The adoption of IFRS 9 has ignited a debate among academics about its impact on credit risk management (CRM) in commercial banks. This study sought to evaluate the moderating effect of management efficiency in the relationship between IFRS 9 and CRM in commercial banks in East Africa. The study used quantitative methods, specifically panel data analysis, and is anchored the Problem Loans and Cost Efficiency Hypothesis. The study used data from 2015 to 2021, covering financial years before and after the adoption of International Financial Reporting Standard No. 9. Secondary data was gathered from the annual financial statements of commercial banks in four East African countries chosen for this study. The data was processed using the statistical software STATA version 14 to generate descriptive and inferential statistics to determine the trend underlying the connection between the dependent and independent variables. The results indicated that management efficiency had a significant moderating effect on the relationship between IFRS 9 and CRM. The model coefficient values were all positive, and the p-values were all less than 0.05. After the interaction, the coefficient of determination increased from 58.02% to 74.61% before and after moderation models, respectively. This implies that credit risk management is significantly related to the interaction term of the independent variables; expected credit losses (p=0.0130), credit loss volatility (p=0.000), and the change in the method of computing interest on NPLs (p=0.037). This implies that management efficiency has significant effects on credit risk management in the long run. The study concludes that efficient management practices are essential for identifying, measuring, mitigating, pricing, and controlling credit risks, enhancing overall bank performance. The study recommends that commercial banks in East Africa prioritize and enhance management efficiency by building strong governance structures, developing a risk-management culture, providing employee training, and implementing robust performance management for credit risk management teams.
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Kiyai et al. (2024) studied this question.
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