Overcoming barriers to financial inclusion: empirical evidence from India

Abstract

PurposeThis paper attempts to measure the state-wise impact of Prime Minister's Jan Dhan Yojana (PMJDY) in 30 states and 6 union territories of India for the years 2016, 2017 and 2018; and tries to develop a state-wise plan for geographical expansion of outlets optimizing the overall impact of the scheme.Design/methodology/approachThe state-wise impact factor is calculated using demographic penetration of the scheme in rural areas, demographic penetration of the scheme in urban areas, percentage of accounts with Rupay cards and average balance in these accounts. The impact factor is postulated to be a linear function of literacy, per capita GDP, demographic and geographic penetration of banks and the number of poor people. The weights for the sub-parameters are derived through principal component analysis. A generalized linear model with heteroscedasticity and autocorrelation consistency method for estimation of the equation with robust standard errors is used.FindingsIt is found that the scheme has been more effective in the states with higher levels of illiteracy which is contrary to the findings of existing studies where illiteracy is identified as a barrier to financial inclusion. A state-wise plan for geographical expansion of outlets is proposed with a view to optimizing the overall impact of the scheme, along with suggestions for improvement.Research limitations/implicationsThe data for ATMs and bank mitras are available for some of the years, for some states and hence missing data were estimated using extrapolation or on an average basis. Furthermore, the panel data are available for three years making the period of panel small. These aspects might have affected the efficacy of our estimates.Originality/valueThe paper evaluates the newly launched ambitious program PMJDY by the Government of India (GoI), it will have far reaching impact on financial inclusion.

Financial inclusion of Muslim minority in Vellore, Tamil Nadu

“…Low-income individuals who lack financial stability often rely on access to finance. Commercial lending institutions generally follow similar policies when extending credit to the economically disadvantaged population throughout the country (Ambarkhane et al, 2022). Though lending institutions from time to time launch different new credit schemes specially designed for the poor, the lack of awareness programmes among poor people keeps them away from access to such schemes (Pal et al, 2022).…”

Does financial inclusion impact socio-economic stability? A study of social safety net in Indian slums

“…Despite noteworthy advancements in all areas of financial reachability and viability, there are apprehensions that these social assistance programmes have not penetrated the urban population, particularly the economically poor sections of society living in slums, into the coverage of essential financial services (Singh et al, 2021). The reasons identified are high corruption among government officials, peer pressure, lack of collateral security, financial illiteracy, lack of awareness and confidence in government officials, poor credit policies, high-interest rates, technological illiteracy and loopholes in grievance redressal mechanism, etc (Ambarkhane et al, 2022;Feghali et al, 2021). Despite various steps taken by the Indian government, the social assistance schemes are not performing as expected in urban areas .…”

“…, 2021). The reasons identified are high corruption among government officials, peer pressure, lack of collateral security, financial illiteracy, lack of awareness and confidence in government officials, poor credit policies, high-interest rates, technological illiteracy and loopholes in grievance redressal mechanism, etc (Ambarkhane et al. , 2022; Feghali et al.…”

Financial Inclusion of Vulnerable Sectors with a Gender Perspective: Risk Analysis Model with Artificial Intelligence Based on Complex Thinking

“…Most of the time, these women are in households where their members have ine cient savings strategies and lack accurate information about the products and services of formal nancial institutions and how to access them (Lusardi, 2019; Zhang and Xiong, 2019; Lyons et al, 2020;Yang et al, 2022). Also, there is no supply of these products and services targeted to their circumstances and needs (Alberro et al, 2016; Cuesta-Gonzalez et al, 2021; Danquah et al, 2021;Ambarkhane et al, 2022). The products and services of conventional nancial institutions have been designed for a population with a credit history, steady economic income, contingent family backup, and nancial education, among others; that is, a population that can be granted credit with a low risk of default (Lotto, 2018;Shihadeh, 2018; Dar and Ahmed, 2020; Amari and Anis, 2021; .…”