When Car Insurance Starts Paying Attention to How You Drive

The Case for Pricing Insurance on How You Drive, Not Who You Are

(Kenzhar Sharap)

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For most drivers, renewal season feels like a quiz they never took. A number appears in an email, the explanation is buried in the fine print, and the logic might as well live in another galaxy. Zego, a UK-based motor insurance provider, is betting that behaviour-based data can do a better job than the usual checklist of age, postcode, and job title.

Through its Sense product and focus on telematics insurance, the company wants pricing to reflect actual driving, not just whatever boxes someone ticked five years ago. That change could gradually alter how people think about fairness in auto insurance.

When Proxies Stop Feeling Convincing

Traditional underwriting leans on hard proxies. Drivers get grouped by where they live, what they do for a living, and what they drive. Then, they’re priced accordingly. A cautious delivery driver on quiet routes might share a bracket with someone who spends weekends racing to the coast, simply because their details look similar on paper.

Behaviour-based models aim to bridge the gap between those categories and real journeys. They look at factors such as braking, acceleration, and late-night mileage, building a picture from thousands of trips rather than relying on a single form. The appeal is obvious: if risk lives on the road, the data should come from there.

Telematics Without the Spy-Box Reputation

Telematics has been around long enough to collect baggage. For many drivers, it still conjures images of a black box glued under the dashboard, silently judging every turn. Zego’s Sense product offers a cleaner, less intrusive version of that idea.

Data comes from smartphones and modern processing, rather than clunky hardware installations that require a calendar appointment. Instead of hiding everything behind a single, vague score, the aim is to provide drivers with clear, actionable feedback on patterns over time.

Behaviour-Based Underwriting and Fairness

Fairness is where the conversation gets interesting. If insurers want drivers to share more information, those drivers expect something in return. Behaviour-linked pricing may feel more legitimate when people can see how specific choices show up later. Repeated harsh braking, regular speeding, or consistently smooth driving can be tied to a renewal quote in a way that feels less arbitrary than a surprise increase.

Zego’s history in higher-exposure segments such as food delivery, private hire, and business vans provides a large sample of real-world risk. Those lessons flow into Sense, where steady, low-risk behaviour can be recognised over time rather than getting lost within a broad demographic band.

Turning Messy Journeys Into Useful Insights

Raw telematics data is chaos. A single commute can generate readings on speed, distance, location, and phone movement, multiplied across days, weeks, and months. Zego relies on data processing and AI tools to interpret those numbers in the background. Sense then turns it into something a human can actually read.

Drivers can see trends rather than one-off scoldings: smoother weeks, recurring risky habits, or late-night runs that are starting to add up. The tech remains largely invisible, while the output appears in small app moments, such as session recaps and renewal calculations that tie back to those patterns.

Trust, Transparency, and What Drivers Will Tolerate

Each part of this process depends on trust. Behaviour-based insurance only works if people believe the interpretation is fair and consistent. Zego positions Sense around recognition, while some insurance companies are more interested in punishment. That emphasises clear explanations, without the mysterious scores that never quite add up.

The company also uses AI internally to refine modelling and reduce friction in customer experiences, enabling teams to focus on calls and cases that still require human intervention. Behaviour-based coverage may not eliminate every traditional factor overnight, but it moves the industry toward a model that more closely reflects how people actually drive.

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