A STUDY ON ARTIFICIAL INTELLIGENCE IN CREDIT RISK ASSESSMENT: A STUDY OF INDIAN BANKING SECTOR

Abstract

Artificial Intelligence (AI) is transforming the credit risk assessment process in the Indian banking sector by improving the accuracy, speed, and efficiency of lending decisions. This study examines the role of AI technologies, including machine learning, predictive analytics, and big data, in evaluating borrowers' creditworthiness and reducing the incidence of non-performing assets (NPAs). It explores how Indian banks utilize AI-driven models to analyze financial and non-financial data, detect fraudulent activities, and enhance decision-making while ensuring regulatory compliance. The study also highlights the benefits of AI, such as improved risk prediction, cost reduction, enhanced customer experience, and faster loan approvals, along with challenges related to data privacy, algorithmic bias, and technological implementation. The findings indicate that AI-based credit risk assessment significantly strengthens risk management practices and contributes to greater financial stability, operational efficiency, and sustainable growth in the Indian banking sector