Literary Overview Related to Perception About MFIs

Perception plays a major role in decision making especially in case of monetary transactions. India, till date, is governed by the rural regions. So, it is important to understand the impact of perception towards formal financial institutions covering both supply and demand side in connection to financial inclusion. Rachana (2011) in her research observes the attitudes and activities of banking services specifically in rural areas, the demography of rural habitat, their financial behavior, etc. The paper incorporated primary data of 200 respondents residing in three villages of Gujrat and collecting information from them with a structured questionnaire. Followed by Chi-square test and tabulation, she came into the conclusion that Regional Rural Banks (RRBs) and Primary Agricultural Credit Societies (PACs) have wide coverage in rural belts but both are running into losses. Also, Kisan Credit Card followed a negative trend. So in this circumstance, commercial banks can tap the untapped zone of rural financially excluded population with the help of Business Correspondence (BC) or Self-Help Groups (SHGs) or by offering flexible and customer-friendly services. Bottom of the pyramid has always been the target group for financial inclusion as they are the most deprived section of the society. The Government of India has already taken aggressive strategies for financial inclusion and under no-frill account, a huge proportion of unbanked adults ended up with a savings account of his/her own. But in reality,

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according to Morawczynski et al. (2010) majority of the bank accounts have not being utilized by the targeted poor. Their research considers data collected from an empirical study conducted in three Indian states with 133 interviews over the period of one month. The demography characteristics of most of the informants were poor, lived-in rural areas and held no-frill savings accounts. The study unfolded two interesting facts—first of all, most of the respondents who possessed bank accounts are not active and secondly focus has been given towards financial education for better financial inclusion. Moreover, the emphasis would be given to peer-to-peer learning for improving the current scenario. Following this Ramji (2009) refers that the numbers of household who hold bank accounts become doubled over the duration of financial inclusion drive. But bank accounts have been opened typically to receive government assistance; mostly NREGA, usage and awareness remain low. More initiatives and applications are needed to boost financial literacy and marketing so that the banking services can be optimally used. Further, Rangappa et al. (2008) mention the transition in the philosophy of commercial bank from class banking to mass banking failed miserably. They observe the reasons behind this are structural limitations and sole focus on credit disbursement to the poor. So, NABARD launched its Self-Help Group (SHGs) bank linkage program to combat the situation. In their paper, 240 households from Davangere district of Karnataka state were selected through multistage stratified random sampling. Primary data regarding certain parameters like demographic profile of the family, borrowing and saving details, and involvement in SHG, etc. have been collected. By applying mean, t-test the relative share of formal and informal sources of borrowing has been tracked down. Further, financial inclusion index has been developed by giving suitable emphasis on selective financial services. They came into the conclusion that SHG bank linkage program is successful for imparting financial inclusion movement and the high degree of FI, with reference to financial inclusion index, observed in that household who are a part of SHGs bank linkage movement. It clearly showed the impact of institutional support for evolving FI and to develop a correct perception towards it in society.

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There are certain elements that are also needed for the creation of right perception towards financial institutions. Allen et al. (2012) find that to access financial services one needs to have a better environment which can be ensured by ownership and use of formal accounts. They have identified certain perceived barriers which prohibit the excluded population to access formal financial institutions. So, policies should be developed to reduce barriers to encourage new and existing account holders for saving and accessing several welfare benefits associated with it. Perception building depends on various clues associated with the targeted population. In order to build a correct perception, both institutions and beneficiaries need to interact with each other in a positive environment. Better financial inclusion and financial literacy are possible only when it starts with the correct perception.

3.3

Perception of Borrowers and Non-borrowers of MFIs: Empirical Evidences

3.3.1 Research Design The implication of empirical research largely depends on the types of data and application of the relevant methodology for effective analysis and interpretation. This section includes a detailed description on the procedure used to collect information and data applied to a field of study, sampling technique adopted, the econometric tests being applied and the scheme followed for the investigation, etc. To serve the purpose of the study, we follow a strong research methodology as discussed under the following points.

3.3.1.1 Data Types For the purpose of the study, primary data have been used. Primary data have been collected from the selected sample from the mentioned backward districts of West Bengal.

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3.3.1.2 Sample Design The selected districts for the study are Purulia, Bankura and Paschim Medinipur which are further subdivided into administrative subdivisions. Purulia is having four subdivisions (Sadar, Manbazar, Jhalda and Raghunathpur), Bankura is having three subdivisions (Bankura Sadar, Khatra and Bishnupur) and Paschim Medinipur is having three subdivisions (Medinipur Sadar, Kharagpur and Ghatal). First of all, from all the three districts, a total number of 600 respondents (200 respondents from each district) have been considered initially for uniformity of sample distribution (at least 50 respondents have been selected from each subdivision of Purulia, Bankura and Paschim Medinipur each subdivision). Out of the total collected sample at least 44 samples (consisting bias-free completed questionnaire) from each subdivision considering both nonborrowers and borrowers have been considered for perception tracking. So, finally 528 respondents (including 264 borrowers and 264 nonborrowers) covering three districts (having at least 176 respondents from each district consisting bias-free completed questionnaire) have been considered for tracking the perception level among the respondents. A sample is a percentage which represents the total population. That’s why it is very vital to choose the correct sample size. Cochran’s formula has been used for determining the sample size. It is considered appropriate when the population size is comparatively large. According to Cochran’s formula, there is two way of estimating sample size given below: I. Cochran’s formula for calculating sample size when the population is infinite in nature: Cochran (1977) build up a formula to calculate a representative sample for proportions as n0 =

(z)2 ( p)(q) (e)2

Here, n 0 is the sample size, z is the selected critical value of desired confidence level, p is the estimated proportion of an attribute that is

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present in the population, q = 1 − p and e is the desired level of precision. Assume there is a large population but in that, we do not know the variability in the proportion that will adopt the practice; therefore, assume p = 0.5 (maximum variability). Furthermore, suppose we desire a 95% confidence level and +5 precision. Then the calculation for the required sample size is as follows: So hence, p = 0.5 q = 1 − p = 1 − 0.5 = 0.5 Z = 1.96 e = 0.05 ( ) z 2 ( p)(q) = (1.96 ∗ 1.96)(0.5 ∗ 0.5) Then n 0 = (1.96 ∗ 1.96)(0.5 ∗ 0.5)/0.05 ∗ 0.05 = 384 II. Cochran’s formula for calculating sample size when population size, i.e., 10,000 or less. Then Cochran indicated out that the sample size can be reduced slightly. He proposed a new corrected formula n = (nn 00 −1) to calculate the final sample size which was used in this 1+

N

study is given below: n =

1+

n0 (n 0 −1) N

.

As here the population size is infinite (more than 10,000) so the sample size in this study is 384 but we have used 500 (250 borrowers and 250 non-borrowers) for perception tracking and analyzing the impact of MFIs on the livelihood for more robustness of result of this study.

3.3.1.3 Data Collection Techniques Primary data have been gathered from the selected sample using multistage random sampling through a structured questionnaire with a reasonable and representative sample size.

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3.3.1.4 Sample Size The total sample size is 528 (264 borrowers and 264 non-borrowers) for this study covering three districts.

3.3.1.5 Study Period For this study, we have collected the required primary data from August 2021 to May 2022.

3.3.1.6 Description of Data In this study, the perception of operating MFIs and their activities are observed. For that purpose, both borrowers and non-borrowers from the selected three districts have been considered in the first questionnaire. The demographic elements considered here are age, occupation, marital status, literacy level, caste profile, religion, family type, area of domicile and income profile of the respondents. Age has four levels which are 20–30 years old, 31–40 years old, 41– 50 years old and above 50 years. Occupation has been classified as six levels: employed, self-employed, agricultural labor, housewife, wage labor and domestic help. Marital status has four variations: married, unmarried, widow and divorced for the questionnaire covering both borrowers and nonborrowers. In the case of borrowers only questionnaire, marital status has three types: married, widow and divorced. The literacy levels of the participants have been classified into six levels. The classifications are illiterate, elementary, primary, secondary, H.S and U.G and above. Caste has four types: general, scheduled caste (SC), scheduled tribe (ST) and other backward community (OBC). Religion has four variations: Hindu, Muslim, Christian and other. Family type of the sample has two variations which are nuclear and joint. Area of domicile has been divided into the rural and urban area. Income profile has five categories starting from monthly income of Rs. 2,000–4,000; 4,000–6,000; 6,000–8,000; 8,000–10,000; and above 10,000.

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3.3.1.7 Statistical and Econometric Tests Used in the Study Descriptive statistics are the summary statistics that quantitatively describe or summarize features of a collection of information. It includes the presentation of numerical facts or data in either table or graphical format and with the methodology of analyzing the data. The basic objective of any table and graph or chart is to give quick, easy-to-read and interpret data for better understanding. Along with descriptive statistics, various other statistical and econometric tests have also been incorporated in this study. To compare the perception level among borrowers and non-borrowers, t-test has been applied. It is one type of inferential statistics, and it has been used when here is a significant difference between the means of both of the factors.

3.3.1.8 Scheme of Investigation The course of the study is entirely designed on the basis of the formulated objectives. A combination of both open and close-ended questionnaire with binary and polychotomous responses used for analyzing the stated objectives. To test the reliability, appropriate reliability test has been carried out on a pilot study considering 30 samples. Considering Zikmund and Babin (2015), the pilot was aimed at verifying the clarity of words, sentence sequence and their relevance. The Cronbach’s alpha for the different parameters is given in Table 3.1. As Alpha score above 0.60 is treated as good in social sciences (Shelby, 2011). So, in this study, the designed questionnaire is regarded as reliable as the Cronbach’s alpha scores are higher than 0.06 considering all the questionnaire. Table 3.1 Cronbach’s Alpha score Elements

Alpha score

Perception tracking

0.704

Source Calculated by authors

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At first, in case of perception tracking among borrowers and nonborrowers, after collecting the responses on a binary scale (Yes/No) through structured questionnaire comprised of 25 questions, all the correct responses have been coded as 1, and all the incorrect responses have been coded as 0. Considering the scores obtained from the survey, all the 528 responses (264 for borrowers and 264 for non-borrowers) have been summed up to develop two indexes for borrowers and non-borrowers, respectively. Then on the basis of the index data statistical test like F and t has been applied to check whether there exists any significant difference in perception level between borrowers and non-borrowers.

3.3.2 Analysis Conducting a survey on a total of 500 respondents (both borrowers and non-borrowers) and 400 respondents (borrowers only that’ll be discussed in detail in the next chapters), the findings of various demographic factors are discussed below, respectively.

3.3.2.1 Demographic Factors of Borrowers Only In case of analyzing age profile of the respondent, 6% sample belong to 20–30 years of age, 44% belong to 31–40 years of age, 42% belong to 41–50 years of age and rest belong to above 50 years of age (Fig. 3.1). Among the 400 samples (borrowers only) 8% are employed, 15% are self-employed, 5% are agricultural labor, 9% are housewife, 31% are wage labor and 34% work as domestic help (Fig. 3.2). Among the borrowers, 79% are married, 15% are widow and 7% are divorced (Fig. 3.3). It is found that among 400 respondents 42% are illiterate, 22% respondents are having the elementary level of education, 24% are having primary education, 7% are having a secondary level of education and 5% are having the qualification of higher secondary (Figs. 3.4 and 3.5).

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176

166

34 20-30 YRS

24 31-40YRS

41-50 YRS

ABOVE 50 YRS

AGE PROFILE OF THE RESPONDENTS

NUMBER OF THE RESPONDENTS

Fig. 3.1 Age profile of the respondents (Source Calculated by authors)

122 32

58 19

134

35

OCCUPATION PROFILE OF THE RESPONDENTS Fig. 3.2 Occupation profile of the respondents (Source Calculated by author)

It is found that among 400 respondents 35% are general, 37% are SC, 20% of respondents are ST and 8% are OBC. Among the 400 borrowers, 92% of respondents are Hindu and only 8% of respondents are Muslims (Figs. 3.6 and 3.7).

NUMBER OF THE RESPONDENTS

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314

59 MARRIED

27

WIDOW

DIVORCED

MARITAL STATUS OF THE RESPONDENTS

NUMBER OF THE RESPONDENTS

Fig. 3.3 Marital status of the respondents (Source Calculated by authors)

169

90

99 32

I L L I T E R A T EE L E M E N T A R Y P R I M A R Y S E C O N D A R Y

10 H.S

0 UG & ABOVE

Fig. 3.4 Literacy levels of the respondents (Source Calculated by authors)

From the survey, it has been observed that 54% of respondents belong to nuclear family whereas 46% respondents belong to joint family setup. It has been found that among 400 sample, 59% reside in the rural area whereas 42% reside in urban areas (Figs. 3.8 and 3.9). Out of 400 respondents, 8% earn Rs. 2000–4000 monthly, 17% earn Rs. 4000–6000 monthly, 58% earn within Rs. 6000–8000, 8% earn within Rs. 8000–10,000 and 8% respondents earn above 10,000 monthly.

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149 80 30

GENERAL

SC

ST

OBC

CASTE PROFILE OF THE RESPONDENTS

NUMBER OF THE RESPONDENTS

Fig. 3.5 Caste profile of the respondents (Source Calculated by authors)

366

34 HINDU

MUSLIM

0 CHRISTIAN

0 OTHER

RELIGION PROFILE OF THE RESPONDENTS Fig. 3.6 Religion of the respondents (Source Calculated by authors)

NUMBER OFTHE RESPONDENTS

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216 184

NUCLEAR

JOINT

FAMILY PROFILE OF THE RESPONDENTS

Number of the Respondents

Fig. 3.7 Family type of the respondents (Source Calculated by authors)

250 200 150

234 166

100 50 0 Rural

Urban

Respondents' Area of Domicile Profile Fig. 3.8 Area of domicile of the respondents (Source Calculated by authors)

Number of the Respondents

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250 200 150

234

100 50

34

67

33

32

0 2,000-4,000

4,000-6,000

6,000-8,000 8,000-10,000 above 10,000 Income Profile of the Respondents

Fig. 3.9 Income profile of the respondents (Source Calculated by authors)

3.3.2.2 Perception of Borrowers and Non-borrowers About MFIs in the Proposed Area To find out the perception level towards MFIs total of 528 respondents have been selected. Among 528 respondents, 264 are borrowers and 264 are non-borrowers. A structured questionnaire of 26 questions with a binary response (Yes/No) has been developed for this purpose. After getting all the responses from a total of 528 respondents’ correct responses have been coded as “1” and incorrect responses have been coded as “0”. Based on this weightage, two separate indexes have been developed (one from the borrower’s view, another from the non-borrower’s view). Now, it has been analyzed whether any significant difference exists among these two groups (borrowers and non-borrowers) considering the perception level. Before going to t-test we have applied F -test to check whether there is any significant difference in variance related to the perception level of the borrowers and non-borrowers. From the F -test, it has been observed that there exists a significant difference in variance between the two selected groups. Considering the significant difference in two groups we have applied t-test with an unequal variance to check the existence of mean difference, if any, among borrowers’ and non-borrowers’ perception level. From Table 3.2, it has been observed that calculated value of t statistics

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Table 3.2 Result of F-test and t-test for perception level of borrowers and nonborrowers Borrowers Non-borrowers

Mean

Variance

F-value

t-value

17.572 16.740

13.69921 14.58673

0.939156 (0.03103920)

2.750143 (0.003807)

() indicate the probability values Source Calculated by authors

is greater than the critical value of t (p = 0.003807), indicate the null hypothesis of having equal mean is rejected at 1% significant level. The result indicates that a significant difference exists among borrowers’ and non-borrowers’ perception level. Also, as the mean difference among the two groups is significant, and the mean value of borrowers is higher than the non-borrowers so it can be concluded that the borrowers are having a better perception level towards MFIs.

