By Nochiketa Dixit, Managing Director – Industries, EDME Insurance Brokers
Car insurance in India has long worked on a simple, blunt formula: price is set mostly by the vehicle’s engine size and the city it’s registered in. That formula is breaking down. AI and a fast-growing insurtech industry are pushing motor insurance toward something more precise pricing and claims that actually respond to how a person drives, not just what they drive.
Premiums Are Starting to Follow the Driver, Not Just the Car
Two drivers with similar cars in the same city used to pay near-identical premiums, regardless of whether one drove cautiously twice a week and the other drove aggressively every day. Usage- and behaviour-based add-ons like Pay As You Drive and Pay How You Drive are correcting that. A driver who covers fewer kilometres, or drives more carefully, can now access a plan priced closer to their actual risk rather than a citywide average. Several major Indian insurers already run products built on this logic, and adoption has been accelerating as AI-based underwriting matures.
That maturity shows up in speed as much as accuracy. Underwriting that once took several days of manual review is now being compressed to a matter of minutes for standard products and motor insurance backed by telematics data is one of the categories where this is already working at scale in the Indian market. For a customer, that means going from “I want a policy” to “policy issued” almost instantly, rather than waiting on a manual approval cycle.
What Data Actually Drives This
Behaviour-based pricing runs on data collected through a telematics device or a connected app always with the driver’s consent. The model typically looks at four signals: distance covered, typical speed, braking and cornering patterns, and the time of day the car is driven most. An AI model turns these signals into a personalised risk score that shapes the premium.
Crucially, this is opt-in. A driver who doesn’t want to share this data simply stays on a standard policy at the regular price no one is pushed into behavioural pricing without agreeing to it first.
Claims: From Days to Minutes
The clearest everyday change is in claims. Instead of waiting for a surveyor to physically inspect a dented bumper, many routine claims today can be resolved through a phone. A driver photographs or records the damage, and a computer-vision model trained on large volumes of historical repair data identifies the damaged parts and estimates repair cost. Some insurers now let customers submit a self-recorded video for minor damage, letting straightforward claims settle without an in-person inspection at all. Complex or high-value claims still go to a human team; the automation is built for speed on routine cases, not to remove judgment from the harder ones.
This matters more than it might seem. Claims experience not price or onboarding is now understood to be the biggest single driver of whether an Indian customer renews their policy. A large share of customers who have a poor claims experience simply don’t come back, which is why insurers are increasingly treating claims automation as a retention strategy, not just an efficiency play.
More Precise Pricing, With a Real Trade-off
The underlying shift is from group-based risk pricing to individual risk pricing. Insurers traditionally bucketed drivers by vehicle type and city, which meant careful drivers quietly subsidised riskier ones in the same bucket. AI-driven models narrow that bucket sharply, rewarding consistent, safe driving with a lower premium.
The trade-off is data. A discount tied to driving behaviour only works if the driver agrees to share that data a genuine privacy decision, not a formality. It’s worth comparing, across insurers, what data is collected, how it’s used, and what saving it actually delivers before opting in.
The Ecosystem Behind the Shift
This is backed by real scale. India’s insurtech sector now counts more than 150 active players, cumulative valuations above USD 15.8 billion, and revenues that have grown roughly tenfold since 2019 to around USD 0.9 billion in 2024. A couple of players have reached unicorn status. And the money is increasingly going into underwriting, pricing, and claims infrastructure rather than just distribution meaning AI’s role here is set to deepen, not plateau.
One caution worth noting: across the industry, most AI pilots don’t make it to full-scale deployment only a small fraction do. The gap usually isn’t the algorithm; it’s whether an insurer’s underwriting, pricing, and claims systems are built to work together. That’s the real work ahead for Indian insurers over the next few years.