Reserve Bank of India (RBI) Governor Sanjay Malhotra has urged Indian banks to accelerate their investment and adoption of artificial intelligence, arguing that AI could have a transformative impact on lending similar to the way UPI changed digital payments. Speaking at the FIBAC 2026 conference, Malhotra said banks should not remain passive observers as AI develops and should actively explore how it can improve lending, operations, customer services, and financial inclusion.
One major opportunity is using AI to make credit assessment more inclusive and efficient. AI can analyze broader sets of information and alternative data to help evaluate borrowers who have limited or no traditional credit histories. The RBI has previously identified potential applications across the credit lifecycle, including alternative credit assessment, fraud prevention, customer service, and risk management. This could help banks reach customers who have historically been underserved by conventional lending models.
However, Malhotra stressed that faster AI adoption must be accompanied by strong governance and human oversight. Banks cannot simply blame an algorithm when an AI-driven decision causes harm or produces an incorrect result. The RBI's responsible-AI framework emphasizes accountability, fairness, explainability, cybersecurity, data governance, and safety. The regulator has also warned that AI can increase fraud and cyber risks, meaning banks need to strengthen their defensive capabilities alongside their AI investments.
The broader message is that India's banking sector is entering a period where AI could become a core part of financial infrastructure rather than an experimental technology. India's existing digital ecosystem, including UPI and other public digital infrastructure, provides a strong foundation for AI-powered financial services. But the RBI's approach emphasizes that innovation and responsibility must develop together: banks need to invest in AI, train their employees, protect customer data, and maintain meaningful human accountability while adopting increasingly autonomous systems.