3.3.3 Findings The analysis shows that there exist perceptual differences among the borrowers and non-borrowers regarding the activities of the MFIs in the proposed area. This finding is similar to Rangappa et al. (2008) and Allen et al. (2012). It is due to attachment, interaction, development of familiarity and learning about the MFIs, its activities, benefits, etc. within the time span. It assists in enhancing financial literacy among the beneficiaries.

References Books, Journal, Research Paper, Working Papers, Reports etc. Allen, F., Demirgüç-Kunt, A., Klapper, L. F., & Martinez Peria, M. S. (2012). The Foundations of Financial Inclusion: Understanding Ownership and Use of Formal Accounts. World Bank Policy Research Working Paper-6290.

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Babin, B. J., & Zikmund, W. G. (2015). Exploring Marketing Research. Cengage Learning. Cochran, W. G. (1977). Sampling Techniques. John Wiley & Sons. Morawczynski, O., Hutchful, D., Cutrell, E., & Rangaswamy, N. (2010). The Bank Account Is Not Enough: Examining Strategies for Financial Inclusion in India. In Proceedings of the 4th ACM/IEEE International Conference on Information and Communication Technologies and Development (p. 24). ACM. Nguyen, L., Gallery, G., & Newton, C. (2019). The Joint Influence of Financial Risk Perception and Risk Tolerance on Individual Investment Decision-Making. Accounting & Finance, 59 (S1), 747–771. https://doi.org/ 10.1111/acfi.12295. Rachana, T. (2011). Financial Inclusion and Performance of Rural CoOperative Banks in Gujarat. Research Journal of Finance and Accounting, 2(6), 1–25. Ramji, M. (2009). Financial Inclusion in Gulbarga: Finding Usage in Access (Working Paper-26). Institute for Financial Management and Research Centre for Micro Finance. Rangappa, K. B., Bai, R., & Sandesh, A. L. (2008). SHG-Bank Linkage Programme and Financial Inclusion: Rural Household Study in Davangere District of Karnataka. In 10th Money and Finance Conference at IGIDR, Mumbai (pp. 18–19). Shelby, L. B. (2011). Beyond Cronbach’s Alpha: Considering Confirmatory Factor Analysis and Segmentation. Human Dimensions of Wildlife, 16 (2), 142–148.

4 Credit Utilization Pattern of the Borrowers

4.1

Introduction

Microcredit incorporates initiatives ranging from modest thrift to credit sustenance for income-generating activities. It provides working capital to engage in micro or small ventures. It is for the advancement of vulnerable and disadvantaged groups across the country. The productive usage of credit amount can bring out vivid positive consequences directly and indirectly. The enlargement of microfinance outlines has brought rural family unit to greater access to credit for a number of purposes. Microcredit facilitated “female entrepreneurship and income generation along with improved household incomes and expenditure”. Human capital investment, exclusively in education, is a conversant precursor of economic progression in developing countries. The contributing influence of microcredit participation influences the likelihood of school enrollment for girls. Moreover, financing of microcredit is extensively help liable as an operative change method for mitigation of poverty and empowerment of women. The effective utilization of microcredit eventually brings down decision-making ability, mobility, savings habits and many more. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4_4

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In certain situations, the microcredit has been used to meet family consumption and social compulsion rather than in income-generating activities. It helps to use helped smooth household consumption and reduced expenditure uncertainties. Furthermore, productive usage of credit amount possibly brings out optimistic changes like enhanced ability to spend, improved social status in household and beyond. Certain characteristics like better gender relation, social cohesion and solidarity among supportive women have been improved due to it. The true sense of empowerment can only be seen after the productive usage of loan amount.

4.2

Credit Utilization and MFI Beneficiaries: Literary Analysis

Microfinance institutions help to include the deprived sector of the society into the mainstream. One of the important contributions of MFI activities is to encourage people to use the credit amount productively and consequently helps to create employability. In the work of Christabel and Raj (2012), analysis of secondary data shows that a huge change occurs due to the SHG movement by MFIs in rural areas. MFIs help to overcome all the gaps like distance, poor infrastructure and telecommunications, heavy branch regulation, etc. and offer credit and credit plus services to overcome the lifestyle challenges. In line with this, Dev (2006) observes, “Microfinance institutions are having a major role for different vulnerable group and self-help group movement if the productivity of the borrowers is maintained with viable economic activities”. The credit and credit plus services of the MFIs are designed to harmonize the credit in the entire farm and non-farm sector. With a similar outcome, Al-Mamun et al. (2010) conduct a crosssection study through stratified random sampling method from states of Peninsular Malaysia (three). In this study, data have been collected from three branches of Amanah Ikhtiar Malaysia’s microcredit program located in the selected states. Here two groups have been selected on the basis of time frame with AIM: control group composed of new clients (duration was less than 24 months) and treatment group made up of

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old clients (between 48 to 72 months). By applying the Mann-Whitney test and Pearson’s chi-square test this study indicates, “Comparatively advanced percentage of total adult members (household) among old ones are advantageously employed and by both household and non-household members in their income-generating activities than that of new respondents. This clearly indicates that partaking in AIM’s microcredit program intensifies employment rate and opportunities in client’s households as well as at community level”. Another study by Mugabi, N. (2010) adopts cross-sectional research in Uganda and finds the different influencing elements and their influences like certain factors like perceptions and attitudes towards consuming microloans, the gender factor using microloans, borrower’s operational and organizational dimensions towards usage credit facilities and outcomes of credit usage on the well-being of the household, etc. By following both survey and ethnographic methods, the researcher finds that other poverty minimizing techniques do not have a huge impact on the financially excluded group. On the other hand, productive microloan procedure improves on the welfare of poor people along with their household members in general. Most interestingly, the effective credit utilization can impact the lives of farmers. A study by Idi et al. (2019) observes the impact of microloans on both beneficiaries and non-beneficiaries and who work as Farmer. They have used structured questionnaire, interview, etc. and engage descriptive statistics and PSM model to identify the influence of micro-credit usage on farmers. The study revealed significant impact of micro-credit usage on maize production and household food security of the beneficiary farmers. Along with the assistance of other infrastructural amenities, market facilities and governing bodies, the scenario can improve in future. In the line with that Dehingia et al. (2019), engage National Family Health Survey (2015–2016) data and assess indicators (three) about the utilization of maternal health service, receipt regarding four or more antenatal check-ups, institutional delivery and check-up (postnatal) among who had a child less than 5 years of age. The analysis reveals the significance of microcredit programs predominantly among poor women in refining health service consumption during and post-pregnancy.

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Societies with different norms sometimes regulate the population, their working ability and employability. With the hassle-free and convenient microloan and other supporting offerings of MFIs, borrowers especially the female counterpart of the society are able to gain confidence, use the credit amount into different setup which will generate income and employability. With the transition of time, this setup can further generate employment for the household and beyond and help others to come forward.

4.3

Observational Evidences Related to Credit Utilization by MFI Beneficiaries

4.3.1 Research Design To serve the purpose of the study, we follow a strong research methodology as discussed under the following points.

4.3.1.1 Data Types For the purpose of the study, primary data have been used which have been collected from the selected sample from the mentioned backward boroughs of West Bengal.

4.3.1.2 Sample Design The selected districts consider here are Purulia, Bankura and Paschim Medinipur with administrative subdivisions. Purulia is having four subdivisions (Sadar, Manbazar, Jhalda and Raghunathpur), Bankura is having three subdivisions (Bankura Sadar, Khatra and Bishnupur) and Paschim Medinipur is having three subdivisions (Medinipur Sadar, Kharagpur and Ghatal). First of all, from all the three districts, a total number of 600 respondents (200 respondents from each district) have been considered. Finally, out of the total collected sample, 450 borrowers i.e., having at least 150 respondents from each district (having at least

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37 samples from each subdivision relying on effective and free from biasness complete questionnaire) considered for analysis further. The respondents were surveyed to comprehend and analyze the bearing of productive credit usage on their livelihood. While selecting the respondents (borrowers only), those completed a minimum of one year of post-credit stage or continuing during survey are only considered for better impact tracking.

4.3.1.3 Data Collection Techniques Primary data have been gathered from the selected sample using multistage random sampling through a structured questionnaire with a reasonable and representative sample size. Multistage random sampling is proposed to be used to collect the data. It involves considering samples in stages by using smaller sampling units at every stage. It is a complex form of cluster sampling. In a multistage sampling technique, sampling is carried out dividing the large population into different stages to make the sample more representative. According to Sedgwick (2015), multistage sampling entails two or more phases of random sampling depending on the hierarchical structure of natural clusters within the inhabitants. It can be used in preference to simple random sampling where the population is geographically diverse.

4.3.1.4 Sample Size The total sample size is 450 (borrowers only) for this study covering three districts.

4.3.1.5 Statistical and Econometric Tests Used in the Study Along with descriptive statistics, various other statistical and econometric tests have also been incorporated in this study. To compare the credit utilization and income and consumption level change in the pre- and

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Table 4.1 Cronbach’s Alpha score Elements

Alpha score

Credit utilization

0.689

Source Calculated by authors

post-loan phase, t-test has been applied. It is one type of inferential statistics, and it has been used when here is a significant difference between the means of both of the factors.

4.3.1.6 Scheme of Investigation The course of the study is entirely designed on the basis of the formulated objectives. A blend of both open- and close-ended questionnaire was considered for analyzing the stated objectives of credit utilization of the respondents. To test the reliability, 30 samples pilot study has been executed. Considering Zikmund and Babin (2012), the pilot was intended at verifying the clarity of words, sentence categorization and their relevance. The Cronbach’s alpha for the different parameters is given in Table 4.1. Shelby (2011) says, “Alpha score above 0.60 is treated as good in social sciences”. So, in this exploration, the designed questionnaire is viewed as reliable as the Cronbach’s alpha scores are greater than 0.06 considering all the questionnaire. Further, to analyze the credit utilization towards income generation, both pre- and post-loan income and consumption level data have been analyzed. On the collected data, t-test has been implemented to see whether there exists any significant difference in these two phases.

4.3.2 Analysis A total of 450 respondents (borrowers) have been considered to check the credit utilization pattern (productive or unproductive) from the selected area. In this study, credit utilization (productively) embraces two areas—“income-generating determinations and education” whereas

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Fig. 4.1 Credit utilization pattern among the borrowers (Source Calculated by authors)

unproductive usage of credit encompasses five categories like “using the loan amount in family health purposes, festivals and social obligations, the redemption of old debt, family consumption and other miscellaneous purposes”. A structured questionnaire has been modified to collect relevant data with responses inclusive of both pre- and post-loan stage. Among the 450 respondents, 90% of the respondents utilize credit productively while 10% utilize it unproductively (Figs. 4.1 and 4.2). Among the productive purpose, 94% of the samples utilize credit for income generation while 6% utilize the credit amount for the purpose of education (Fig. 4.3). Basically, income-generating activities refer to the microenterprises initiated by MFI borrowers. In this segment, 53% respondents utilize the credit amount for animal husbandry, 21% utilize it for business purpose, 11% use it for cottage industry setup, 10% utilize it for agriculture-based microenterprise, 3% use it for service microenterprises and 2% utilize the loan amount for transportation-based microenterprises. Among the different categories of microenterprises of our study, major average income generated by the animal husbandry sector followed by

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Fig. 4.2 Productive utilization of credit patterns (Source Calculated by authors)

Fig. 4.3 Distribution of respondents among various categories of microenterprise (Source Calculated by authors)

“business, agriculture, cottage industries, service and transport-related microenterprises” (Fig. 4.4). Now, bearing in mind the objective of analyzing the borrower’s credit utilization towards income generation, we have collected pre-post data from 450 samples to comprehend if there exists any significant difference level in income. After collection of pre- and post-loan income, we have check it statistically to scrutinize difference in variance among two groups.

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Fig. 4.4 Average income earned by different categories of microenterprises (Source Calculated by authors)

In this context, first, we have applied F -test to check whether there is any significant difference in variance related to the pre- and post-income level of the respondent. From the F -test, it has been observed that there exists a significant difference in variance between the two selected groups. Considering the significant difference, we have applied t-test with an unequal variance to check the existence of mean difference, if any, in the pre- and post-loan phase income level. From the table, we can see that the calculated value of t statistics is greater than the critical value of t (p = 0.00321) at 5% significance level. The result specifies that a significant difference related to income level occurs in the pre- and post-loan chapter of the selected sample (Table 4.2). The result of the significant changes in the income level of the pre– post phase motivated us further to investigate their consumption pattern in the pre- and post-loan phase. To analyze the significant difference in the pre- and post-loan consumption level of the respondents, 450 sample Table 4.2 Result of F-test and t-test for pre- and post-income Pre-income Post-income

Mean

Variance

F-value

t-value

68,968 86,670.93

2.05E + 08 3.4E + 08

0.894062 (0.0000)

7.633 (0.00321)

Source Calculated by authors

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Table 4.3 Result of F-test and t-test for pre- and post-consumption level Pre-consumption Post-consumption

Mean

Variance

F-value

t-value

3790.01 6560.13

6.39E + 08 1.7E + 08

0.0685 (0.00313)

16.3387 (0.00732)

Source Calculated by authors

has been selected. After collecting the pre- and post-loan consumption expenditure statistical test has been applied to check whether there is a difference in variance between these two groups. Here the F -test has been conducted first to dissect whether any significant difference exists in the consumption level in pre-post phase and notice a significant difference in variance between the two selected groups. Considering this, further t-test has been applied with an unequal variance to discover the presence of mean difference, if any, among preand post-consumption level (Table 4.3). From the table, we can see that the calculated value of t statistics is greater than the critical value of t (p = 0.00732) at 5% significance level. The upshot indicates that a significant alteration exists in the pre- and post-credit point consumption level of the selected sample. Acknowledging that, the mean value of post-consumption level is superior than pre-loan consumption, and it reflects the increasing trend in household consumption due to access to microfinance institutions.

4.3.3 Findings Financial inclusion needs a supportive and sustainable environment to flourish. Credit and credit plus services along with various social responsibilities ensure the outreach and penetration of financial inclusion. Credit itself is one of the crucial instrument or improvement tool for the poor. In this study, both pre- and post-income and consumption scenario has been scanned for the selected 450 respondents to track down the impact of productive credit utilization, if any. Not only that, a detailed breakdown of respondents’ profile has also been taken place in terms of credit utilization, categories, average annual income, etc. It has been found that there is a positive influence of microloan usage on the betterment of livelihoods of the sample as well as her household.

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References Books, Journal, Research Paper, Working Papers, Reports etc. Al-Mamun, A., Wahab, S. A., & Malarvizhi, C. A. (2010). Examining the Effect of Microcredit on Employment in Peninsular Malaysia. Journal of Sustainable Development, 4 (2). https://doi.org/10.5539/jsd.v4n-2p174 Christabel, P., & Raj, V. (2012). Financial Inclusion in Rural India. IOSR Journal of Humanities and Social Science, 2(5), 21–25. Dehingia, N., Singh, A., Raj, A., & McDougal, L. (2019). More than Credit: Exploring Associations Between Microcredit Programs and Maternal and Reproductive Health Service Utilization in India. SSM-Population Health, 9 (3). https://doi.org/10.1016/j.ssmph.2019.100467 Dev, S. M. (2006). Financial Inclusion: Issues and Challenges. Economic and Political Weekly, 41(41), 4310–4313. Idi, A. S., Damisa, M. A., Ahmed, B., Edekhegregor, O. I., & Oladimeji, Y. U. (2019). Micro-credit Utilization and Its Impact on Famers Maize Output and Household Food Security in Kaduna State, Nigeria. Journal of Agriculture and Environment, 15 (1), 19–31. Mugabi, N. (2010). Micro-Credit Utilization and its Impact on Household Income: A Comparative Study of Rural and Urban Areas in Iganga District. Makerere University. Sedgwick, P. (2015). Multistage Sampling. Bmj. https://doi.org/10.1136/bmj. h4155. Shelby, L. B. (2011). Beyond Cronbach’s Alpha: Considering Confirmatory Factor Analysis and Segmentation. Human Dimensions of Wildlife, 16 (2), 142–148. Zikmund, W. G., Babin, B., Carr, J., & Griffin, M. (2012). Basic and Applied Research. Business Research Methods.

