Ethical and Regulatory Challenges of Deploying AI Powered Credit Management Systems in Banks

Background: The application of Artificial Intelligence (AI) in banking has transformed credit management by enhancing efficiency, accuracy, and risk assessment. However, these advancements also raise critical ethical and regulatory concerns, including transparency, bias, data privacy, and compliance with existing laws. Methods: This quantitative study explored the ethical and regulatory aspects of AI-driven credit management systems. A structured questionnaire was administered to employees of 15 commercial banks in Dhaka and Chittagong. Out of 500 distributed questionnaires, 400 valid responses were analyzed using descriptive statistics, reliability testing, and multiple regression analysis to test the proposed model. Results: Findings revealed that ethical challenges, particularly bias mitigation and decision transparency, were rated as more pressing than regulatory issues. Both ethical and regulatory constructs significantly predicted perceived risks associated with AI adoption. Weaknesses in regulatory frameworks were found to exacerbate operational risks by limiting oversight. AI-adopting banks demonstrated stronger strategic responses, including training, audits, and governance practices, compared to non-adopting banks. Conclusion: The study highlights the need for robust governance mechanisms, routine AI audits, and stronger collaboration with regulators to ensure responsible AI deployment in credit management. Addressing ethical risks and strengthening regulatory frameworks are critical to mitigating operational and reputational risks while fostering sustainable adoption of AI in the banking sector.