Analysis of default risk in microfinance institutions under the Basel III framework

Abstract

International organizations such as OECD, WBG, IMF, UN and EU, as well as research studies, have highlighted the increasing contribution being made by microcredit finance institutions (MFIs) to financial inclusion, sustainable economic development and the fight against poverty. However, access to MFI credit is still far from the desired level for small and micro-enterprises, especially in developing countries. The countries of Latin America and the Caribbean, where approximately half of the small formal companies do not have access to credit, have the world's highest financial gap ratio compared to potential demand (87%). In this context, effective instruments are needed to assess default risk, through credit ratings. Based on the Basel III regulations, an empirical study was conducted of two microcredit portfolios corresponding to two MFIs in two Latin American countries (Bolivia and Colombia) during the period 2012-2015, to identify the explanatory variables of the probability of default on loans granted by MFIs, using a logistic regression model and a neural network. The results obtained show that the main variables in this respect are the amount of the loan, the number of payments in arrears, the guarantees provided, the assessment of the credit analyst, male gender of the borrower and the level and trend of the general stock exchange index. The conclusions presented advance previous research findings and may be useful for MFI managers, regulatory institutions, financial analysts, scholars, policy-makers and applicants for microcredits to undertake a business project, especially in times of emerging crisis, such as that caused by the Covid-19 pandemic.

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“…Implementation varies by region, in the European Union regulation started in phases during period 2019 and 2025. In credit risk area regulation aims at increasing sensitivity of standardized method of credit risk and to selectively restricts use of results from internal model approach to reduce variability between FIs model outputs (Durango-Gutiérrez et al, 2021). The use of external ratings will have more detailed rules and use is complemented by the new approach to counterparties without external rating.…”

A Comparative Evaluation of the Effects of Credit Risk Control on the Profitability of Micro-Finance Bank

“…Their analysis indicates that a higher percentage of female loan officers increases loan portfolio risk where female loan officers have higher chances of giving female loan borrows loan and this may decrease the default rate of loans offered in microfinance banks. Durango-Gutiérrez et al, (2021) conducted a study on microfinance banks in Bolivia and Colombia based on credit portfolios. The author used a logistic regression model and neural network to analyze data from 2012 -2015.…”

The impacts on informal financing strategy of small and micro enterprises by interest rate risks and public health emergencies

“…Yang et al ( 2022 ) investigated the factors that influence SME patent collateralization for loans. Durango-Gutierrez et al ( 2021 ) discovered that the default likelihood of microcredit financing institution loans may be described by loan amount, arrears payments, guarantees, credit analyst evaluation, borrower gender, and stock exchange index.…”