5 Microfinance and Employability

5.1

Introduction

The term employability resembles the opportunities of employment measures, engagement to certain pattern of job/s which in return confirms some monetary as well as non-monetary gains. This term is crucial for the development and sustainability of the market and economy. “India is widely known for enjoying its demographic dividend. With almost half of India’s current population (more than 1.2 billion people) under the age of 26 and the median age of the country projected to be 29 by 2020, India is making for the youngest country in the world”, says India Skills Report, 2020. So, to make the most of this phenomenon, the nation requires constant up-gradation towards capacity building or manpower skill advancement to keep balance between supply and demand. India is rural centric in nature so a huge population inhabit in rural vicinity. As compared to urban setup, rural areas lack different rudiments like the modern amenities, employment avenues, industrialization, etc. On top of that, females in rural backdrop with immense possibility lose their focus and potential due to lack of © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4_5

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consciousness and assistance. So the vicious cycle of poverty prolongs for a longer period of time. According to Mc.Kernan, 2002, “Microcredit programs provide a two-tiered approach to poverty alleviation: credit for the purchase of capital inputs in order to promote self-employment and non-credit services and incentives for better management of resources”. So, setting up microenterprises help to generate employment, accelerate income, savings and overall lead to the way to poverty alleviation.

5.2

Studies on Employability Through MFIs

The economic growth of any country is closely associated with the financial development (Jalilian et al., 2002). It is foreseeable that access to finance plays an essential role in the journey of lessen up the income inequality. Al-Mamun et al. (2010) mention, “It helps to boost up the income as well as the employability of the hardcore poor households across globe”. In a country like India, inclusion of finance is an immense assignment (Manjunath & Rao, 2015). Moreover, certain elements like transaction costs, financial illiteracy, fear of approaching formal financial institutions, lack of collateral, poor credit information, etc. act as obstacles or delaying the flow of inclusive growth (Gangopadhayay, 2009). From the very beginning, microfinance plays the role of poverty reduction tool across different economies (Rajbanshi et al., 2015). In his study in Bangladesh, Mia (2017) with the help of secondary data has observed that MFIs contributed a lot towards the development of socioeconomic as well as economic profile of the beneficiaries. But the regulatory framework needs to be more aligned. Further, majority of the constructive activities are confined to be urban setup so income and employment equality need to be well balanced. In another study of Hussain (2017) use 2000 household data to assess the possibility of employment generation through microfinance programme in Bangladesh. The household composed of both participant and non-participant in microfinance activities. The duration of

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their collected data is from 1998–2004. Both participants and nonparticipants participate through a questionnaire survey. The objective is to have a close encloser at operational and impact testing of different MFIs. By applying OLS methods, fixed effect regression technique, it has been found, “The effect of microcredit program participation on household self-employment working hours and labor income in Bangladesh is higher than the non-participants”. It is also been found in this paper that microcredit increases self-employment and motivate necessary conditions like working environment and entrepreneurial skill that are advantageous to self-employment activities. The upsurge in self-employment areas is deciphered into intensification is household labor income of participants. Another study observes that microfinance institutions and its offerings sometime able to generate opportunities more than self-employment. In their study on 168 clients and three distinct Islamic MFIs of Pakistan, Mahmood et al. (2016) have found, “Microcredit not only helps in promoting self-employment but also has positive impact on employment generation of a big class of people-family workers, community workers as well as of the family workers who has been migrated to another city. Therefore, it is concluded that the promotion of the Islamic microfinance can help in socioeconomic uplifting of the society by overcoming unemployment problem and poverty reduction of the target population and their associates”. Furthermore, Islamic microfinance is able to support poor and the unemployed to rectify the lifestyle pattern. Societies with different norms sometimes regulate the population, their working ability and employability. With the hassle-free and convenient microloan and other supporting offerings of MFIs, borrowers specially the female counterpart of the society are able to gain confidence, use the credit amount into different setup which will generate income and employability. With the transition of time, this setup can 76 further generate employment for the household and beyond and help others to come forward.

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Experiential Analysis of Employability Through MFIs

5.3.1 Research Design To track down the impact of microcredit on employability, multiple regression analysis has been used. It attempts to model the linkage between two or more explanatory variables and a response variable by fitting a linear equation to the observed data. Regression is used when relationships between two or more explanatory variables with an endogenous variable, whose value is to be predicted, and independent or explanatory variables, about which knowledge is available to have been examined. When the problem involves 2 or more explanatory variables, it is termed as multiple regressions. For analyzing the influence of microcredit considering employability, multiple regression analysis has been applied. Here accepted independent variables are “categories of microenterprise, duration and volume of credit”, and “employability” has been treated as dependent variable. After composing primary data, microenterprises have been alienated into broad categories of six which are “animal husbandry, business, agriculture based, cottage industries, service and transport-related microenterprises”. Considering on the average incremental income (annually) all the categories have been dispensed values ranging from 1 to 6. Duration of the microcredit stands for “the gap between day of taking credit from any MFIs and the day of survey has taken place”. Volume of borrowings stands for “the amount of loan one individual gets from the MFIs”. The employability has been calculated “with the number of total manpower engaged in a microenterprise, daily working hours and number of days work per week and converts the total number into monthly basis”. Now considering selective independent variables (category of microenterprise, duration and amount of borrowing) and dependent variable (employability) multiple regression analysis has been carried out to scrutinize the impact of microcredit on employment generation. Also, to track the pattern of credit utilizations along with the impact of microcredit on employability borrowers from the selected region have been observed through a structured questionnaire.

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5.3.2 Analysis In this context, detailed observation has been followed to determine the impact of microcredit in terms of employment generation. In order to determine the impact of microcredit, certain variables: category of microenterprise, duration and volume of credit (Alam, 2013) relating to microcredit have been considered as independent variables and employability as the dependent variable. This study has used multiple regression analysis to measure the impact of microcredit on employability. Table 5.1 shows the proportion of variance of the dependent variable explained by the independent variables (denoted by R 2 ). Here R is the multiple correlation coefficients between all the independent and dependent variables. In this model, the value is 0.850, which indicates that there is a positive covariance shared by the independent and dependent variables. The value R 2 is the proportion of variance explained by the given set of independent variables is 0.722. It indicates 72.2% of the variance of the dependent variable is explained by the independent variables which is also significant at 1% level of significance as the computed value of F statistics is higher than the table value. Further, the coefficients of two independent variables “category of microenterprise” as well as the “volume of credit” are significant at 1% level of significance. The finding draw the indication that “category of microenterprise” and “volume of credit” have a significant positive impact on the response variable, i.e., “employability generation of microenterprises” (Table 5.2). But duration of credit has no significant impact on the employability. The probable reason may be mentioned here that impact of microcredit Table 5.1 Result of regression analysis R

R2

Adjusted R2

Std. error of estimate

F-value

Significance level

0.850

0.722

0.730

133.83751

333.421

0.000

Notes Predictors (constant): category of microenterprise, duration of credit, volume of credit, *p‹ 0.05 Source Researchers own calculation

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Table 5.2 Result of coefficients for employability Independent variable

Coefficient

tvalue

Sig

Collinearity statistics

Constant Category of microenterprise Duration of credit Volume of credit

102.036 167.987

2.780 27.717

0.003 0.000

Tolerance 0.827

VIF 1.218

0.276 0.045

0.987 3.014

0.329 0.002

0.965 0.742

1.035 1.178

Source Calculated by researcher

can be better tracked when they uplifted to second loan cycle Copestake et al., (2001). In this study, majority of the borrowers are in their first loan cycle so duration has no significant impact on employability here. Also, majority of the microenterprises are initiated and organized by family members, working hours and volume of work are flexible, external manpower engagement is almost zero so in which category the borrowers along with her family member utilize the credit amount and the volume of credit plays the significant role. The regression equation mentioned below demonstrates that category of microenterprise and volumes of credit are both positively associated with employability, and the relationship is statistically significant at 1% level of significance. The regression equation is: Employability = 102.036+167.987 Cat+ 0.276 Dur + 0.045 Vol [Cat = Category of microenterprise; Dur = Duration of credit; Vol = Volume of credit].

5.3.3 Findings The result shows that the majority of the beneficiaries initiated different microenterprises like animal husbandry, agriculture-based setup, cottage industries, service setup, transportation-based services, etc. By utilizing their credit on various micro setup, they are able to have a better lifestyle, nutrition and health profile, fewer school dropouts, etc. in the research area. The respondents are able to upgrade their lifestyle if they utilise the credit amount properly with appropriate time and supportive working conditions. This result is reflecting the study of Dev (2006) and Hussain (2017).

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References Books, Journal, Research Paper, Working Papers, Reports etc. Alam, S. (2013). The Impact of Credit and Non-Credit Aspects on SelfEmployment Profit: A Comparison of Microcredit Programs and Commercial Lenders in Rural Bangladesh. The Journal of Developing Areas, 47 (1), 23–45. Al-Mamun, A., Wahab, S. A., & Malarvizhi, C. A. (2010). Examining the Effect of Microcredit on Employment in Peninsular Malaysia. Journal of Sustainable Development, 4 (2). https://doi.org/10.5539/jsd.v4n-2p174 Copestake, J., Bhalotra, S., & Johnson, S. (2001). Assessing the Impact of Microcredit: A Zambian Case Study. Journal of Development Studies, 37 (4), 81–100. Dev, S. M. (2006). Financial Inclusion: Issues and Challenges. Economic and Political Weekly, 41(41), 4310–4313. Gangopadhayay, S. (2009). How can Technology Facilitate Financial Inclusion in India? A Discussion Paper. Review of Market Integration, 1(2), 223–256. Hussain, A. K. M. (2017). Three Essays on the Impact Assessment of Microcredit Program Participation in Bangladesh Using Household Longitudinal Survey. Doctoral dissertation, University of Dhaka. Bangladesh. Jalilian, H., & Kirkpatrick, C. (2002). Financial Development and Poverty Reduction in Developing Countries. International Journal of Finance & Economics, 7 (2), 97–108. Mahmood, T., Arby, M. F., Hussain, T., & Sattar, A. (2016). Impact of Microfinance on Income Generation and Living Standards. Pakistan Economic and Social Review, 54 (1), 73–80. Manjunath, D., & Ramaprasada Rao, C. (2015). The Extent of Financial Exclusion and Financial Inclusion Initiatives in India. Adarsh Business Review, 2(1). Accessed on July 5, 2018. https://ssrn.com/abstract=2779178 Mia, M. A. (2017). An Overview of the Microfinance Sector in Bangladesh. The Journal of Business, Economics, and Environmental Studies, 7 (2), 31–38. Rajbanshi, R., Huang, M., & Wydick, B. (2015). Measuring Microfinance: Assessing the Conflict Between Practitioners and Researchers with Evidence from Nepal. World Development, 68, 30–47.

6 Performance Analysis of the Active MFIs

6.1

Introduction

Microfinance institutions have been served to the population who are at the verge of financial exclusion, lack development and growth in a sustainable manner. The charm of MFIs lies in its low-capital offerings, easy operational and repayment progression. Microfinance institutions are special financial institutions having both the profit and social welfare motive (Gutiérrez-Nieto et al., 2007). So, to analyze the performance and the role in financial inclusion of the active MFIs operated in the selected region a non-parametric linear programming method called Data Envelopment Analysis (DEA) has been painstaking. Farrell (1957) first proposed efficiency which shows “the ability of the firm to produce the existing level of output with the minimum inputs (Input-oriented) or to produce maximum possible output with a given set of inputs (output-oriented)”. The different MFIs have been referred here as DMUs in DEA measurement. As suggested by Golany and Roll (1989) and Drake and

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4_6

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Howcroft (1994), “DMUs number should be at least twice the total number of input and output factors”. Here, all the MFIs (Member of Association of Microfinance Institutions, West Bengal) which are operational in the West Bengal for at least last five years have been considered for efficiency measurement. Various input and output variables for five consecutive years (2016–2017 to 2020–2021) have been considered. Here DMU number is fifteen (selected fifteen MFIs), i.e., more than twice the number of input and output variables. The selection of inputs and outputs in the model was grounded on outreach and sustainability framework which support the financial inclusion activities. Here three input variables: Finance Cost, Employee Benefit Expenditure and Number of offices and three output variables: Operating Income, Other Income and Number of Active Borrowers (Berger & Humphrey, 1997; Dekker & Post, 2001; Desrochers & Lamberte, 2003; Ferdousi, 2013) have been selected considering the role of MFIs in financial inclusion.

6.2

Performance Evaluation of MFIs: Literary Review

From the very beginning, microfinance plays the role of poverty reduction tool across different economies (Rajbanshi et al., 2015). Different MFI’s goal achievement duration also dependent on the supply side of operations. There are quite a good number of researches on the performance measurement of microfinance institutions. The measurement technique may involve multiple approaches with different levels of considerations. “Most of the microfinance institutions are enjoying high loan repayment rate but that may not ensure high profitability”, propose Cull et al. (2006). The data are composed of 124 microfinance institutions (MFIs) in 49 developing countries taken from the Microfinance Information Exchange (or the MIX) (1999–2002) to analyze their performance. By applying a cross-country analysis MFIs from Eastern Europe, Central Asia, Sub-Saharan Africa (AFR), South Asian (SA) institutions, East Asia and the Pacific (EAP), Middle East and North Africa have been considered for performance analysis. By applying regression, it has been

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found in this paper that certain independent variables like raising interest rates, labor cost, etc. are allied with amended financial performance for individual-based lenders only but not for village banks or solidarity group lenders. Also, raising capital costs is inversely proportional to profitability for individual-based moneylenders but in case of village banks, these capital costs are allied with an even higher decline in profitability. In line with this, Berger and Humphrey (1997) conduct an analysis with 130 studies from 21 countries. Both parametric (Frontier efficiency) and non-parametric (Data Envelopment Analysis or DEA and Free Disposal Hull or FDH) can be used for efficiency measurement. In this paper, the result after applying five frontier analyses indicate that DEA and FDH studies are similar to frontier models but with relatively lower mean and greater dispersion than the results of the frontier models. Moreover, depending on the findings government regulations and policies have been taken care of for the improvement of financial institution sector. This context reflects the importance of considering correct methods for efficiency measurement. In contrast to that, Singh et al. (2014) conduct DEA to analyze the efficiency of selected MFIs. They have applied the output-oriented Constant Return to Scale DEA model with twenty Indian MFIs. Secondary data regarding three input and three output variables have been collected from MIX market database. The analysis indicates that three MFIs are efficient DMUs with insights about the improvement measures for the inefficient one. In line with that, Ferdousi 2013 mentions that based on DEA identification of MFIs is possible. In his study, he compares between MFIs active in Bangladesh, India and China. Along with efficiency measurement, he also applied Tobit regression analysis to identify the determinants of efficiency of the selected MFIs. Here, two input and two output variables have been used with different kind of MFIs based on their location, size, financial management and performance. The result indicates that MFIs in Bangladesh are comparatively more efficient than others. Also, the size of the MFIs and positive return on investment are considered to be an important determinant in terms of efficiency. Performance measurement is a basic part of the evaluation process of any organization. Based on the efficiency of microfinance institutions,

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operational and managerial activities can be modified and regulated; outreach issue can be taken care of and further formulation of policy also be taken care of.

6.3

Empirical Observation and Analysis of Operating MFIs Performance Evaluation

6.3.1 Research Design To serve the purpose of the study, we follow a strong research methodology as discussed under the following points.

6.3.2 Data Types For the purpose of the study, secondary data have been used. Secondary data have been collected from the annual reports available in websites of the operational MFIs in the mentioned backward districts of West Bengal.

