Harnessing Artificial Intelligence: Redefining Credit Risk Management for Banks in India

In recent times, Artificial Intelligence (AI) is adopted in Indian banking sector in areas such as customer lending services, fraud risk and credit risk management. However, AI usage in banks face issues with respect to lack of governance and business strategy, along with fragmented IT systems, sub-optimal core technology, outdated operating models, lack of strategy in talent management, which are the core challenges in Indian banking system for AI adoption. Indian banks have augmented application of AI in varied scales but has no uniformity is its usage. Historical data, statistical models, and expert judgment gave the framework for credit risk assessment. With the introduction of Artificial Intelligence, Credit risk has become an important component of banking risk. In the wake of this scenario, the present study attempts to explore how Indian banks are using AL & ML in their credit risk management practices. The objective of the paper is to identify the various purposes of the use of AI in Indian banks. The study used secondary data sources of select Indian commercial banks to highlight the potential usage of AI and the findings reveal that banks are at different stages of employing AI-based technological applications in credit risk management. Banks encounter challenges such as, lack of governance drive for AI and ML adoption and majorly fail to disclose their annual budget plans for AI and ML. Valuable insights have been evolved through this study that would help the banks, policy makers, government and customers at large to understand the current status of the use of AI, its applications, challenges and opportunities proving that there is a need for quality checks on the data used by banks and rationalization of AI models through a technical certification process.