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AI Moves Beyond Chatbots to Core Fintech Functions
Fintech companies in India are deepening their AI integration, shifting from customer-facing tools like chatbots to critical backend operations. This includes AI deployment in underwriting, advanced fraud detection, Know Your Customer (KYC) processes, debt collection, customer support, and compliance monitoring. AI is also being used to improve engineering workflows and internal productivity.
This accelerated AI adoption is a direct response to the massive growth in digital transactions. India saw over 22.64 billion Unified Payments Interface (UPI) transactions in March alone, a volume that makes manual oversight difficult. "AI has clearly moved beyond the experimentation stage and is now becoming deeply embedded into our operational and technology framework," said Rohit Mahajan, CEO of Plutos ONE, whose company uses AI for compliance, onboarding, and operational support.
Fighting Advanced Fraud with AI
New generative AI tools are creating more sophisticated phishing and scam attempts, posing challenges for existing fraud detection systems. A study found that most Indian organizations feel current KYC systems are insufficient against AI-generated fake documents, with GenAI seen as a significant fraud threat. Payment provider PayU uses AI for real-time fraud monitoring. "Payment fraud moves at machine speed," stated Manas Mishra, Chief Product Officer at PayU and Wibmo. "The real-time monitoring layer is increasingly AI-led, but human expertise remains critical for governance, investigations, regulatory judgement, and complex escalations." PayU's AI handles constant monitoring and pattern recognition, while human teams focus on strategic investigations.
Profitability Drive Pushes AI Adoption
With funding slowdowns and increased market scrutiny, fintechs are seeking operational efficiencies and cost reductions through AI. Gaurav Gupta, Senior Vice-President at Payoneer, noted AI's deep integration in product development, R&D, customer support, compliance, and growth. "An execution layer changes how work gets done, with AI handling more of the workflow and humans supervising and making the final calls where needed," he explained. While AI helps firms scale without proportional headcount increases, experts emphasize it's not solely a cost-cutting measure. "There is strong evidence of cost reduction in areas where AI has moved beyond experimentation," commented Vijay Mani, Partner at Deloitte India.
AI Boosts Lending, Support, and Engineering
Lending and underwriting are key areas for AI. Fintech lenders are using alternative data for credit assessment, behavioral scoring, and real-time risk monitoring. The Reserve Bank of India (RBI) Governor has encouraged banks to use AI for better customer grievance handling, leading to multilingual AI support and conversational interfaces. PayU uses AI-assisted systems for about 30-40% of initial merchant queries. Technology teams are also adopting AI coding assistants and automated testing to speed up development.
Governance and Accountability Challenges Remain
Despite rapid adoption, challenges in AI governance and accountability persist. Issues like explainability in lending, bias, and AI hallucinations are major concerns in finance. "At PayU, responsible automation matters more than full automation," said Mishra. "Areas involving money movement, regulatory compliance, sensitive data, and customer protection must continue to have human oversight." Deloitte's Mani added that true AI impact will come from redesigning processes with AI in mind, balanced with governance. Larger platforms might gain an edge with more data, but AI alone doesn't replace solid business fundamentals.