Article’s

The rapid expansion of India’s FinTech sector has accelerated the adoption of Artificial Intelligence (AI) in credit risk assessment and lending decision-making. This study examines how AI-driven analytics influence the accuracy of credit evaluation, the speed of loan processing, and the overall quality of lending decisions among FinTech, banking, and NBFC professionals. A descriptive and analytical research design was adopted, drawing on primary data collected from 120 respondents through a structured questionnaire, supplemented by secondary literature. Data were analyzed using percentage analysis, mean and standard deviation, correlation, and multiple regression in MS Excel. The analysis indicates a positive and statistically significant relationship between AI adoption and both credit risk assessment efficiency and lending decision quality, while also highlighting challenges such as data quality, model interpretability, and regulatory alignment. The study concludes that AI adoption, when supported by robust governance and skilled personnel, meaningfully strengthens credit risk assessment and lending outcomes in India’s FinTech industry, and offers practical recommendations for FinTech firms, digital lenders, banks, and NBFCs.