Nitin Chugh of Perfios warns that regulatory hurdles and the need for human oversight will slow the full adoption of artificial general intelligence in financial services, despite advancements in agentic AI systems tailored for credit assessment and risk management.
The banking, financial services and insurance sector is likely to stay cautious about fully automated decision-making and artificial general intelligence, according to Nitin Chugh, the managing director and group chief executive of Perfios. Speaking at the Global Fintech Fest 2026, Chugh said financial services remain conservative because they are heavily regulated, and that makes a rapid leap to AGI unlikely. He argued that even as automation advances, people will still be needed in the loop, especially where judgement, accountability and risk appetite matter.
That view fits a broader debate in banking, where technology can speed up routine work without necessarily replacing human oversight. Chugh said automation should help underwriters process more loans in a day, but not eliminate them. In his view, the biggest gains are likely to come in repetitive, low-level tasks, while complex decisions in lending and risk will continue to require human review, particularly at larger institutions that are more cautious about exposure and due diligence.
Perfios used the event to unveil what it describes as an agentic AI operating system for financial firms. The company says the platform is designed to help lenders assess credit using everyday data, including dairy payout records and UPI transactions for rural borrowers, as well as GST, trade and banking information for micro, small and medium-sized enterprises. It also claims the system can support access to government schemes such as PM Mudra and PM Vishwakarma, and provide young customers with budgeting and investment guidance based on spending patterns.
Chugh said the appeal of AI lies in handling unstructured data, which is harder for humans to process consistently at scale. He pointed to village-level indicators such as weather patterns, flood or drought risk, market access and public services as inputs that can help build a more complete risk picture. Krishna Chaitanya B, Perfios’ chief product officer, added that firms should be selective about where they deploy AI, warning that large language models can be expensive to run and maintain. Chugh, who joined Perfios after senior roles at State Bank of India, HDFC Bank and Ujjivan Small Finance Bank, has long argued that agentic AI will reshape workflows, but only where ambiguity is low enough for machines to take over first.
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