6.3.3 Sample Design This study has been focused on the responsibility of microfinance institutions in financial inclusion. In West Bengal, total fifteen microfinance institutions inclusive of five MFIs active in the selected region (Purulia, Bankura and Paschim Medinipur) are operating for the last five consecutive years (2016–2017 to 2020–2021) (Table 6.1). So, all those institutions are considered for analysis along with five MFIs. As the performance of any MFIs is cumulative so we have considered Pan-India data for performance analysis. The overall performance evaluation further gives us an insight on the reality check of both supply and demand side of comparison in the BOP among the remote and backward province of West Bengal.

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Table 6.1 Active MFIs in West Bengal Sl. No.

Name of MFIs

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Asirvad Microfinance Limited Arohan Financial Services Limited Annapurna Microfinance Pvt Limited Ujjivan Financial Services Uttarayan Financial Services Pvt Ltd Sarala Women Welfare Society Satin Credit Care Network Limited Grameen Shakti Microfinance services Pvt Ltd Fusion Microfinance Private Limited Spandana Sphoorty Financial Limited Muthoot Microfin Limited Asa International India Microfinance Limited Bharat Financial Inclusion Limited Belghoria Janakalyan Samity (Bjs) Bandhan

Source Association of Microfinance Institutions

6.3.4 Data Collection Techniques Secondary data have been gathered from the selected MFIs official website. Starting from 2016–2017, selective data have been compiled for the consecutive five years from the annual reports of the selective MFIs. Considering the five years data of selective input and output variables (Finance Cost, Employee Benefit Expenditure, Number of offices, Operating Income, Other Income and Number of Active Borrowers), an average value of each variable has been considered for further analysis.

6.3.5 Statistical and Econometric Tests Used in the Study In order to analyze the performance efficiency of selective MFIs, Data Envelopment Analysis (DEA) has been applied.

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6.3.6 Analysis The details of the selected input and output variables are given below: Finance cost composed of interest expenses on borrowings and other, loan processing fees, bank charges and other related costs; employee benefit expenditure stands for all the tangible or intangible compensation given to employees apart from base wages or base salaries; number of offices stands for the total number of branches through which the microfinance activities are being operated; operating income composed of interest on loans, loan processing fees and other financial services; other income reflects incorporate items, such as interest from the company’s bank accounts, profit from the sale of a fixed asset; number of active borrowers means the number of entities who currently have an outstanding loan balance with the MFI or are liable for repaying any portion of the Loan Portfolio. The descriptive statistics of the selected input and output variables are given in Table 6.2. Table 6.3 summarizes the DEA result of selected fifteen DecisionMaking Units (DMUs). The input-oriented scores of efficiency of fifteen MFIs by applying CCR and BCC models have been represented here. The score indicates that three MFIs i.e., Satin Creditcare, BFIL and Spandana have the decreasing return to scale that indicates the DMUs while operating a proportional increase of all input variables produces a less than proportional increase in output towards a constant return to scale. The score also indicates the need for supervision to increase both managerial and operational efficiency for better returns. Further, the performance efficiency remains constant for Asirvad, Bandhan, Bjs and Muthoot which means in terms of operational and managerial functionally they are able to maintain their standard consistently for the selected time period. Apart from that, Annapurna, Arohan, Fushion, Grameen Shakti, Sarala, Ujjivan and Uttarayan reflect their improvement in terms of performance efficiency during the specified tenure. The overall majority of the MFIs is doing well and shows their efficiency which denotes the acceptance of these financial institutions in the different districts of West Bengal. Also beyond penetration, maximum of

3,47,29,804 18,88,18,71,388 1,09,60,10,560 637 3,22,67,28,727 2,98,34,11,463

No. of borrowers Operating income Other income Branches Finance cost Employee benefit expenditure

16,04,088 5,00,34,07,608 10,73,48,785 481 2,38,20,49,579 1,24,17,35,630

Median

Data Compiled from the Respective MFI’s Annual Reports (2016–2020) Source Calculated by authors

Mean

Descriptive statistics

Table 6.2 Descriptive statistics of selected input and output variables 37,49,56,200 79,63,80,47,997 10,85,51,02,260 2,847 18,32,42,22,659 12,30,20,42,846

Maximum

15,257 6,21,82,826 20,79,471 13 30,158 12,197

Minimum

102,997,566.4 29,183,340,624 2,962,262,784 745.7882074 4,993,722,711 4,015,012,765

SD

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Table 6.3 DEA analysis of MFIs under CCR and BCC model Sl. No.

MFIs

TE

PTE

SE

RTS

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Annapurna Arohan Asa Asirvad Bandhan Bjs Fusion Grameen Shakti Muthoot Sarala Satin Creditcare Spandana BFIL Ujjivan Uttarayan

0.427222 0.375465 0.040341 1 1 1 0.303918 0.313646 1 0.247792 0.351902 0.878751 0.159321 0.075269 0.583677

0.43117 0.376142 0.067044 1 1 1 0.305085 1 1 0.27405 0.385212 1 1 0.075782 0.643076

0.990844 0.998201 0.601717 1 1 1 0.996173 0.313646 1 0.904185 0.913529 0.878751 0.159321 0.993226 0.907633

Increasing Increasing Increasing Constant Constant Constant Increasing Increasing Constant Increasing Decreasing Decreasing Decreasing Increasing Increasing

Source Calculated by authors

these organizations are able to maintain or improve their efficiency which finally contributes to the financial inclusion movement of the state. Now considering our study area out of total fifteen MFIs, five are operational in three selected districts (Purulia, Bankura and Paschim Midnapore) of West Bengal. The active MFIs are Arohan, Asa India, Bandhan, BFIL and Ujjivan. Apart from one MFIs i.e., BFIL, other three MFIs are in a better position in terms of performance efficiency. Bandhan is having TE (Technical Efficiency) score 1 which means the MFIs are efficient and operating at most productive scale size and its SE (Scale Efficiency) is also 1 which represents the managerial efficiency of the selected institution.

6.3.7 Findings In West Bengal, numerous microfinance institutions (MFIs) have been established and have been operational towards undertaking the credit access problem of the underprivileged. In this study, the result depicts the performance level of the active MFIs in the specified area for the consecutive five years. The performance level of active MFIs is mostly

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following an increasing trend. The positive growth in accordance with the performance of the MFIs reflects the penetration and acceptability of it among the creditors. Cater to the needs of the rural and urban financially excluded population, microfinance institutions need to have financial and operational efficiency towards financial inclusion. Unless and until the MFIs are not efficient enough, they are not able to reach the remotest area and the people who still rely on unorganized financial market for lending.

References Books, Journal, Research Paper, Working Papers, Reports, etc. Berger, A. N., & Humphrey, D. B. (1997). Efficiency of Financial Institutions: International Survey and Directions for Future Research. European Journal of Operational Research, 98(2), 175–212. Cull, R., Davis, L. E., Lamoreaux, N. R., & Rosenthal, J. L. (2006). Historical Financing of Small-and Medium-Size Enterprises. Journal of Banking & Finance, 30 (11), 3017–3042. Dekker, D., & Post, T. (2001). A Quasi-Concave DEA Model with an Application for Bank Branch Performance Evaluation. European Journal of Operational Research, 132(2), 296–311. Desrochers, M., & Lamberte, M. (2003). Efficiency and expense preference in Philippines’ cooperative rural banks. CIRPEE Working Paper: 03–21. https://doi.org/10.2139/ssrn.382360. Drake, L., & Howcroft, B. (1994). Relative Efficiency in the Branch Network of a UK Bank: An Empirical Study. Omega, 22(1), 83–90. Farrell, M. J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society, Series A, 120 (III), 253–281. Ferdousi, F. (2013). Performance of Microfinance Institutions in Asia: DEA Based Efficiency Analysis. International Conference on the Modern Development of Humanities and Social Science (pp. 91–94). Atlantis Press. Golany, B., & Roll, Y. (1989). An Application Procedure for DEA. Omega, 17 (3), 237–250.

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Gutiérrez-Nieto, B., Serrano-Cinca, C., & Molinero, C. M. (2007). Microfinance Institutions and Efficiency. Omega, 35 (2), 131–142. Rajbanshi, R., Huang, M., & Wydick, B. (2015). Measuring Microfinance: Assessing the Conflict Between Practitioners and Researchers with Evidence from Nepal. World Development, 68, 30–47. Singh, C., Mittal, A., Garg, R., Goenka, A., Goud, R., Ram, K., Suresh, R. V., Chandrakar, R., Garg, R., & Kumar, U. (2014). Financial Inclusion in India: Select Issues (Working Paper No. 474). IIM Bangalore Research Paper.

7 Role of MFIs Towards Empowering the Women

7.1

Introduction

Financial inclusion becomes a necessity when the question of poverty slashing and growth in a sustainable manner appears. Financial inclusion not only ensures social development but it can ensure more sustainable positive consequences out of it. Md. Yunus believes that if the parameter of economic development covers the concern of equality, employability, minimization of poverty, improved physiological and mental well-being and so on, then it must affix women into its alleyway. The starting point of this may be ensuring the surrounding that can ensure free thinking, free mobility, power dynamics, safety, etc. In a summarized form, it may resemble to a breathing environment for all specifically for women. Empowerment has become an issue of international importance. No society can prosper without the empowerment ability of its population. But this concept of empowerment needs nurture and sustainability. It enriches slowly and able to change the attitude and ability of the general social order. It stretches the potential resources of the population. As per

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4_7

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Sustainable Development Goals (SDGs), gender sameness and empowerment are integral to overall development of economy. United Nations General Assembly (UN-GA) proposed Agenda 2030 where strive for empowerment and equality continues its journey globally. Economic, environmental and social imperatives craft sustainabilityoriented empowerment an irreplaceable phenomenon. Now the question arises why the issue of women empowerment attracts majority of the attention. There may be plentiful logic behind this but traditionally in a nation like India, women are mostly discriminated and deprived on a financial and economic growth constraint. On the top of that assurance of women empowerment brings out development for her entire household. In general, women prefer to spend for their family and household needs rather than for her personal purpose. Women are more of maker or creator. No one can rebuff the role of institutional efforts towards empowerment. That is the reason MFIs prefer to serve female that enhances the impact of organization’s activities.

7.2

Building Up Women Empowerment by the Offerings of MFIs: Bibliographic Review

There are plenty of works done on women empowerment. Now with the aim of measure empowerment, literature needs to be reassessed bearing in mind its related terms, data and thoughts sporadically. Jain and Jain (2015) conduct a survey on 100 respondents in Rajasthan, and by applying ANOVA, it has been found that there is a direct association between the access to microfinance institutions and poverty alleviation along with women empowerment. Nevertheless, he observes that “Social backwardness, indebtedness and presence of other microcredit programs in the same or nearby villages have a significant positive influence on women’s participation in the micro-financial program”. Similarly, in his work Khursheed (2022) mentions that MFIs are a critical tool to enlighten the female empowerment across the society. It

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helps to overcome the difficulties caused by poverty and its allied issues. In his study covering the rural Pakistan he tries to portray an investigative empirical analysis uncovering the linkage between MFIs, empowerment and entrepreneurship. Here engaging two techniques i.e., in-depth interview followed by focus group discussion, the findings out of all primary data establishes that MFIs are having a significant contribution in the society. But Gupta and Roy (2022) focus on the necessity of policy formulation intruding the empowerment, education and employment of females is the need of the hour. They survey over secondary data from National Family Health Survey and try to understand the decisionmaking ability of current married women from 15 to 49 years of age in India. Their study reveals that economic empowerment backed by other socio-economic variables has a prominent role in improving the decision-making ability of the women. It has been known that economic advancement and nation-building rest on the active engrossment of women in the workforce. The adverse situation during COVID gives a hard time in this context as the women entrepreneurial activity and income generation getting down. In their study, Wijerathne and Tharanga (2022) try to find out empowerment in pandemic in Sri Lanka inclusive of four independent factors viz. microcredit, micro-savings, micro-insurance, and training. The result finds that apart from micro-insurance, other independent variables have had a significant positive impact in this scenario. Empowerment is multifaced and according to Karl (1995) says it as, “A process of awareness, a way of capacity building, involves greater participation, decision making power, control and to transformative action”. Another study on 58 countries by Lopez-Claros and Zahidi (2005) measures female empowerment on the standard of five parameters comparing with their counterparts. Those parameters are “economic participation, economic opening, political empowerment, educational skill and health and comfort”. The analysis is being completed on the base of secondary data taken from executive opinion survey of World Economic Forum and established the information that nations that are unable to use the full potential of one-half of their societies are unsuccessful to use their human resources and added competitive potential.

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Also, alternatively common mode to determine women empowerment is to weigh by economic advance. As per Swain (2006), “Households have been influenced by SHGs in the matter of management, decision making, involvement, social and economic empowerment”. “Out of the various lending models, group lending system or Self-Help Groups (SHGs) are gaining popularity in India”, mentioned by Gwalani and Parkhi (2014). They also mention, “Group lending system is also recognized to have a significant impact on empowerment. They have been winding up the fact that efforts have been made to accomplish the goal but for a diversified nation like India it is essential to bring the basics first, and customize the models as per the requirement, thus, will direct to financial development in a country that will help to accelerate economic growth”. There are plentiful literatures that revolve around stating clarification related to empowerment from multitudinous dimensions. Twoempowerment contexts i.e., psychological and social can be hugely display disparity due to location factor. Garikipati’s (2008) observation in Andhra Pradesh’s drought-prone villages, “Female-only act as a medium of borrowing and utilize the credit in the unproductive movements of the family particularly to defeat the weather shock took place in the villages. The result shows the requirement for more reassess on the policymaking, focusing on the significance of social security program, conditional credit on the transfer of asset, etc.” Duflo (2012) mentions, “Close associations exist between economic development and women empowerment. When economic development occurs, women can involve themselves more in the decision-making procedures and are able to take good care of their children well-being. Both components reinforce each other even if it is not evident that it can fetch equality in terms of gender in society”. Two elements i.e., financial awareness and education are very crucial and needed for female empowerment. According to Hung et al. (2012), “It has been observed that females are less financially literate than men from the collected primary data of 12 countries. Inferior level of fiscal literacy discourages female counterpart of the society to dynamically take part in the economy. Now microfinance plays a position in the financial inclusion of the economy. A huge number of people who are financially excluded because of a variety of reasons may be incorporated in

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the formalized money market throughout microfinance which accelerates the greater prospect of female empowerment”. Shankar (2013) has addressed a field survey of a total 103 field officers engaged in various MFIs to check one key issue. She has been observed, “Microfinance can indeed break the barriers but in some restricted areas only. Reasons may be an insufficient operating system, lack of flexibility and profitability, etc.” Nagaraja (2013) entails powers into four edifices—“power over, power to, power with and power within”. He finds, “There is an urge to understand that the notions of empowerment and autonomy are adequately diverse. Again, it is also true that although not the women’s empowerment and autonomy have a relation with women’s entrance to resources or material well-being; it is to be acknowledged that there is an assortment of potential connections and there exist different forms of linkages among these variables”. In line with that, Kandpal et al. (2013) observe, “Women involvement rate in community development program boosts significantly by adding up features like access to employment, adult education, mobility, political membership, etc.”. This study has been backed by responses from 487 female of rural Uttarakhand (North India) and engaging snowball sampling method. Equally, Rathiranee and Semasinghe (2015) experience, “Empowerment of women throughout Self-Help Groups (SHGs) in Sri Lanka is significant in skill development, courage, confidence-building but there are no options in, sustainable rural development especially diminution of poverty, formation of employment and creation of assets in the rural areas. Further, their study incorporates primary data consists of 100 rural women respondents to recognize the influencing factors on female empowerment of rural area in Sri Lanka using direct personal interviews, judgment and convenience random sampling. Using an assortment of tools such as factor analysis, multiple regression analysis three factors namely decision making, liberty of mobility and family support seem to be positively attached with empowerment”. Further, Garikipati et al. (2017) observe the effectiveness of MFIs towards gender equality. Three areas have been chosen (empowerment through MFIs, level of gender discrimination and the influence of power) to shape the outcomes of microfinance activities. The study introspects the understanding about

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the reason to shape the outcomes of microfinance activities and should be included for further policy formulation. Andhra Pradesh has vital significance in the context of microfinance. Lakshmi et al. (2013) investigate MFI’s effect in both pre- and postcredit involvement phase relating to socio-economic empowerment in Krishna district’s ten selective mandals. After applying mean, standard deviation and paired t-test it has been observed that participation in SHGs contributes a lot towards various dimension of empowerment of the selected respondents. Another study by Kabeer (2012) reflects, “regular waged work has the greatest potential along with paid work outside the domestic domain on women’s lives” and also recommends, “A research schedule that focuses on constraints and preferences that establish gendered patterns of labor market outcomes, both in provisions of labor force involvement as well as the segmented nature of the occupational structure. Three sets of research questions turned around covering the issues of the specific barriers and obstacles to women’s mobility towards better jobs or transition to higher value-added enterprise”. Microfinance has an effect on female empowering women (Bali Swain and Yang Wallentin, 2014) but to mention economic empowerment (Buvinic and Furst-Nichols 2016; Rashid et al., 2015). Swain et al. (2014) establish, “In the southern parts of India empowerment of females takes place all the way through economic factors” on the ground of collected household data all over from five different states of India. Southern states that superior autonomy in decision-making acts as hindrance towards female empowerment. But Rashid et al. (2015) study, “economic empowerment co-relates with the services of Microfinance Institutions. But the respondent supported the information that only involvement in MFIs could not guarantee empowerment but due to the inclusion of advisory services, respondents are able to manage towards a better empowerment level”. On the other side, Buvinic and Furst-Nichols (2016) observe, “The parallel class of involvements has significantly different results in terms of economic empowerment relying on the client. The same kind of interventions (investment, skill training, job search assistance, etc.) would have a diverse impact on the different age group. Further, the social constraint is an essential issue to spot the empowerment level especially in the case of adult female borrowers”.

