OPTIMIZING PROFITABILITY THROUGH CREDIT RISK METRICS IN COMMERCIAL BANKING OF AN EMERGING MARKET: INSIGHTS FROM PANEL REGRESSION ANALYSIS

Abstract

This studyexamines the effect of credit risk management on the profitability of commercial banks, with a focus on two key profitability measures: Earnings Per Share (EPS) and Profit After Tax (PAT). Using panel data regression analysis, the study explores how factors such as Non-Performing Loans (NPL), Loan Loss Provision (LLP), Loans and Advances (LA), and Total Deposits (TD) influence these profitability indicators. The results show that while the relationship between credit risk management practices and profitability is complex, key variables such as Loan Loss Provision and Loans and Advances significantly impact profitability, both directly and indirectly. Non-performing loans, though influential, do not have as strong a relationship with profitability as expected. The findings suggest that banks can improve profitability by optimizing credit risk management practices, with an emphasis on better provisioning, strategic loan growth, and enhanced monitoring of credit quality. This research contributes to the understanding of how effective credit risk management can drive financialperformanceincommercialbanksandoffersinsightsforbothpractitionersand policymakersaimingto strengthen the banking sector's resilience and profitability.

Keywords

• Credict risk management
• bank profitablity
• earnings per share
• non-performing loan
• loan loss provision