Predicting the Likelihood of Loan Default Among Marginalised Population: A Case Study on Rural Bengal

Abstract

Credit is the lifeline of all economic activity, which can enhance earnings, augmenting capital formation and helping the poor to move out of poverty. Further, during the time of economic downturn, maintaining the loan repayment performance of micro borrowers is one of the biggest challenges for the MFIs. The rate of loan default among borrowers has been increasing, leading banks and other financial institutions to be in the midst of the NPA crisis. This chapter tries to identify the key factors of microloans that contribute to the risk of default using the data from a cross-section survey conducted among 500 rural borrowers living from the rural areas of West Bengal applying a multivariate statistical technique. The determinants include various borrower-specific and loan-related characteristics. It reveals that the risk of default increases for female borrowers than male, for aged borrowers, lower household income, number of dependent family members if loans taken from non-formal borrowers. On the other side, the risk of default decreases with the education level of the borrowers, assets holdings other than agricultural land and an increase in business experiences of the borrowers. Furthermore, default chances are higher on loans for consumption and emergency purposes than other types of loans. The results of this study have a significant impact on the credit assessment and the monitoring of loans by MFIs, particularly during the time of economic recession when the financial institutions are seeking ways to get out of the financial crisis.KeywordsMicrofinanceRepaymentFormal creditDefault riskLogistic regression