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But these aspects draw few criticisms about microfinance and its purposes in the empowerment progression (Ashraf et al., 2010; Asim, 2009). Asim (2009) founds, “Participation in microfinance activities may not always ensure empowerment but it may help in partial empowerment in the domains of household decisions like sale/purchasing of house, house repair, etc. where they are the least empowered, to begin with by conducting a survey on 275 households in the North-eastern regions of Lahore District and analyzed by using probit regression model”. But according to Ashraf et al. (2010), “There is also an argument over the role of microfinance in empowering women, rather empowerment can be better judged by the female decision-making power towards saving the product in the family. Here, considering a randomized controlled trial, it has been examined that whether access to and marketing of an individually-held commitment savings product direct to an enhancement in female decision-making power within the boundary of household with a positive impact, specifically for women who have below-median decision-making power in the baseline”. Rashid et al. (2015) find, “Microfinance has a significant and favourable impact on the economic status of women. But considering primary data from ten MFIs they also conclude that only participation in MFIs may not guarantee empowerment and incorporation of advisory services must be supplemented along with that”. We may comment that women empowerment is the most influential outcome of the financial inclusion program. Society’s development depends largely on gender equality. To make this happen MFIs are working actively to empower the female and help them to come forward into limelight. Besides the above literature studies of Piot-Lepetit and Nzongang (2014), Arora and Meenu (2012), Schuler et al. (1998), Panda (2009) and Rai and Ravi (2011) have a significant impact on financial inclusion, perception, credit utilization, employability and empowerment issue.

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In-depth Existential Analysis on Women Empowerment by MFIs Offerings

7.3.1 Research Design The research design for understanding the role of MFIs towards empowerment has been discussed below in details:

7.3.1.1 Data Types In the study, primary data have been used. Primary data have been collected from the selected respondents from three backward districts (Purulia, Bankura and Paschim Medinipur) of West Bengal.

7.3.1.2 Sample Design A total number of 450 borrowers were surveyed to understand and analyze the impact of MFIs towards empowerment. While selecting the respondents (borrowers only), those completed at best one year of post-credit stage or enduring the credit repayment rotation during the survey are only considered for better impact tracking. For the purpose of the study, 450 borrowers, having at least 150 respondents from each district (having at least 37 samples from each subdivision on the basis of bias-free effective and complete questionnaire), have been taken into contemplation for further analysis.

7.3.1.3 Data Collection Technique Primary data have been gathered from the selected sample using multistage random sampling through a structured questionnaire with a reasonable and representative sample size.

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7.3.1.4 Sample Size The total sample size is 450 considered specifically for tracking empowerment.

7.3.1.5 Study Period For this study, we have collected the required primary data from April 2021 to May 2022.

7.3.1.6 Description of Data In this work, three magnitudes have been considered for tracking empowerment of the respondent which are economic, psychological and social. We ponder if the sample is having “economical, psychological, and social’ (either anyone of this or every dimension)” of empowerment then it has been considering the sample as an empowered one. . Economic empowerment: It has been expressed by “financial contribution which has three specific areas- children education, health and family expenses. If the respondents contribute in all the three areas additionally in the post-loan phase, it has been given the weightage of “3”, similarly, for additional contribution to any two fields “2”, for additional contribution in any one field coding of “1” and for no additional contribution in the post-loan phase “0” weightage has been assigned. Economic empowerment can be influenced by a lot of factors, but here the study consider own asset (Asset), controlling of resources (Control), self-employment (Self ), enhancing savings (Savings), access to bank/ post office (Account), reason for borrowing (Borrow), knowing the procedure to access banking/ post office services (Procedure), poverty reduction (Poverty), buying certain assets: two-wheelers, furniture, television (TV), brick home, sanitation and gas connectivity to determine economic empowerment” (Duflo, 2012; Lakshmi & Vasantha, 2013).

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. Social empowerment: Now this term is measured by “additional awareness on the social activities in the post-loan phase. It has two elements having the weightage of ‘1’ for yes and ‘0’ for no. Among the various influencing factors of social empowerment, here we consider awareness about children’s education (School), number of dropouts (Dropout), examinations of children’s held every year (Exam.no.), exercise of voting power (Vote), political awareness (Pol), participating in social campaign (Social), awareness about the minimum age of marriage (Min.age), awareness about the sources of loan (Source of loan) and the age when the respondent got married (Age)” (Hashemi et al., 1996; Kandpal et al., 2013). . Psychological empowerment: This terminology is measured by “participation in decision making, which has four sub-areas: children marriage, family savings, asset purchase and a visit to the maternal house/relatives. If any respondents show enhanced participation in all the four areas in the post-loan phase the weightage is being awarded as “4”, for improved participation in any three areas it would be “3”, for increased participation in any two areas it would be “2”, for any increased participation in any one area it would be “1” and for no improvement in level of participation in the post-loan phase the weightage has been awarded as “0”. With the context to psychological empowerment, the influencing factors are “access to mobile (Mobile), free communication with others (Free comm), able to express opinion freely outside (Express), able to take decisions on purchasing small items (Small items), able to visit financial institutions or offices alone (Alone visit), rely for health (Health), decider for family issues (Decider), decision-making ability for outside the household (Dec), recommendation power (Recom), skill development (Skill dev) and peaceful family life (Family)” (Ashraf et al., 2010; Rathiranee & Semasinghe, 2015; Sarumathi & Mohan, 2011). In this study, for all the explanatory variables, the weightage of “1” has been assigned if the post-loan phase response is positive and better in comparison with the pre-loan phase response, otherwise it has been assigned as “0”.

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7.3.2 Analysis To find out MFI-based financial inclusion or more precisely the activities of MFIs are capable of empowering women “economically, psychologically and socially”, a survey has been taken place covering 450 respondents. All the respondents are women borrower, living below the poverty line, having at least one child and be located in within the selected region for this study. Data collection covers both pre- and postloan phase scenario for tracking the impact of MFIs on the sample. Depending on the additional contribution/participation in the post-loan phase, all the responses have been coded as either 0, 1, 2, 3 in case of economic empowerment or as 6, 5, 4, 3, 2, 1 or 0 in case of psychological empowerment and 0 or 1 in case of social empowerment. If any respondents are not able to contribute, unaware or not able to possess anything in pre-loan phase, it is coded as “0” and similar areas can be handled in the post-loan phase is coded as “1”. To track down the impact of MFIs on empowerment, this study considered the pre- and post-loan chapter data of each dimension. To observe if there any significant difference exists in the “pre- and post-loan phase” of the economic empowerment level of the respondents, we have applied F -test in the first stage, and the result did not prove to be statistically significant. Keeping the equal variance in mind, in the next stage we have applied t-test to scrutinize the presence of mean difference, if any. From the table, we can see that calculated value of t statistics is greater than the critical value of t (p = 0.0000) at 1% significance level, and the mean of post-loan phase economic empowerment was higher than the pre-loan phase. It designates a snowballing trend in the direction of economic empowerment of the borrowers. While considering the psychological empowerment, we have applied F -test initially. The result indicates a significant difference in variance among the two phases. Considering this, t-test has been applied with an unequal variance to confirm the mean difference, if any, among pre-post period. From the table, we can see that calculated value of t statistics is greater than the critical value of t (p = 0.0000) at 1% significance level and the mean of post-loan phase psychological empowerment was higher

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than the pre-loan phase. It specifies an snowballing trend on the road to psychological empowerment of the borrowers here. In the next, we have considered social empowerment, and in this case, the F -test result did not prove to be statistically significant. Keeping the equal variance in mind, we have applied t-test to investigate the existence of mean difference, if any, in the empowerment level of pre- and postloan phase. From the table, we can see that calculated value of t statistics is greater than the critical value of t (p = 0.0000) at 1 significant significance level and the mean of post-loan phase social empowerment was higher than the pre-loan phase. It specifies an cumulative tendency on the way to social empowerment of the respondents here. Considering the below-mentioned result, it can be concluded that MFIs are capable of empower women economically, psychologically and socially (Tables 7.1, 7.2 and 7.3). Table 7.1 Result of F-test and t-test for economic empowerment of the borrowers Pre-loan phase Post-loan phase

Mean

Variance

F-value

t-value

0.392 2.232

0.266 0.512

0.908 (1.0883E–09)

39.021 (1.656)

() indicate the probability values Source Calculated by Researcher

Table 7.2 Result of F-test and t-test for psychological empowerment of the borrowers Pre-loan phase Post-loan phase

Mean

Variance

F-value

t-value

1.209 3.228

0.172 0.113

0.637 (6.565E–07)

30.725 (0.001)

() indicate the probability values Source Calculated by Researcher

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Table 7.3 Result of F-test and t-test for social empowerment of the borrowers Pre-loan phase Post-loan phase

Mean

Variance

F-value

t-value

0.313 0.758

0.215 0.184

0.855 (0.050965)

14.080 (2.37E–40)

() indicate the probability values Source Calculated by Researcher

7.3.3 Findings One of the major objectives of the MFI program is to enhance the level of female empowerment level. As empowerment itself is a self-explanatory qualitative term, it can be checked and explained with different parameters. In this study, MFIs role on women empowerment has been analyzed using t-test considering empowerment level in the pre- and post-loan phase of the respondents. All the contributing variables which constitute the dimensions of economic, psychological and social empowerment has been analyzed in both pre- and post-loan phase. Women empowerment has been analyzed from three dimensions over here: economic, psychological and social. It has been observed that sustainable functioning of MFIs and borrowing from the said institution help the women borrower to be better empowered in all three dimensions. The reason behind this is by participating in group-based lending system the borrowers gradually acquire series of interdependent positive consequences. It may be grasping confidence, acquire professionalism through training programs of MFIs, augment participation in decision making progression etc. Moreover, peer pressure motivate them towards savings and supporting environment help them to initiate income generating activities, financial literacy increase, dependency on private money lenders decrease etc.

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References Books, Journal, Research Paper, Working Papers, Reports, Etc. Arora, S., & Meenu. (2012). The Banking Sector Intervention in the Microfinance World: A Study of Bankers’ Perception and Outreach to Rural Microfinance in India with Special Reference to the State of Punjab. Development in Practice, 22(7), 991–1005. Ashraf, N., Karlan, D., & Yin, W. (2010). Female Empowerment: Impact of a Commitment Savings Product in the Philippines. World Development, 38(3), 333–344. Asim, S. (2009). Evaluating the Impact of Microcredit on Women’s Empowerment in Pakistan. Lahore School of Economics. Centre for Research in Economics and Business (CREB). Pakistan. Bali Swain, R., & Yang Wallentin, F. (2014). The Impact of Microfinance on Factors Empowering Women: Regional and Delivery Mechanisms in India’s SHG Programme. Working Paper no- 492. Stanford University. Buvinic, M., & Furst-Nichols, R. (2016). Promoting Women’s Economic Empowerment: What works?. The World Bank Research Observer, 31(1), 59–101. Duflo, E. (2012). Women Empowerment and Economic Development. Journal of Economic Literature, 50 (4), 1051–1079. Garikipati, S. (2008). The Impact of Lending to Women on Household Vulnerability and Women’s Empowerment: Evidence from India. World Development, 36 (12), 2620–2642. Garikipati, S., Johnson, S., Guérin, I., & Szafarz, A. (2017). Microfinance and Gender: Issues, Challenges and the Road Ahead. The Journal of Development Studies, 53(5), 641–648. Gupta, I., & Roy, A. (2022). What Really Empowers Women? Taking Another Look at Economic Empowerment. Journal of Social and Economic Development. https://doi.org/10.1007/s40847-022-00215-y Gwalani, H., & Parkhi, S. (2014). Financial Inclusion-Building a Success Model in the Indian context. Procedia-Social and Behavioral Sciences, 133, 372–378. Hashemi, S., Schuler, S., & Riley, A. (1996). Rural Credit Programs and Women Empowerment in Bangladesh. World Development, 24 (4), 635–654.

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Hung, A., Yoong, J., & Brown, E. (2012). Empowering Women through Financial Awareness and Education (Working Papers on Finance, Insurance and Private Pensions no-14). OECD Publication. Jain, D., & Jain, B. (2015). Does Microfinance Empower Rural Women? An Empirical Study in Udaipur District. Rajasthan Researchers World Journal of Arts, Science and Commerce, 3(1), 76–89. Kabeer, N. (2012). Women’s Economic Empowerment and Inclusive Growth: Labour Markets and Enterprise Development. International Development Research Centre, 44 (10), 1–70. Kandpal, E., Baylis, K., & Arends-Kuenning, M. (2013). Measuring the Effect of a Community-Level Program on Women’s Empowerment Outcomes: Evidence from India. The World Bank. Karl, M. (1995). Women and Empowerment: Participation and Decision Making (Vol. 10). Zed Books. Khursheed, A. (2022). Exploring the Role of Microfinance in Women’s Empowerment and Entrepreneurial Development: A Qualitative Study. Future Business Journal. https://doi.org/10.1186/s43093-02200172-2 Lakshmi, K., & Vasantha, S. (2013). Microfinance Crisis in Andhra Pradesh and Regulatory Response. CLEAR International Journal of Research in Commerce & Management, 4 (12), 32–36. Lakshmi, P. A., Jampala, R. C., Kishore, O., & Dokku, S. R. (2013). The Role of Micro Finance in the Empowerment of Women-An Empirical Study with Special Reference to Krishna District, Andhra Pradesh. Journal of Contemporary Research in Management, 8(3), 25. Lopez-Claros, A., & Zahidi, S. (2005, May). Women Empowerment: Measuring the Global Gender Gap. Geneva Switzerland World Economic Forum 2005. Nagaraja, B. (2013). Empowerment of Women in India: A Critical Analysis. Journal of Humanities and Social Science (IOSR-JHSS), 9 (2), 45–52. Panda, D. K. (2009). Assessing the Impact of Participation in Women SelfHelp Group-Based Microfinance: Non-Experimental Evidences from Rural Households in India. International Journal of Rural Management, 5 (2), 197– 215. Piot-Lepetit, I., & Nzongang, J. (2014). Financial Sustainability and Poverty Outreach within a Network of Village Banks in Cameroon: A Multi-DEA Approach. European Journal of Operational Research, 234 (1), 319–330. Rai, A., & Ravi, S. (2011). Do Spouses Make Claims? Empowerment and Microfinance in India. World Development, 39 (6), 913–921.

