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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65123
Volume:
10 |
6 |
Jun 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Commerce
Nehru Arts and Science College
Commerce
Nehru Arts and Science College
AI’s transformative impact has been profound since its advent, changing how enterprises, including those in the banking and finance sector, operate and deliver services to customers. The introduction of AI in banking apps and services has made the sector more customer-centric and technologically relevant. AI-based systems are now helping banks reduce costs by increasing productivity and making decisions based on information unfathomable to a human. Big data and artificial intelligence (AI) assist businesses with decision-making. They help companies create new products and processes or improve existing ones. As the amount of data grows exponentially and data storage and computing power costs drop, AI is predicted to have great potential for banks. This chapter discusses the implications of big data and AI for the banking industry. First, we provide background on big data and AI. Second, we identify areas in which banks can benefit from big data and AI, and evaluate their applications for the banking industry. Third, we discuss the implications of big data and AI for regulatory compliance and supervision. Lastly, we conclude with the limitations and challenges facing the use of big-data-based AI.
KEYWORDS
Artificial Intelligence (AI) is transforming both public and private sector banks by improving efficiency, accuracy, customer service, and decision-making. AI-powered technologies such as chatbots, fraud detection systems, credit scoring models, and predictive analytics help banks streamline operations and enhance customer experiences. Private sector banks have generally adopted AI more rapidly due to greater technological investments, flexible organisational structures, and stronger innovation strategies. Public sector banks, while progressing steadily, often face challenges related to legacy systems, regulatory procedures, and resource constraints. However, increasing digitalisation and government initiatives are encouraging wider AI adoption across the banking sector. AI is expected to play an even more significant role in personalised banking, risk management, cybersecurity, and financial inclusion. As technology continues to evolve, banks that effectively integrate AI with human expertise will gain a competitive advantage. Therefore, continuous investment in AI infrastructure, employee training, data security, and ethical governance will be essential for ensuring sustainable growth and long-term success in the banking industry.
1. Haris, M., Ahmad, T. (2021). An empirical study on artificial intelligence and credit risk assessment in the banking industry. International Journal of Finance and Economics, 6(1), 43–59. 2. Saini, S., & Gupta, R. (2021). Artificial Intelligence in Fraud Detection. Journal of Financial Services Research, 55(2), 111-137. 3. Singh, S., Ravi, V. (2021), Artificial intelligence's effects on Indian banking. 15(4), 36–47, Indian Journal of Finance. 4. Srinivasan, V., & Arumugam, M. S. (2021). Artificial intelligence and its application in the banking sector. Journal of Retailing and Consumer Services, 61, 102586. 5. L. Sharma,M. Siddiqui L., (2020), The impact of artificial intelligence on the banking sector. 6. M. Bhatia, R. Tiwari, et al (2020), Artificial Intelligence in Banking: Current Status and Future Prospects. International Journal of Current Technology and Engineering covers the years 1947 to 1951. 7. Sharma, A., Shukla, R. (2020), Review on AI Adoption in Indian Banking Industry. 8(8), 1–7 in 8. International Journal of Scientific Research and Management. 9. S. Nandi, R. Chakraborty,(2020)Examining artificial intelligence in the financial industry. International Journal of Advanced Science and Technology. 29(5), 1545-1554. 10. Jain, "Artificial Intelligence for Risk Management in Indian Banking Industry," International Journal of Engineering and Applied Sciences, vol. 6, no. 4, pp. 43-46, 2019
Publication Date
6/17/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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