Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{198876,
        author = {Arpita Bhojraj Nimje and Nitin Prakash},
        title = {A Study of Artificial Intelligence in Credit Risk Assessment and its Impact on Investors: A Case Study of HDFC Bank},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {11762-11768},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198876},
        abstract = {The banking industry is one of the areas where Artificial Intelligence (AI) is changing the manual approach to credit risk assessment, evolving into more efficient and data-driven, and predictive systems. The paper will discuss the AI and its use in credit risk evaluation as well as assess the effects of AI on shareholders, specifically HDFC Bank of Nagpur. Conventional credit assessment methods tended to have inadequate financial information and subjective decisions resulting to inefficiency, delays and chances of default. On the contrary, AI systems are powered by machine learning, big data processing, and real-time processing to increase the precision and speed of credit decisions.
The study will use descriptive and analytical research paradigm on the basis of secondary sources of data such as academic journals, banking reports and industry publications. The results show that AI can contribute to the quality of credit evaluation significantly through the use of alternative sources of data including transaction behavior, online footprints, and the profiling of consumers. Using AI in its credit risk management system, HDFC bank has been efficient in real-time monitoring, detecting fraud and making predictions.
Financially speaking, AI-based credit risk assessment allows an investor to increase financial stability through the minimization of non-performing assets (NPAs) and improved profitability, as well as risk management practices. It translates to a rise in the level of investor confidence and an improved market performance. The paper, however, also finds the problem of data privacy concerns, algorithmic bias, absence of transparency and regulatory issues. The study arrives at the conclusion that the drawbacks notwithstanding, AI is an important part of the contemporary banking industry which has a beneficial effect on financial organizations and investors.},
        keywords = {Artificial Intelligence, credit risk assessment, HDFC bank Nagpur, machine learning, investors, banking technology, financial risk, predictive analytics, NPAs.},
        month = {April},
        }