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Rashid, F., John, M., Consolatta, N., & Stephen, S. (2015). Impact of Microfinance Institutions on Economic Empowerment of Women Entrepreneurs in Developing Countries. International Journal of Management Science and Business Administration, 1(10), 45–55. Rathiranee, Y., & Semasinghe, D. M. (2015). Factors Determining the Women Empowerment Through Microfinance: An Empirical Study in Sri Lanka. World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 9 (5), 1595–1599. Sarumathi, S., & Mohan, K. (2011). Role of Micro Finance in Women’s Empowerment: An Empirical Study in Pondicherry Region Rural SHG’s. Journal of Management and Science, 1(1), 1–10. Schuler, S. R., Hashemi, S. M., & Badal, S. H. (1998). Men’s Violence Against Women in Rural Bangladesh: Undermined or Exacerbated by Microcredit Programmes? Development in Practice, 8(2), 148–157. Shankar, S. (2013). Financial Inclusion in India: Do Microfinance Institutions Address Access Barriers. ACRN Journal of Entrepreneurship Perspectives, 2(1), 60–74. Swain, B. R. (2006). Microfinance and Women Empowerment. Swedish International Development Corporation Agency. Wijerathne, B. G. D. N. D., & Tharanga, B. B. (2022). ARSYM (pp. 181– 184). Faculty of Business Studies and Finance, Wayamba University. Sri Lanka.

8 Identification of Determinants Influencing the Economic, Psychological and Social Empowerment of the Female Borrowers

8.1

Introduction

Poverty is much widespread issue of our country. To be in a sustainable growth plateau, one of the main challenges caused by poverty needs immediate concern and cure. It has been known that infrastructural issues, risk components and profitability hinder the penetration of formal financial institution in remote. On the contrary, microfinance covers it all. It supplements the feelings of economic liberty among the deprived population. Females with high economic liberty have more bargaining power (Eggers del Campo & Steinert, 2022) and improved decision-making capacity (Sharma et al., 2020). The pecuniary liberty enlightens further and add-on different subtleties of empowerment gradually. This notion adds more weightage and relevancy to the concept of empowerment. Women empowerment has become an essential axiom in and around growth and development of any society. This is equally relevant for developed nations as the challenges towards attaining empowerment get restructured or reshaped along with time and context. The credit disbursed by MFIs acts as a functional initiator to create series of effects © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4_8

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to enhance beneficiaries’ overall progression. Discrimination on the basis of gender is a much-discussed topic now but the solution or extinct of this issue still remain unreached. MFIs are endowed with novelty to the notion of sustainability of empowerment. In order to catalog the determinants of diverse dimensions of empowerment (economic, psychological and social), the selected respondents must be a female borrower, living below the poverty line, with at least one child and reside within the selected region for this study.

8.2

Economic, Psychological and Social Empowerment of the Female: Literary Study

The determining factors of different kinds of empowerment vary with assortments of elements. It depends on the socio-cultural as well as other locational issues too along with other subsidiaries. Further, a new insight has been explored by Weber and Ahmad (2014) that the level of empowerment is equally proportionate to the duration of loan cycle. A study on beneficiaries of a Pakistani microfinance shows the decision of taking loan and mobility act as the indicator of empowerment and those who are in higher loan cycle exercise these activities well and good. In an interesting study by Cinar and Kose (2018), women empowerment has been observed in Turkey. It is a Muslim-driven country but with progressive mindset for female. In their paper, they develop “an index of women self-perceived empowerment”. Parameters like “health, education, income, social life, and personal care” have taken into consideration in the index. It has been observed by them that despite of different liberal attitude Turkish women suffer shortcoming in empowerment. With the multilevel analysis, it has been found that “higher levels of education, religiosity, and income level are determinants with women’s empowerment at individual level”. According to Anggadwita and Ramadani (2021), not only environment but socio-cultural environment and social perception have a widespread role on the women entrepreneurs in Indonesia. These

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entrepreneurs are engaged in micro, small and medium sized creativities. Socio-cultural environment and social perception support to engulf the entrepreneurial orientation of the respondents. Gradually, it enhances the social empowerment level of the beneficiaries. A study by Rai and Shrivastava (2021) reveals that empowerment variations and determinants can be different in the same society. In their study by applying factor analysis and structural equation modeling, they observe that the members of SHGs are more socially empowered while the non-SHG members who have availed microfinance services are more economically and psychologically empowered. In this paper, the key determinants are family size which determine the types and extent of empowerment among the respondents. In a country like India, government also plays a vital role to bring about changes in the empowerment level of the female counterpart of the society. A study by Sahu et al. (2021) has been seen that government initiative like Pradhan Mantri Mudra Yojana (PMMY) provides all the necessary support towards attaining women employment. Independent women slowly and steadily prosper in the domain of psychological, social and economic empowered zone. In addition to that, education can be an important determinant of economic advancement, upgrading in family matters, decision to use public services and political empowerment (Aggarwal et al., 2020), giving birth to first child as son create opportunities for empowerment for women in a patriarchy society (Saha & Sangwan, 2019).

8.3

Descriptive and Analytical Framework on Beneficiaries’ Economic, Psychological and Social Empowerment

8.3.1 Research Design The research design for understanding the determinants influencing the economic, psychological and social empowerment related to the female borrowers has been discussed below in details:

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8.3.1.1 Data Types In the exploration, the primary data have been poised from the selected respondents from three backward districts (“Purulia, Bankura and Paschim Medinipur”) of West Bengal.

8.3.1.2 Sample Design A total number of 450 borrowers were surveyed to understand the determinants to detect three magnitudes of empowerment i.e., economic, social and psychological. The respondent must have crossed at least one year post-credit segment in order to track the determinants clearly.

8.3.1.3 Data Collection Technique Primary data have been gathered from the selected sample using multistage random sampling through a structured questionnaire with a reasonable and representative sample size.

8.3.1.4 Sample Size The sample size in total is 450 considered specifically for tracking empowerment.

8.3.1.5 Study Period For this study, we have collected the required primary data from August 2021 to May 2022.

8.3.1.6 Description of Data Here, three dimensions resemble empowerment—“economic, psychological and social”. We ponder if the sample is partaking economical,

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psychological and social (anyone of this or every dimension) of empowerment, then it has been considering the sample as an empowered one. . Economic empowerment: The economic empowerment has been enumerated by financial contribution which has three specific areas— children education, health and family expenses. If the respondents contribute in all the three areas additionally in the post-loan phase, it has been given the weightage of “3”, similarly, for additional contribution to any two fields “2”, for additional contribution in any one field coding of “1” and for no additional contribution in the post-loan phase “0” weightage has been assigned. Economic empowerment can be influenced by a lot of factors, but here the study consider own asset (Asset), controlling of resources (Control), self-employment (Self ), enhancing savings (Savings), access to bank/post office (Account), reason for borrowing (Borrow), knowing the procedure to access banking/post office services (Procedure), poverty reduction (Poverty), buying certain assets: two-wheelers, furniture, television (TV), brick home, sanitation and gas connectivity to determine economic empowerment (Duflo, 2012; Lakshmi & Vasantha, 2013). . Social empowerment: Social empowerment is designated by “additional awareness on the social activities during post lend chapter”. It entails of two elements having the weightage of “1” for yes and “0” for no. Among the innumerable influencing facets of social empowerment, here we consider “awareness about children’s education (School), number of dropouts (Dropout), examinations of children’s held every year (Exam.no.), exercise of voting power (Vote), political awareness (Pol), participating in social campaign (Social), awareness about the minimum age of marriage (Min.age), awareness about the sources of loan (Source of loan) and the age when the respondent got married (Age)” (Hashemi et al., 1996; Kandpal et al., 2013). . Psychological empowerment: Psychological empowerment is measured by “participation in decision making, which has four sub-areas: children marriage, family savings, asset purchase and a visit to the maternal house/relatives”. If any respondents show boosted partaking in all the areas (four) in the post-loan chapter, the value is being

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awarded as “4”, for upgraded partaking in any three areas it scored “3”, for increased partaking in any two extents it would be “2”, for any changed participation in any one area it would be valued as “1” and for no enrichment in level of partaking in the post-loan chapter the weightage has been awarded as “0”. With the milieu to psychological empowerment, the influencing factors are “access to mobile (Mobile), free communication with others (Free comm), able to express opinion freely outside (Express), able to take decisions on purchasing small items (Small items), able to visit financial institutions or offices alone (Alone visit), rely for health (Health), decider for family issues (Decider), decision-making ability for outside the household (Dec), recommendation power (Recom), skill development (Skill dev) and peaceful family life (Family)” (Ashraf et al., 2010; Rathiranee & Semisinghe, 2015; Sarumathi & Mohan, 2011). In this study, for all the explanatory variables the weightage of “1” has been assigned if the post-loan phase response is positive and better in comparison with the pre-loan phase response, otherwise it has been assigned as “0”.

8.3.2 Analysis 8.3.2.1 Economic Empowerment In order to identify the influencing variable towards empowering economically of female borrowers, seven independent variables have been considered here. The dependent variable (contribution) is having three categories depending on the ability to contribute (1, 2, 3). In case of the post-loan phase, if the sample is able to contribute additionally to three areas (education, family expenses and health), it has been coded as 3, again if she is able to additionally contribute to two areas (either education, family expenses or health), it has been coded as 2 and likewise coding of 1 has been done (able to contribute to any one area). If the pretenders are not able to additionally contribute to any area in the postloan chapter, it has been coded as 0. As the dependent variable is having three levels so ordered logistic regression method has been engaged.

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Table 8.1 Percentage of contribution of the respondents Contribution

Frequency

Ability to contribute additionally to any of the areas like education, family expenses and health (1) Ability to contribute additionally to any two areas either in education or family expenses or health (2) Ability to contribute additionally to education, family expenses and health (3) Total

16

Percent 3.55

159

35.33

275

61.11

450

100.00

Source Calculated by Authors

From Table 8.1, we have found that 61% respondents can contribute to all three areas mentioned above in the post-loan chapter, 35% are able to contribute to any two areas and only 4% are able to contribute to any one of the areas in the post-loan phase. For the sake of finding out the determinants of economic empowerment, 7 explanatory variables have been engaged in the ordered logistic regression model and upshot summarized in Table 8.2. The fallouts indicate that out of the total 7 variables 5 have a significant stimulus on women economic empowerment. The significant explanatory variables are “decision-taking on controlling of resources, self-employment, help to increase savings, having active bank or post office and having own asset” which is found to be significant at 95% confidence level.

8.3.2.2 Psychological Empowerment To find out the contributing factor towards psychological empowerment of the respondents, seven independent variables have been incorporated in the analysis. Here, the dependent variable (decision making) is having six categories depending on the additional participation in the decision making of various categories (1, 2, 3, 4, 5 and 6) in the post-loan phase. In post-loan phase, if the sample is able to additionally participate in all the areas (“daughter/son’s marriage, family savings, asset purchase, visit to maternal house, house repair and access credit facility”), it has been coded as 6, likewise if she is able to additionally participate to any

Source Calculated by Authors

3.641 1.784 2.265 0.320 2.567 2.577 0.411

1.140 0.536 0.784 0.170 1.290 2.197 0.873

4.13 1.93 2.36 –2.14 1.88 1.11 2.64

0.000 0.048 0.018 0.331 0.045 0.267 0.008

1.292 0.579 0.818 –1.137 0.947 0.947 1.458

–0.032 –0.005 –0.022 0.017 –0.021 0.009 0.049

Y = Pr(1) = 0.206 –0.231 –0.056 –0.180 0.201 –0.186 –0.164 0.324

Y = Pr(2) = 0.349

Marginal effects

Control Self Savings Access Active Procedure Ownasset

Z

P >z

Stand error

Coefficient

Contribution

Odds ratio

LR chi2 (7) = 83.81 Prob > chi2 = 0.0000 Log-likelihood = −272.149 Pseudo R2 = 0.133

Method: Ordered Logistic Regression Number of obs = 450 Dependent variable: contribution of the borrower (1 = any one area, 2 = any two areas, 3 = any 3 areas and 0 = no contribution) Mean of the dependent variable = 2.578

Table 8.2 Determinants of economic empowerment

0.263 0.062 0.203 -0.218 0.207 0.185 –0.373

Y = Pr(3) = 0.629

0.825 0.765 0.833 0.705 0.66 0.935 0.273

Mean of the variable

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Table 8.3 Percentage of participation in decision making Decision making

Frequency

Percent

Not able to make decisions additionally in either of daughter/son’s marriage, family savings, asset purchase, visit to maternal house, house repair and access credit facility (0) Able to make decisions additionally in either any one of the areas (1) Able to make decisions additionally in either any two of the areas (2) Able to make decisions additionally in either any three of the areas (3) Able to make decisions additionally in either any four of the areas (4) Able to make decisions additionally in either any five of the areas (5) Able to make decisions additionally in all the areas (6) Total

27

6

17

3.77

48

10.66

63

15.75

194

43.11

14

3.00

87

19.25

450

100.00

Source Calculated by Authors

five areas mentioned above, it has been coded as 5 and likewise coding towards 4, 3, 2 and 1 has been awarded. If the respondent is unable to additionally participate in the decisionmaking process regarding any of the above-mentioned areas, it has been coded as 0. As the dependent variable is having seven levels so ordered logistic regression method has been applied. From Table 8.3, we may comment that in the post-loan phase, 19.25% respondents can participate in all the areas mentioned above, 3% are able to additional participation in the post-loan phase to any five areas, 42.7% are able to participate in any four areas, 15.75% participate in any three areas, 10.25% participate in any two areas and only 3.25% are able to contribute to any one of the areas. Also, 5.75% of respondents is not able to add participate in any of the decision-making areas. To reconnoiter the determinants of psychological empowerment, 7 explanatory variables have been designated in the ordered logistic regression model and result condensed in Table 8.4. The result presented in the table indicates that among the total 7 explanatory variables 6 have a

Y = Pr(1) = 0.026

−0.026 0.019 −0.052 −0.013 −0.015 −0.019 −0.031

Y = Pr(0) = 0.044

−0.052 0.033 −0.115 −0.024 −0.028 −0.034 −0.064

Marginal effects

Source Calculated by Authors

Awareness Mobile Freecomm Express Dec Visitalone Smallitems

Participation

0.895 −1.239 1.487 0.628 0.734 1.158 1.083

Awareness Mobile Freecomm Express Dec Visitalone Smallitems

LR chi2 (7) = 62.82 Prob > chi2 = 0.0000 Log-likelihood = −602.924 Pseudo R2 = 0.049

Coefficient

Participation

−0.068 0.061 −0.116 −0.040 −0.046 −0.061 −0.082

Y = Pr(2) = 0.088

2.448 0.289 4.424 0.534 0.480 0.314 2.953

−0.063 0.092 −0.072 −0.051 −0.059 −0.089 −0.074

Y = Pr(3) = 0.153

Odds ratio

0.088 0.056 0.188 0.019 0.018 −0.029 0.107

Y = Pr(4) = 0.477

0.281 0.599 0.479 0.292 0.282 0.437 0.330

0.016 −0.020 0.023 0.012 0.014 0.020 0.019

Y = Pr(5) = 0.032

Standard error

0.105 −0.241 0.142 0.098 0.116 0.214 0.126

Y = Pr(6) = 0.175

3.19 −2.07 3.10 2.15 2.60 2.65 3.28

Z

Method: Ordered Logistic Regression Number of obs = 450 Dependent variable: participation in the decision making (1 = any one area, 2 = any two areas, 3 = any 3 areas, 4 = any 4 areas, 5 = any 5 areas, 6 = any 6 areas and 0 = no participation) Mean of the dependent variable = 3.725

Table 8.4 Determinants of psychological empowerment

0.848 0.95 0.918 0.688 0.7 0.878 0.805

Mean of the variable

0.001 0.390 0.002 0.032 0.009 0.008 0.001

P >z

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significant influence on women psychological empowerment. The significant explanatory variables are “awareness about current affairs, speak with outsiders, able to express her opinion freely outside, able to take decision outside the household, alone visit government offices/banks and purchasing small items” are statistically significant to the level of empowerment of the respondents which are found to be significant at 0.05% level.

