Credit Risk Management Practices and Performance of Selected Microfinance Banks in Nigeria

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Date

2023-12

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Lead City University

Abstract

Credit risk management has been one of the critical challenges facing Nigerian Microfinance Banks (MfB’s) due to loan repayment defaults, poor assets quality, inadequate loan loss provisions and capital adequacy. This study empirically investigates the effect of Credit Risk Management (CRM) practices on selected microfinance banks performance in Nigeria from 2016 to 2020. It uses a secondary dataset to evaluate the effect of credit risk management practices on return on asset (ROA), return on equity (ROE), net interest margin (NIM), client base (CB) and operating income (OI) of some selected MfBs. EVIEWS and STATA statistical packages were used to carry out the descriptive statistics, correlation analysis, scatter charts and the regression analysis. The findings reveal that Non-performing loan ratio has negative and significant relationship with ROA ( 0.12,t c 1.20, p  0.05) , ROE (  3.11,t c  3.14, p  0.05) , NIM ( 0.22,t c 0.15, p0.05) , CB (  0.21, t c  2.18, p  0.05) and OI(  0.14,t c  1.19, p  0.05) . Loan loss provision to deposit ratio has negative and significant effect on ROA (  0.12,t c  4.56, p  0.05) , ROE (  0.04, t c  1.89, p  0.1) , NIM (  1.55,t c  3.44, p  0.05) , but positively affects CB (  0.03, t c  2.71, p  0.05) and OI (  0.04,t c  1.12, p  0.05) . Also, Asset Quality Ratio has positive effect on all parameters of MFBs i.e. ROA (  0.10,t c  1.08, p  0.05) , ROE (  0.31,t c  3.28, p  0.05) , NIM (  0.03,t c  0.02, p  0.05) , CB (  0.20,tc  2.05, p  0.05) and OI (  0.17, tc 1.47, p  0.05) . However, leverage ratio negatively affect ROA (  2.48,tc  1.90, p  0.1) , ROE (  0.23,tc  3.82, p  0.05) , NIM(  6.74,tc  3.65, p  0.05) and OI(  0.05 tc  0.71, p  0.05) but directly influence CB (  0.63,tc  10.44, p  0.05) . The joint predictors of credit risk management adversely influence ROA (  0.17,tc  2.12, p  0.05) , ROE (   0.06,tc  0.96, p  0.05) , NIM (  0.84,tc  0.62, p  0.05) , CB (  0.38,tc  5.37, p  0.05) , and OI (  0.003,tc  0.07, p  0.05) . The study concludes that credit risk management significantly influenced the performance of MfB’s in Nigeria and recommends that the management must pay adequate attention to understand and improve its credit risk management practices to ensure positive performance and avoid the negative consequences of wrong practices. Also, a dynamic regulatory framework is needed to ensure MfB’s delivered on the expected gains and avoid unnecessary loss of customers’ deposits. Keywords: Bank performance, Client base, Credit risk, Microfinance Banks, Micro loans.

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Keywords

Bank performance, Client base, Credit risk, Microfinance Banks, Micro loans

Citation

Kate Turabian

URI

https://repository.lcu.edu.ng/handle/123456789/468

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Department of Accounting