Indian Fintech Moves Beyond AI Demos

What happened

AI is all set to take centre stage at the Global Fintech Fest (GFF) in Mumbai this week, with product launches, live demos and industry conversations on how this emerging tech is reshaping financial services. But beyond the buzz, the bigger story is how deeply AI-powered systems are entering the Indian fintech stack, from customer onboarding and credit decisions to fraud detection, servicing and payments.

These constraints are not stopping adoption, but shaping the ecosystem. Currently, the main regulatory and compliance issues faced by Indian fintechs include: India’s payment ecosystem also has safeguards in place to make transactions more secure. For instance, card details need to be encrypted and cannot be exposed to or stored by an AI agent.

However, the bigger challenge is that very few people are using AI agents to make payments today. 04% of UPI’s total transaction volume. This dataset is still too small for payment companies and merchants to understand how consumers behave when an AI agent is making purchases on their behalf.

The conversations ahead of GFF point to a fintech ecosystem that is increasingly focused on scale, but not yet equally prepared for the cost of scaling. Kowta said less than 10% of bank budgets currently go towards AI, with spending often taking place project by project. However, he expects the approach to change over the next one year.

Smaller banks may slow down their AI plans, while larger banks could commit significantly bigger budgets, potentially investing ₹500 Cr to ₹1,000 Cr at one time to build shared infrastructure, governance and AI capabilities rather than funding disconnected projects. For now, much of the industry is still in an AI computerisation phase. It is using the tech to perform existing tasks faster.

The bigger change will come when banks redesign workflows around AI instead of adding an AI assistant to an old process. The message from the ecosystem is not that AI adoption is slow. It is moving quickly in customer service, onboarding and fraud prevention.

He argues that no lab has solved alignment and monitoring well enough to continue scaling at maximum speed for much longer.

Why it matters

To understand where the industry stands and where it is headed, Inc42 spoke with senior executives from Zeta, HyperVerge, TruCommerce and RevRag AI, who are participating in the seventh edition of GFF.

The experts believe Indian fintechs have moved beyond the proof-of-concept phase: voice agents are handling customer interactions, AI is accelerating KYC and verification, fraud systems are becoming more sophisticated, and in-app assistants are beginning to execute tasks rather than simply answer questions. The next challenge is figuring out where these applications can deliver measurable value, and how far fintechs can take them without compromising trust, compliance and accountability.

So, where is AI delivering the most immediate value for fintechs today? Let’s unravel in this edition of The AI Shift… Fintech companies are using AI to make existing processes faster and more efficient rather than letting it make financial decisions on its own. Kedar Parikh, the CPO of HyperVerge, an AI-powered identity verification and KYC platform, divides the sector’s adoption of AI into three broad phases.

This pattern is visible in customer service as well. According to Sivaram Kowta, the president of digital banking at Zeta India, a digital banking and card-issuing technology company, customer support, fraud management and underwriting are among the most active areas for AI adoption. Zeta’s AI agent resolves around 80% of customer-service calls for US-based subprime credit-card fintech Sparrow, Kowta said.

Singh said the next wave of deployment will go beyond contact centres, with fintechs, banks and non-banks such as PhonePe and Bajaj Financial Services exploring AI across in-app journeys, back-end workflows, branches, kiosks and other customer touchpoints. He expects these use cases to move from early deployments to broader scale across the BFSI sector by the end of this year and into next year.

The closer AI gets to a financial decision, the more difficult deployment becomes. In lending, for example, an AI system can collect customers’ financial history, classify information and apply existing rules but cannot become the final authority to approve a loan. Kowta said the RBI has made it clear that regulated entities cannot shift responsibility for credit decisions to an AI model.

A bank must understand the decision and remain accountable for it. As a result, banks and NBFCs are using AI in underwriting while retaining a human at the final decision point. If every other step in the lending process is automated but the final credit review remains manual, the overall process may become faster, but it does not become fully autonomous. The compliance challenge is more complex.

What to watch

But the next jump, allowing AI to influence decisions involving money, will depend on whether Indian fintechs can build the compliance and accountability layers that make those systems trustworthy. OpenAI chief scientist Jakub Pachocki published a striking essay titled “An Alien Mind,” warning that increasingly capable systems may develop goals misaligned with human values.