8.3.2.3 Social Empowerment Finally, to locate the influencing elements towards social empowerment of the selected respondents, eight explanatory variables have been considered in the study. The dependent variable (participation in social protest/ awareness) is having two categories (1 and 0). In case if the respondent is able to participate during the post-loan phase in any social awareness or social protest program, it has been coded as 1, and if she is not able to participate or additionally participate in any such program, it has been coded as 0. So, having the binary responses here logistic regression method has been applied. From Table 8.5, we may comment that 82.50% respondents can participate in social protest mentioned above and 17.50% respondents are not able to participate in any of the social protest program during the post-loan phase. Further in essence to explore the determinants of social empowerment, 8 explanatory variables have been reserved in the logistic regression model and result summarized in Table 8.6. The result shows that out of Table 8.5 Percentage of participation in social activities Social protest

Frequency

Not able to participate in social protest/awareness in post-loan phase (0) Able to participate in social protest/awareness in post-loan phase (1) Total

79

17.55

371

82.50

450

100.00

Source Calculated by Authors

Percent

0.090 −0.280 0.093 1.269 1.476 1.099 1.122 3.185

Eduins Dropout Examsno Representative Vote Age Min. age Approach

Source Calculated by Authors

Coefficient

Social protest 1.095 0.755 1.098 0.281 4.374 3.001 3.071 24.172

Odds ratio 0.327 0.367 0.345 0.356 0.366 0.649 0.412 0.421

Standard error

Method: Logistic Regression Sample size = 450 Dependent variable: Social protest participation (1 = yes and 0 = no) Mean of the dependent variable = 0.825

Table 8.6 Determinants of social empowerment

0.28 −0.76 0.27 3.56 4.04 1.69 2.72 7.57

Z 0.782 0.445 0.787 0.000 0.000 0.090 0.006 0.000

P >z 0.009 −0.029 0.009 0.133 0.155 0.115 0.118 0.334

Marginal effects

LR chi2(8) = 94.35 Prob > chi2 = 0.0000 Log-likelihood = −138.315 Pseudo R2 = 0.254

0.42 0.265 0.64 0.538 0.52 0.113 0.873 0.875

Mean of the variable

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the total 8 variables, 4 have significant stimulus on women social empowerment. The significant explanatory variables are “awareness about the name of local representative, able to exercise vote on own judgment, awareness about the minimum age of marriage for healthy family planning and approaching MFIs in need” and are found to be significant at 0.05% level.

8.3.3 Findings The collected data revealed some interesting facts about the different determinants separately for three dimensions of empowerment.

8.3.3.1 Economic Empowerment In case of economic empowerment, the study reveals that access to formal borrowing and familiarity with the access procedure to bank/services of post offices is immaterial in the determination of the incidence of economic empowerment. Controlling of resources is a significant basis of contribution for the family. With higher of resources control, the respondents are more expected to be in the upper level of contribution. In the same pace, with a higher level of self-employment and increased saving the respondents are more expected to be in the higher level of contribution. The coefficient of payments to different account linked services (Active) and possessing own assets are highly significant. If controlling of resources increases by 1 unit the samples are about to be 3% unlikely to contribute in any one area, about 23% unlikely to contribute to any two areas and about 26% more prospective to contribute in all the three areas. Further, if self-employment increases by 1 unit, the samples are about to be 1% unlikely to contribute in any one area, about 5% unlikely to contribute in any two areas and about 6% more expected to contribute in all three areas. In case of 1 unit increase in savings, the samples are about to be 2% less expected to contribute in any areas, about 18% less probable to contribute in any two areas and about 20% more expected to contribute in all the three areas. Again, if payments to different account linked

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services (Active) increases by 1 unit, the samples are about to be 2% less probable to be in the fair contribution (1) level, about 19% less likely to be in the good contribution (2) level and about 21% more expected to be in the excellent contribution (3) status which means higher economic empowerment. Likewise, if own assets increase by 1 unit, the respondents are about to be 5% less expected to be in the fair contribution (1) level, about 32% less probable to be in the good contribution (2) level and about 37% more prospective to be in the excellent contribution (3) level.

8.3.3.2 Psychological Empowerment In terms of psychological empowerment, from Table 8.4 it can be commented that awareness about current affairs is a significant cause for active participation in decision making. With more awareness level, the respondent is more presumably to actively partake in the decisionmaking progression in the family. Similarly, with the increased ability of freely communication with outsiders and free expression of opinions respondents are more ostensive to participate positively in the decision-making activity. The coefficient of increased ability to take decision outside the household, alone visit government offices/banks and purchasing small items is significant, and respondents are more hopefully to be in the higher level of participation in decision-making process. If awareness about current affairs increases by 1 unit, the samples are about to be 5% unlikely not to participate in any decision-making process, about 2% less preferred to participate in any one area, about 6% less expected to participate in any two areas, about 6% less prospective to participate in any three areas, about 8% more probable to participate in any four areas, about 1% more likely to participate in any five areas and about 10% more likely to participate in all areas of decision making (six). Further, we may comment from Table 8.4 that if the respondent able to speak with outsiders increases by 1 unit, the samples are about to be 11% less possibly not to participate in any decision-making process, about 5% less expected to participate in any one area, about 11% less probable to participate in any two areas, about 7% less probable to

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participate in any three areas, about 18% more prospective to participate in any four areas, about 2% more expected to participate in any five areas and about 14% more expected to participate in all areas of decision making. If ability to express opinion freely outside increases by 1 unit, the samples are about to be 2% unlikely to participate in any decisionmaking process, about 1% not likely to participate in any one area, about 4% unlikely to participate in any two areas, about 5% unlikely to participate in any three areas, about 2% further likely to participate in any four areas, about 1% more expected to participate in any five areas and about 9% more prospective to participate in all areas of decision making. If ability to take decision outside the household increase by 1 unit, the samples are about to be 3% not likely to participate in any decisionmaking process, about 1% not likely to participate in any one area, about 5% unlikely to participate in any two areas, about 6% not likely to participate in any three areas, about 2% more probable to participate in any four areas, about 1% more prospective to participate in any five areas and about 12% further likely to participate in all zones of decision making. If ability to visit government offices/banks alone increases by 1 unit, the respondents are about to be 3% unlikely not to participate in any decision-making process, about 2% unlikely to participate in any one area, about 6% less probable to participate in any two areas, about 9% less expected to participate in any three areas, about 3% unlikely to participate in any four areas, about 2% more probable to participate in any five areas and about 21% more possible to participate in all extents of decision making. If the ability to purchase mall items by her own increases by 1 unit, the respondents are about to be 6% unlikely not to participate in any decision-making process, about 3% unlikely to participate in any one area, about 8% less likely to participate in any two areas, about 7% dubious to participate in any three areas, about 10% more possible to participate in any four areas, about 2% more possible to participate in any five areas and about 12% more expected to participate in all six areas of decision making. In the case of psychological empowerment, MFIs borrowing assistances the respondent to be more poised and also to advance her

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business or entrepreneurial skills. The extent of psychological empowerment leads her into the outside of the home front, fabricates possibilities for employability and also helps to have better decisions in future.

8.3.3.3 Social Empowerment While discussing about social empowerment, the study reveals that awareness about children’s educational institute, number of dropouts, awareness about the number of exams held every year and age of the female are immaterial in the determination of the incidence of social empowerment. The coefficient of the arena “awareness about local representative” is highly significant. The regression coefficient advocates that if “the awareness about the local representative” upsurges by one per cent, the probability of social protest participation will enhance by 13% points. This may be reasoned due to high awareness about the social display, peer pressure and political stimulus on the respondents’ social behavior. Regularly vote at the election on own judgment is a significant cause of participation in social protest program. One per cent higher borrowers regularly vote at the election on own judgment enhance the probability of social protest participation (social empowerment) by 15%. It reflects the decision making the ability of the respondents. Likewise, awareness about the minimum age required for marriage and preferring financial institutions in case of credit need are significant. The coefficient advocates that if awareness about the minimum age required for marriage and preferring financial institutions in case of credit need increase by one per cent, then the probability of social protest participation will increase by 11 and 33%, respectively. The reason may be well-informed respondents can use their own judgment logically and help to make the society more responsive and responsible.

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References Books, Journal, Research Paper, Working Papers, Reports, Etc. Aggarwal, S., Kumar, P., & Garg, V. (2020). Empowering SHGs Women Through Micro-finance in Uttar Pradesh. International Journal of Law and Management. https://doi.org/10.1108/IJLMA-02-2020-0051 Anggadwita, G., Dana, L. P., Ramadani, V., & Ramadan, R. Y. (2021). Empowering Islamic Boarding Schools by Applying the Humane Entrepreneurship Approach: the Case of Indonesia. International Journal of Entrepreneurial Behavior & Research, 27 (6), 1580–1604. Ashraf, N., Karlan, D., & Yin, W. (2010). Female Empowerment: Impact of a Commitment Savings Product in the Philippines. World Development, 38(3), 333–344. Cinar, K., & Kose, T. (2018). The Determinants of Women’s Empowerment in Turkey: A Multilevel Analysis. South European Society and Politics, 23(3), 365–386. Duflo, E. (2012). Women Empowerment and Economic Development. Journal of Economic Literature, 50 (4), 1051–1079. Eggers del Campo, I., & Steinert, J. I. (2022). The Effect of Female Economic Empowerment Interventions on the Risk of Intimate Partner Violence: A Systematic Review and Meta-Analysis. Trauma, Violence, & Abuse, 23(3), 810–826. Hashemi, S., Schuler, S., & Riley, A. (1996). Rural Credit Programs and Women Empowerment in Bangladesh. World Development, 24 (4), 635–654. Kandpal, E., Baylis, K., & Arends-Kuenning, M. (2013). Measuring the Effect of a Community-Level Program on Women’s Empowerment Outcomes: Evidence from India. The World Bank. Lakshmi, K., & Vasantha, S. (2013). Microfinance Crisis in Andhra Pradesh and Regulatory Response. CLEAR International Journal of Research in Commerce & Management, 4 (12), 32–36. Rai, V., & Shrivastava, M. (2021). Microfinancial Drivers of Women Empowerment: Do Self-help Group Membership and Family Size Moderate the Relation? The Indian Economic Journal, 69 (1), 140–162. Rathiranee, Y., & Semasinghe, D. M. (2015). Factors Determining the Women Empowerment Through Microfinance: An Empirical Study in Sri Lanka. World Academy of Science, Engineering and Technology, International Journal of

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Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 9 (5), 1595–1599. Saha, B., & Sangwan, N. (2019). Credit Where Credit’s Due: The Enabling Effects of Empowerment in Indian Microfinance. World Development. https://doi.org/10.1016/j.worlddev.2019.06.009 Sahu, T. N., Agarwala, V., & Maity, S. (2021). Effectiveness of microcredit in employment generation and livelihood transformation of tribal women entrepreneurs: evidence from PMMY. Journal of Small Business & Entrepreneurship, https://doi.org/10.1080/08276331.2021.1928847. Sarumathi, S., & Mohan, K. (2011). Role of Micro Finance in Women’s Empowerment: An Empirical Study in Pondicherry Region Rural SHG’s. Journal of Management and Science, 1(1), 1–10. Sharma, S., Mehra, D., Akhtar, F., & Mehra, S. (2020). Evaluation of a Community-Based Intervention for Health and Economic Empowerment of Marginalized Women in India. BMC Public Health, 20 (1), 1–16. Weber, O., & Ahmad, A. (2014). Empowerment Through Microfinance: The Relation Between Loan Cycle and Level of Empowerment. World Development, 62(10), 75–87.

9 Summary and Conclusion

9.1

Summary of the Study

Throughout the globe, microfinance institutions provide access to a huge population who are financially excluded. MFIs always act as a support system, if utilized properly, to overcome certain issue resembling the financial burdens, endure intricacy allied to poverty, equality concern, vulnerability both inside and outside, etc. Here, an in-depth study considering both primary and secondary data gives the overall as well as the micro-level picture of MFIs in the selected district of West Bengal. In the first part, it has been observed that majority of the respondents are in their prime age group (31–40 years), earner (either working as wage labor or as domestic help), married, having no or minimum literacy, belongs to scheduled caste, Hindu, having nuclear family setup, domicile of rural area and monthly income lies between Rs. 6,000 and 8,000. Financial inclusion needs a supportive and sustainable environment to flourish. Beyond credit disbursement, credit plus services along with various social responsibilities ensure the outreach and penetration of financial inclusion. From observing the various initiatives of MFIs, it © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4_9

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has been found that a holistic approach has been followed by the operating MFIs to attain financial inclusion. For effective financial and social inclusion, creating a supportive environment along with awareness is equally important (Adams & Bartholomew, 2010). MFIs are continuously strived to influence the financially excluded population by initiating various primary and supportive activities. To be precise, along with credit and credit plus services various initiatives of MFIs are also being observed to have an overall understanding of the impact of MFIs in financial inclusion. Further, the impact assessment of MFIs has been observed in the district level study. The impact assessment of the MFIs started from the correct perception tracking towards operating MFIs. In this context, ttest has been applied, and it has been found that perception towards MFIs varies between borrowers and non-borrowers, and borrowers are having a better perception towards MFIs in the selected region. The reason behind better perception of the borrowers may be their constant interactions and involvement with MFIs in a sustainable manner. It helps them to build up better financial literacy and more accurate perception related to MFIs activities. Perception, especially in case of finance sector, plays a major role for further inclusion. So having a more accurate perception towards the activities of MFIs indicate a better tomorrow in the selected region. The role of MFIs towards financial inclusion further has been analyzed by observing the utilization of credit towards generating income. In this context, pre- and post-income levels have been observed to comprehend the impact of MFI borrowings. Also, the consumption level covering both pre- and post-loan phases is also being observed for a better understanding of the impact of MFIs on the borrowers. For this purpose, t-test comparing the status of income and consumption in the pre- and post-loan phase of the respondents indicates an increasing trend which refers the role of MFI borrowings in income generation and supporting the better standard of living. Moreover, the consumption level has also been risen up and indicates a better standard of living. Especially in case of frequencies of consumption of protein-based food item (fish, egg and meat) has been increased in the post-loan phase. It indicates the betterment in the diet patterns of the respondents and better nutrition.

