CREDIT APPRAISAL PARAMETERS AND ASSET QUALITY OF MICROFINANCE BANKS IN KENYA
Abstract
Microfinance banks play an important role in the provision of a wide range of financial services and products. However, they have been struggling with huge volumes of increasing NPLs which negatively affect their performance. The general objective of the research was to determine the effect of credit appraisal parameters on asset quality of microfinance banks in Kenya. Specific objectives were to determine the effect of borrower’s character, capacity, credit rating, credit history and collateral on asset quality of MFBs in Kenya. The research was underpinned on information asymmetry theory, transaction cost theory, theory of credit scoring and the 5 c’s model of client appraisal. The findings reveal significant relationships between credit appraisal parameters and asset quality in MFBs in Kenya. Borrower's character, capacity, credit rating, credit history, and collateral all exhibit positive coefficients, indicating that improvements in these areas are associated with better asset quality. Specifically, borrower's character, capacity, credit rating, credit history, and collateral exhibit coefficients of -0.354, -0.135, -0.163, -0.216, and -0.311, respectively, all significant at p < 0.05. These findings underscore the importance of robust credit appraisal processes in mitigating credit risk and maintaining asset quality within MFBs. Therefore, the study recommends enhancing borrower assessment mechanisms, including character evaluation, capacity analysis, credit rating procedures, credit history reviews, and collateral valuation, to progress asset quality management in Kenyan Microfinance banks.
Keywords: Asset quality, Borrower’s capacity, Borrower’s Character, Collateral, Credit history, Credit Rating
Full Text:
PDFReferences
Aikman, D., Haldane, A. G., & Nelson, B. D. (2015) ‘Curbing the Credit Cycle’, The Economic Journal, 125, 1072–1109.
Association of Microfinance Institutions (AMFI) (2023). AMFI Members: https://amfikenya.com/membership-categories/
Battiston, S., Stolbova, V., Napoletano, M. &Roventini, A. (2017). Financialization of Europe: A Comparative Perspective. ISI Growth Working Paper No. 22/2017
Liedholm, C. (1985). Small Scale Enterprise Credit Schemes: Administrative Costs and the Role of Inventory Norms. Working Paper No. 25, Department of Agricultural Economics, Michigan State University.
Moradi, S., &Rafiei, F. M. (2019). A dynamic credit risk assessment model with data mining techniques: Evidence from Iranian banks. Financial Innovation, 5(1), https://doi.org/10.1186/s40854-019-0121-9
Mulyungi, W. &Mulyungi, M. P. (2020). Effect of Client Appraisal on Financial Performance of Financial Institutions in Rwanda: A Case Study of Guaranty Trust Bank Rwanda PLC. International Journal of Science and Research, 9(6), 2-32.
Mungai, J. N., Maingi, J. &Muathe S. M.A (2018). Effect of Borrower' Characteristics to Government Funded Micro-Credit Initiatives in Murang'a County, Kenya. International Journal, 3(11).
Murigi D. M. & Thuo, A. (2018). Credit Risk Management and Loan Performance in Microfinance Banks in Kenya. International Journal of Economics, Commerce and Management, 6(4), 623-643
Musa, M. M. &Nasieku, T. (2019). Effects of Credit Risk Management on Loan Performance of Commercial Banks in Kenya: A Case of Listed Commercial Banks in Kenya. International Journal of Recent Research in Social Sciences and Humanities, 6(2) 140-146
Mwangi, A. W. (2021). Effect of credit management on asset quality of microfinance institutions in Nairobi Metropolitan (Doctoral dissertation), KCA University, Nairobi.
Mwaura, D. &Jagongo, A. (2017). Credit Policy and Financial Performance of Commercial Banks in Kenya. International Journal of Current Research, 9(1), 45912-45918.
Reis, G. D., Pfeuffer, M., & Smith, G. (2020). Capturing model risk and rating momentum in the estimation of probabilities of default and credit rating migrations. Quantitative Finance. 1?16
Simba, B. & Mugo, S. (2018). Effect of Borrowers Capacity and Capital Information on Credit Risk Management: A Case of Microfinance Institutions in Nakuru Town. Mara Research Journal of Business and Management, 3(1), 25 – 43.
Tounsi, Y., Hassouni, L., &Anoun, H. (2018). An enhanced comparative assessment of ensemble learning for credit scoring. International Journal of Machine Learning and Computing, 8(5), 409–415. DOI: 10.18178/ijmlc.2018.8.5.721
Wanjiru, K. W. (2016). Microfinance Institutions in Kenya. Strathmore University, Nairobi, Kenya
Williamson, O.E. (2007). Transaction Cost economics: An Introduction. Economics discussion papers.2007-3, march 1, 2007 Economic sociology. CSES working paper series, paper # 13 October 2003.
Zhang, Y., & Chi, G. (2018). A credit rating model based on a customer number bell-shaped distribution. Management Decision, 56(5), 987–1007. https://doi.org/10.1108/MD-03-2017-0232
Zhao, Q. (2017). Do managers manipulate earnings to influence RAF credit rating agencies’ decisions? Evidence from watchlist. Review of Accounting and Finance, 16 (3), 366–384.
Refbacks
- There are currently no refbacks.