India is looking to artificial intelligence (AI) as the next major transformation in its financial sector after the extraordinary rise of the Unified Payments Interface (UPI). Over the past decade, UPI has changed how Indians send and receive money, pay merchants and access digital financial services. Now, policymakers, banks and fintech companies are exploring whether AI can take that digital infrastructure a step further by making financial services more intelligent, personalised and increasingly automated.
The shift is becoming a major theme at the Global Fintech Fest in Mumbai, being held from September 8 to 11. Policymakers, financial institutions, technology companies and fintech founders are discussing agentic AI, tokenisation and other technologies that could shape the next phase of India’s financial ecosystem. Prime Minister Narendra Modi, Finance Minister Nirmala Sitharaman, RBI Governor Sanjay Malhotra and SEBI Chairman Tuhin Kanta Pandey are among the key figures participating in the event.
From UPI Payments to AI-Powered Finance
UPI provides the foundation for India’s next financial technology push. The platform processed 24.51 billion transactions worth about ₹29.82 trillion in August 2026 alone, highlighting the enormous scale of India’s digital payments ecosystem. The government says UPI processed more than 24,162 crore transactions worth approximately ₹314 lakh crore during FY2025-26, with more than 700 banks connected to the system.
However, UPI primarily solved the problem of moving money quickly and seamlessly. AI could address a different part of finance: helping machines make decisions around money.
AI systems could analyse transaction histories, cash flows, GST records and other information to assess borrowers, particularly people and small businesses with limited traditional credit histories. RBI Governor Sanjay Malhotra has said AI could do for lending what UPI did for payments by expanding the number of people who can be evaluated for credit.
That could be particularly important in India, where millions of individuals and small businesses remain outside traditional lending models. Instead of relying only on conventional credit histories, AI could analyse alternative financial information to create more detailed assessments of a borrower’s ability to repay.
AI Could Transform Lending, Fraud Detection and Customer Service
Lending is only one area where financial institutions are increasing their use of AI. Banks are already deploying AI tools for customer service, operational automation, risk monitoring and fraud detection. More advanced systems could analyse transactions in real time and identify unusual behaviour before losses become significant.
For customers, AI could also make financial products more personalised. Instead of offering the same loan, insurance policy or investment product to a large group of customers, AI systems could potentially analyse individual financial behaviour and recommend products based on specific needs.
The next step could be agentic AI, where software does more than provide recommendations and can actually perform actions on a user’s behalf.
India is reportedly preparing a framework that could allow AI agents to make small UPI payments without requiring users to approve every individual transaction. Early applications could include routine purchases such as groceries, while more advanced uses could eventually allow AI agents to place orders based on price limits or make investments according to instructions set by customers.
Such a system could turn UPI from a platform that simply enables payments into an infrastructure through which AI agents can independently execute financial instructions.
The Biggest Challenge Will Be Trust and Regulation
The opportunity comes with significant risks. Giving AI greater control over financial decisions raises questions about privacy, cybersecurity, bias and accountability.
An inaccurate AI lending model, for example, could incorrectly reject a legitimate borrower. A compromised AI agent could potentially make unauthorised transactions. There could also be difficult questions over responsibility when an automated system makes a financial mistake.
This is why the RBI has been urging banks to treat AI adoption as a strategic issue rather than simply another technology project. Malhotra has stressed that financial institutions need to understand the systems they deploy and maintain appropriate human oversight.
India’s advantage is that AI would not be developing in isolation. It can potentially be built on top of a large digital public infrastructure ecosystem that includes UPI and other digital identity and data platforms. This gives Indian financial institutions access to an enormous digital environment in which new AI-powered services can be developed and tested.
The transformation could therefore follow a pattern similar to UPI. The first phase made digital payments fast, cheap and interoperable. The next phase could make financial services more intelligent, automated and personalised.
But the success of India’s AI-finance push will ultimately depend on whether innovation can be combined with strong safeguards. If regulators and financial institutions can maintain trust while allowing AI to develop responsibly, artificial intelligence could become the next major chapter in India’s digital finance story — potentially doing for financial decision-making what UPI did for payments.
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