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Again, while the analysis has been taken place to understand the impact of credit utilization on the borrowers, the study found that the majority of the borrowers utilize the credit amount productively. Though MFIs disburse credit for productive purposes only still a minor percentage of the respondents are utilizing it for unproductive purposes. The common reasons can be mentioned as social obligations, occurrence of unavoidable circumstances, burden of old debt, etc. So, it somehow disturbs the objective of MFIs where more supervision is absolutely needed. In the next part of the study, we have assessed the impact of microcredit on employability. In this study, the majority of the borrowers initiated various microenterprises. Based on the increasing average annual income, animal husbandry has been found as the most preferred category of microenterprise followed by business; agriculture-based microenterprise setup; cottage industries; service; and transportationbased microenterprises. Animal husbandary has been found to be the most preferred professions may be due to the geographic profile of the selected districts. These districts are having average to poor agricultural productivity, lack of soil productivity, inadequate supply of water for irrigation, especially in summer etc. Now, by applying multiple regression, we have found that microcredit has a major impact on employment generation. Borrowing from MFIs helps to build up the capital necessary to start-up microenterprises (McKernan, 2002). During the course of time, the microenterprises, if operated effectively, help to generate employment and income. Further, the study analyzes the level of efficiency towards financial inclusion using Data Envelopment Analysis (DEA). It has been observed that MFIs perform well and follow an increasing trend towards attaining efficiency with two input and two output variables. Out of thirteen operating MFIs efficiency has been measured. This finding indicates the acceptability and outreach of the MFIs among the borrowers. Further analysis has been considered to find out the influencing variables towards economic, psychological and social empowerment. Both economic and psychological empowerment influencing variables have been analyzed by using logit (ordered logistic regression) and social empowerment influencing variables have been analyzed by logit (logistic

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regression) model depending on the category. From ordered logistic regression, it has been observed that in case of economic empowerment, five independent variables (decision-taking on controlling of resources, self-employment, help to increase savings, maintaining active accounts and possessing own asset) and in case of psychological empowerment, six independent variables (awareness about current affairs, speaking with outsiders, able to express her opinion freely outside, able to take decision outside the household, alone visit government offices/banks and purchasing small items by her own) influence the level of empowerment significantly. In case of logistic regression, social empowerment has been influenced by four independent variables, namely awareness about the name of local representative, able to exercise vote on own judgment, awareness about the minimum age of marriage and considering MFI in the time of credit need. One of the major objectives of the MFI program is to enhance the level of female empowerment level. In this study, the MFIs role on women empowerment has been analyzed using t-test considering empowerment level in the pre- and post-loan phase of the respondents. All the contributing variables which constitute the dimensions of economic, psychological and social empowerment have been analyzed in both pre- and post-loan phase. Women empowerment has been analyzed from three dimensions over here: economic, psychological and social. It has been observed that borrowing from MFIs helps the women borrower to be better empowered in all three dimensions. The reason behind this is by participating in group-based lending system the borrowers gradually acquire confidence, training programs of MFIs help to enhance their professional skill, enhance participation in decision-making process, peer pressure motivates them towards savings and supporting environment help them to initiate income-generating activities, financial literacy increase, dependency on private money lenders decrease, etc.

9 Summary and Conclusion

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171

Conclusion

Financial inclusion is a global phenomenon though according to World Bank, almost 2 billion working-age adults do not have an account at a formal financial institution (Demirgüç-Kunt, A. et al., 2015). Microfinance has got hyped in recent times but in reality, it needs to go a long way. Financial literacy and awareness about the activities and benefits of MFIs can only be able to include the financially excluded population into organized financial market. This phenomenon is also supported by various government initiatives from time to time. Microfinance is an option to resolve the problem of poor people. It has introduced numerous initiatives ranging from awareness building, assisting towards borrowers’ development, etc. to create a supporting environment for societal improvement through corporate social responsibilities continuously (Haq et al., 2010). More and more financial inclusion ensures the possibility of sustainable growth and development to any nation. Accurate perception towards MFIs, its activities, etc. help to motivate anyone to think about MFIs in the time of need. So, responsibilities lie on the shoulders of microfinance institutions to create more and effective awareness campaign, continuous monitor to access the unreached population in order to create the correct perception about MFIs among the population. Apart from that, utilizing the credit in a productive way helps to generate income, a better standard of living and employability (Salia & Mbwambo, 2014). By setting up various microenterprises, borrowers are able to generate and gradually raise their income and consumption level as well. It also shows the way towards building savings behavior. To cater to the needs of the rural and urban financially excluded population, microfinance institutions need to have financial and operational efficiency towards financial inclusion. Unless and until the MFIs are not efficient enough, they are not able to reach the remotest area and the people who still rely on unorganized financial market for lending. In this study, the selected active MFIs reflects efficiency by following various financial inclusion initiatives, exceptional customer service, penetration of credit plus services (micro-insurance, micro-pension, etc.), training,

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financial literacy program, assured reach, wide geographical spread, efficient manpower, rigorous monitoring, team effort and mass marketing programs implemented from time to time. Equality ensures development and balance in the society. In order to strengthen any nation no one can deny the role of empowerment among the feminine gender. It can be assessed through different magnitude. In this study, it has been expressed through three extents i.e., economic, psychological and social scale. The study inclusive of limited sample spread over a limited geographic location. Out of the different variables, a few ones are influencing the empowerment profile of the respondent. It has been globally acclaimed that MFIs are liable for the better being of the females. This study also establishes this fact. But to ensure that, in the initial phase wide spreading of financial literacy and awareness is compulsory to create more accurate perception, lesser financial fraudulent, less political influences, more information and accessibility for subsidized lending programs, better usage of lending amount, etc. which in the long run enhance the effectiveness and operational proficiency of the MFIs. Financial inclusion has become one of the top priorities across the globe including India. But in our country, a good amount of population is still in dark, don’t have the basic financial know-how. There are huge gap exists on credit source and utilization information, the accessibility and penetration of MFIs, supply of MFIs in remote locations and likewise. So, bigger responsibilities lie on the shoulder of active MFIs in terms of awareness building, transformation of females towards confidence and empowerment and so on. More futuristic studies covering MFIs and its activities will help us to comprehend the prospects and problems associated with it, the journey of entrepreneurship, etc. in a better manner.

9.3

Contribution of the Study

Microfinance institutions have been served to the population who are at the verge of financial exclusion, lack development and growth in a sustainable manner. The current study on the role of MFIs for imparting financial inclusion has been considering the backward regions of the

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state. However, the available literature into this circumstance is limited with respect to eastern India specifically focusing the backward zone of West Bengal. Financial inclusion is one of the powerful tools for the sustainable betterment of the economy. So, initiatives and policies are always on the preference list to earn more stability and improvement of society. This empirical study contributes a detailed understanding of the dynamism of microfinance institutions and the impact of it into the financial inclusion map of our nation. It analyzes the various initiatives taken by MFIs along with its role into different spheres of inclusion. The present study is expected to add various primary contributions to the existing literature. First, it analyzes the literature by examining the significance of FI in the Indian economy and intends to be a basic coverage for further study and observe the role of MFIs in the grass-roots level spreading in the backward zones towards contribution to FI. The findings of this study are expected to put light on the real issues which influence the bottom of the pyramid population. At the same time, this study is expected to highlight some avenues for financial policymakers in the context of policy formulation especially considering the inclusion and empowerment issues. Apart from policymaking, the current study puts some light on the necessity of correct perception building specifically among the excluded population which can make the forward journey possible. Further, this study addresses a sensitive and essential issue-empowerment. By engaging contemporary econometric models, a detailed observation has been taken place which shed lights on the defining issues for further betterment of female empowerment status. This study engages various econometric models that may provide contribution to the available literature about the understanding of the analysis to the methods applied. So, this kind of study is relevant in emerging economies like India. This study highlights the relevance of financial inclusion, the way to achieve it and the after effect of FI on the beneficiaries. So, more detailed studies considering multiple dimensions can be followed and established for sustainable future of India.

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Recommendations and Policy Implications

A cross-section study on the role of MFIs covering three backward districts of West Bengal has been taken place in this study. All the offerings (both credit and non-credit) have an overall effect on the beneficiaries and their surroundings. Financial inclusion plays a crucial role in the well-being of the country. This study emphasizes on financial education which seems to be the first and foremost need for the improvement of the financial inclusion sector. For this, all the institutions should come forward and get involved actively to cover all the nooks and corners of our nation. However, this is indeed going to be a tedious task given the historical background that nearly half of India’s population remains unbanked even after sixty-seven years of independence. The Government of India and the RBI have been making concerted effort for more than six decades to increase penetration of formal financial institutions. This study suggests that to be an efficient and effective microfinance institution, it needs technology to be adopted with a human touch. Technology should be applied with customer-friendly approach and on-hands assistance should always be present for the easy and right execution of the MFI services. The study recommends that suitable policy should be designed to encourage the beneficiaries to utilize the monetary amount for betterment of their lifestyle, income and savings status. Awareness program should be initiated for not utilizing the credit amount into any unproductive purpose or solely for investment purpose. This study also recommends formulating detailed programs for the urban and rural regions. The profile and lifestyle demand are different in these two profiles so customized policy and programs should be formulated for fulfilling the heterogeneous need of the financially excluded population. It is evident that MFIs with its assistance help to create employability. Our study suggests that it is the responsibility of the MFIs to highlight

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the type of sector from where the possibilities of employment opportunities may be possible based on the geographical regions or locations and demographic nature of the creditors. It is utmost important to take customer care issue seriously especially in the finance sector. It is suggested that sensible and helpful staff, convenient location of the branch, customer-centric approach, etc. need to be incorporated in the daily execution of the microfinance institutions. Strict supervision is needed to create awareness about the chit funds, financial scams, Ponzi schemes, informal unorganized money lending and the relevant consequences of it in front of the eyes of the both financially included and excluded population. In the age of digitalization, handling of technology for monetary transaction is an important issue. Customer education programs should be adopted and implemented specifically for the creation of awareness about security issues to avoid further theft and harassment. It is the fundamental liability of the authorities to ensure easy accessibility of financial services and ensuring a guaranteed regulatory mechanism to monitor the effective execution of microfinance institutions in our society. This study observes that institutional support is an utmost needful element for the quality improvement, marketing and promotional activities of micro-entrepreneurship ventures. Both government and nongovernment bodies should come forward to make microenterprise setup more visible, viable and contemporary to boost up the inclusion movement.

9.5

Limitations and Direction for Further Studies

Every study has its own limitations or shortcomings. That leads the way for further research and analysis, a new vision to judge the context, scenario or practice. This study is also not an exception to it. In this study, while observing the impact of MFIs, we considered only three backward districts of West Bengal. The fact is that it is only a very limited region to observe for any effective conclusion. The sample area can be

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increased for better results. Moreover, the sample size is comparatively small. As we all know a comparative bigger sample size is a better representative of the population so a bigger sample size can be considered for assessing the whole population in a better way. Further while mentioning the various variables to define certain parameters in this study, the numbers are again very limited. Here, we consider a smaller number of independent variables to find the influence the employability. Again, a very limited number of independent variables have been used to analyze the extent of financial inclusion along with women empowerment. In future more variables can be incorporated to get more detailed findings. In the case of secondary data analysis, we have considered only five years data with six input and output variables. As the operational tenure of certain microfinance institutions is comparatively new in the selected regions, we left with no other choice than with very short time duration. The period is too short to analyze the efficiency test of any financial institutions. In the future the periods along with the number of active MFIs can be further increased for better results. To get more purified result we might apply the other relevant statistical and econometrical techniques as well. This study shows the direction of further research to examine the role of MFIs covering a larger area, with a bigger population. This study may also emphasize on the comparative analysis between MFIs and other formal financial institutions about their efficiency towards inclusion drive. Moreover, the study can be stretched the analysis and comparison between the financial inclusion status of rural and urban zone. This study also can be expanded on empowered female, their impact analysis on society and their contribution to the financial inclusion journey. With all the limitations involved, this study contributes to the present status on the MFIs and its journey in the selected areas. A few concerns exist in this study which needs to be mentioned before wrapping up. This sudden pandemic and the nature of COVID-19 are still not fully known. So dependency on the limited existing literature may limit the possible major issues associated with it. However, the inferential statistics may be its own limitations that may have influence on the

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findings of this study. Future research endeavors should be integrating data for assessing sudden pandemic situation. Financial inclusion is considered as an important issue in many countries including India. Throughout the economy, there is a certain percentage of the population who are not sufficiently able to access the formal financial sector. Due to irregularity of income, employability and poverty, a certain section of the society will lack the motivation to transact the basic services of financial institutions. Also, financial illiteracy sometimes acts as an obstacle and creates distorted perception towards financial services. The consequence leads to prosperity of private money lending, chit funds, harassment, gender inequality, etc. Also with the flow of time a good proportion of manpower and productivity get wasted. Various organizations including microfinance institutions are working with the objective of financial inclusion for the up-gradation of economy as well as the society. Microfinance institutions which specifically targeted the low income group can act as a potential and powerful medium to contribute financial awareness, motivate the target population to access formal financial services like zero balance account, imparting training program to build and update the technical and professional skill, assist them in interaction with industry, lending money with hassle-free terms and condition, influencing savings behavior, generate employability, women empowerment, improvement of household and lifestyle modification.

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Index

A

CRISIL Inclusix 7, 64

A C Shah Committee 33 Association model 62 D B

Business correspondents (BC) 33, 42, 56, 57 Business Facilitators (BFs) 33

Data Envelopment Analysis (DEA) 51, 123, 125, 127, 128, 130, 169 Decision-Making Units (DMUs) 123, 125, 128 Decreasing returns to scale 128 Deepak Mohanty Committee 36

C

Cochran’s formula 91, 92 Coefficient 54, 55, 161, 162, 164 Commercial banks 3, 9, 23, 24, 28–30, 35, 42, 50, 56, 58, 88, 89 Community banking model 62 Constant return to scale 125, 128 Co-operative model 62

E

Economic empowerment 135, 136, 138, 141, 143, 144, 153–156, 161, 162, 170 Economic independence 18 Empowerment 8, 9, 12, 19, 24, 27, 59, 65–67, 69, 72–75, 104,

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Datta and T. N. Sahu, Financial Inclusion and Livelihood Transformation, https://doi.org/10.1007/978-981-99-4141-4

197

198

Index

133–141, 143–145, 149–153, 159, 161, 170, 172, 173

F

Financial exclusion 6, 21, 22, 48, 52, 123, 172 Financial inclusions (FI) 2, 5–7, 9–11, 18–28, 30–33, 35–58, 60, 61, 63, 64, 66, 75, 76, 88–90, 112, 123, 124, 126, 130, 131, 133, 136, 139, 143, 167–169, 171–174, 176, 177 F-test 100, 101, 111, 112, 143–145

G

Global Hunger Index (GHI) 16 Grameen joint liability group models 62

Micro-pension 65, 171 Millennium Development Goals (MDGs) 1 Mobility of savings 18 Multiple regression analysis 137

N

National Bank for Agriculture and Rural Development (NABARD) 5, 25, 26, 29, 34, 55, 57, 63, 89 No frills account 25, 32

O

Ordered logistic regression 154–158, 169, 170

P I

Increasing returns to scale 128

J

Jan Dhan Aadhaar Mobile (JAM) 24, 31, 32

L

Logistic regression 159, 160, 170

M

Microcredit 3, 5, 8, 10, 29, 61, 64, 75, 76, 103–105, 116–119, 134, 169 Micro-insurance 171

Poverty eradication 2, 19 Pradhan Mantri Jan Dhan Yojana (PMJDY) 9, 24, 31, 51 Psychological empowerment 9, 142–144, 153–155, 157–159, 162, 163, 169, 170

R

Rangarajan Committee 6, 35 Regression 50, 51, 54, 58, 60, 117–120, 124, 125, 139, 164, 169 Rotating savings and credit association (ROSCA) 63

Index

199

S

V

Social empowerment 10, 12, 72, 142–145, 151, 153, 159–161, 164, 169, 170 Sustainable Development Goals (SDGs) 1 Sustainable lifestyle 19

Variable returns to scale 128 Variance 100, 101, 110–112, 119, 143, 144

W T

t-test 89, 94, 100, 101, 108, 111, 112, 138, 143–145, 168, 170

Women empowerment 7, 8, 10, 11, 38, 59, 66, 67, 74, 76, 134, 136, 139, 145, 149, 150, 170, 176, 177