Overview
Ranvir Singh, Chairman and CEO of Kissht, addressed the CNBC‑TV18 Banking Transformation Summit, stating that artificial intelligence (AI) has progressed to a point where lenders can rely on it to make credit decisions without human intervention. He distinguished between merely automating a lending decision—already common in digital lending—and using AI to enhance the intelligence behind underwriting.
AI‑Enhanced Underwriting
Singh explained that traditional lending focused on a simple binary question: will the customer repay? With AI, lenders can pose a richer set of questions, such as the circumstances under which a customer will pay, early‑warning signals of deterioration, and pattern matching across millions of borrowers. He warned of “false precision” that AI can create, noting that large datasets may still lead to poor conclusions if the underlying interpretation is weak.
Repayment Infrastructure Shift
The discussion moved to repayment mechanisms, where Singh highlighted that the transition from National Automated Clearing House (NACH) to Unified Payments Interface (UPI) AutoPay has made repayment considerably easier and more seamless for digital lenders. He added that the merchant discount rate (MDR) is not expected to materially affect the economics of lending, asserting that customer quality and accurate risk differentiation remain far more critical.
Capital Versus Underwriting Discipline
When asked what Indian fintechs receive insufficient credit for, Singh emphasized their ability to target narrow customer segments with obsessive focus and granular understanding—an advantage he believes is undervalued. Conversely, he argued that the availability of large capital is overrated; abundant funding paired with mediocre underwriting can be highly inefficient. Funding can accelerate growth, but it cannot substitute for strong underwriting discipline.
Strategic Takeaway
Singh concluded that while technology can remove friction and speed up processes, the fundamental discipline of lending—identifying the right customers, distinguishing risk levels, and making consistent decisions—remains unchanged. Fintechs that combine rapid automation with deep, segment‑specific risk insight are positioned to succeed.
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