AI-Driven Credit Assessment in Banks and Non-Banking Finance Companies (NBFCs) in India: A Comprehensive Analysis
This study examines the application of AI frameworks in real- world scenarios, including regulatory compliance, fraud detection, credit scoring, default prediction, and portfolio management (Moscato et al., 2020). By leveraging AI to gain deeper insights into borrower creditworthiness, financial institutions can enhance decision- making, streamline processes, and foster a more stable financial environment. However, alongside its transformative potential, the implementation of AI presents significant challenges. Ensuring data quality, improving model interpretability, adhering to regulatory compliance, and addressing ethical considerations are crucial to achieving fair and unbiased outcomes. This paper highlights both the opportunities and complexities associated with integrating AI into financial systems, emphasizing the need for balanced and responsible adoption. 2025 by IGI Global Scientific Publishing. All rights reserved.
Malhotra, Shikha; Dhanya, K.A.; Prathibha, Raj M.S.; Mohanty, Priyakrushna
Machine Learning and Modeling Techniques in Financial Data Science;pp.275-292
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.4018/979-8-3693-8186-1.ch011 https://www.scopus.com/pages/publications/105007273514?origin=resultslist
Malhotra S., Christ University, India; Dhanya K.A., Christ University, India; Prathibha R.M.S., Christ University, India; Mohanty P., Christ University, India