Bangladesh Bank Training Academy Journal

Abstract

This study examines the effects of AI-driven FinTech solutions on credit risk management in the retail banking of Bangladesh. Three leading commercial banks in Bangladesh- BRAC Bank Limited, Mutual Trust Bank Limited, and The City Bank Limited are selected to examine the effectiveness of credit risk management during the 2023–2024 time frame. A quantitative research design is used to analyse on loan performance, and primary survey data are collected from 150 retail borrowers of the selected banks. The study employs Partial Least Squares–Structural Equation Modeling (PLS-SEM) to test the proposed conceptual framework. The results reveal that repayment timeliness has a significant positive effect on portfolio quality, while operational cost per loan, loan default rate, and average loan processing time exert significant negative effects. Furthermore, portfolio quality is found to have a strong positive influence on credit risk management effectiveness. The findings suggest that AI-driven FinTech solutions enhance credit risk management primarily by improving borrower repayment behaviour and strengthening loan portfolio health, rather than solely through cost and speed efficiencies. The research contributes to understanding the effect of AI-driven FinTech solutions adoption in retail banking. It provides valuable insights in AI-driven digital financial technology on credit risk management for practitioners, policymakers, and educators.