India’s health insurance industry is moving towards more personalised solutions, with technology and generative AI creating scope for products and policy experiences tailored more closely to individual customer needs, according to Niva Bupa’s Ankur Kharbanda. That was the message from Ankur Kharbanda, executive director and deputy chief executive of Niva Bupa Health Insurance, speaking on a panel about the industry’s trust gap at the Global Fintech Fest 2026 in Mumbai on 10 September. Insurance penetration is still low, he said, and the industry has long built for the mass market, but technology now makes targeted cover for specific customer profiles possible.
What Per-customer Cover Looks Like
The shift moves insurers beyond broad demographic segments towards plans built on specific needs. Kharbanda pointed to cover aimed at younger buyers that bundles health insurance with maternity and wellness benefits, and to tiered hospital networks for customers in smaller cities that leave out some premium hospitals in exchange for lower premiums. Someone who already holds an employer health cover of ₹3 lakh to ₹5 lakh, he said, may not need a conventional top-up; a product with a deductible can add protection at a much lower premium and later become that person’s base cover. Over time, he added, technology could analyse a customer’s information and recommend the most relevant product, rather than leaving the buyer to navigate a stack of add-ons and riders.
Where Trust Breaks Down
Trust, Kharbanda said, tends to crack when there is a gap between what a customer believes they bought and what the insurer actually provides. That makes clear, repeated communication at the point of sale important, especially for health cover that may be bought now but used years later. The harder test comes at the claim. He put the industry’s claims settlement ratio above 90 percent and Niva Bupa’s above 95 percent, adding that most unsettled claims relate to waiting periods, with a smaller share coming from gaps between what customers understood and how claims were processed. Cashless discharge remains a sore point, Kharbanda said. He noted that the insurer may take around two hours and the hospital another two to three hours, but customers tend to perceive the entire wait as an insurance delay. Insurers are turning to AI to strip friction out of that journey.
Policies Explained in the Buyer’s Own Language
Generative AI could also let customers deal with their policies in a language they actually understand. Kharbanda suggested people might use WhatsApp or similar tools to ask whether a specific medical situation is covered, or simply ask for the three things that matter most in a policy. That kind of plain-language help speaks to a real problem, since much mis-selling and many disputes trace back to buyers never fully grasping what they signed up for. Independent, commission-free guidance sits in the same space, and MyRupia, which holds no insurer stake and earns nothing on the sale, helps buyers cut through the jargon and match cover to their own situation before they commit.
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