Impact of AI-Based Credit Scoring on Loan Risk Management in Indian Banks

Abstract Artificial Intelligence (AI) has become an important technological advancement in the banking sector. Banks are increasingly using AI to improve decision-making processes, especially in credit risk assessment and loan management. Credit scoring is a method used by banks to evaluate the creditworthiness of borrowers before approving loans. Traditional credit scoring models rely mainly on historical financial data and statistical methods, which sometimes fail to accurately predict loan defaults. AI-based credit scoring systems use machine learning algorithms and large datasets to analyze borrower behavior and financial patterns more effectively.This research paper examines the impact of AI-based credit scoring on loan risk management in Indian banks. The study is based on secondary data collected from academic journals, banking reports, and financial technology publications. The research highlights how AI improves credit risk prediction, reduces loan default rates, enhances operational efficiency, and supports financial inclusion. The paper also identifies challenges associated with AI implementation, including data privacy concerns, algorithmic bias, and regulatory issues. The findings suggest that AI-based credit scoring significantly strengthens loan risk management and improves the efficiency of banking operations.