[Student IDEAS] by Mingyou Yuan - Master in Management at ESSEC Business School
Car insurance is no longer just about who you are, but how you drive. As connected vehicles quietly share drivers' every move, premiums increasingly depend on algorithms and invisible data exchanges. This article explores how the digitization of auto insurance is subtly rewriting society’s fundamental contract of shared risk and fairness.
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Kenn Dahl couldn’t understand why his car insurance jumped 21% overnight. The Seattle software entrepreneur had a spotless driving record, yet his insurer hiked his premium with no warning. Puzzled, Dahl shopped around for quotes from other companies – only to find they were high as well. Finally an agent hinted at the culprit: Dahl’s own car. By invoking consumer data laws, Dahl obtained a 258-page file from LexisNexis, a data broker, detailing every trip he’d taken in his Chevrolet Bolt over six months – 640 journeys, each with start time, distance, and counts of hard brakes and rapid accelerations. General Motors (GM), it turned out, had been quietly sharing Dahl’s driving behavior via its OnStar connected-car system, feeding an algorithm that flagged him as a higher risk. “It felt like a betrayal,” Dahl later said, “They’re taking information that I didn’t realize was going to be shared and screwing with our insurance.” His baffling rate hike was no glitch – it was a preview of a revolution sweeping auto insurance, powered by the constant digital chatter of our cars1,2.
For over a century, car insurance has been a game of averages. Insurers pooled drivers into broad categories by age, gender, location, and vehicle type, spreading the costs of accidents across many policyholders. A young city-dweller with a sports car paid more than a middle-aged rural minivan driver, but within those groups everyone paid roughly the same. This traditional model of risk pooling treated driving behavior as a black box – individual habits were largely invisible, so premiums were based on proxies and population stats3. Now that black box has been flung open. Usage-based insurance (UBI), once a niche idea, is moving into the mainstream. Instead of setting rates solely on who you are and what you drive, insurers are increasingly looking at how, when, and even where you drive, in real time.
Today’s vehicles are effectively rolling computers with wheels – and they’re online. Over 85% of new cars sold in 2018 came with built-in wireless connectivity, and by 2025 an estimated 470 million connected cars will be roaming roads worldwide4. These cars can stream a rich flow of real-time information: not just how far or how fast you drive, but how precisely you drive. Did you accelerate hard out of that last turn? How often do you forget to signal lane changes? Do you habitually speed in rainy weather? Your car knows – and increasingly, so do insurers. AI algorithms crunch data from vehicles to classify drivers into finely graduated risk categories, from very conservative to extremely aggressive, based on dozens of cues. For example, a telematics system might note that one driver rarely exceeds speed limits and always uses turn signals, while another routinely brakes hard and changes lanes without signaling. Even external conditions can be factored in: the system can tell if you blast down the highway during a downpour or fail to dim your high-beams at night. The result is an individualized risk profile – and a premium tailored to match. As one telematics analyst quipped, traditional insurers grouped people by the law of averages, but connected cars allow pricing by “the correctness of a computation” for each driver5.
The sheer volume of data captured by connected vehicles is transforming how insurance works. Instead of a static annual premium, pricing can adjust dynamically. Your behavior behind the wheel this week could nudge your bill up or down next month. It’s a far cry from the old days of set-it-and-forget-it policies. Insurers are also tapping connected-car data for claims and safety services: vehicles can automatically report accidents with precise telematics, helping adjusters reconstruct what happened and even detect fraud.
The benefits of this data bonanza are often touted in rosy terms. Advocates argue it rewards safe drivers with lower rates, encourages better habits through instant feedback, and can even save lives by reducing crashes. Usage-based insurance also promises a fairer shake for those who drive less or drive more carefully than their demographic peers. Why should a 25-year-old who never speeds subsidize an occasionally reckless 50-year-old, or vice versa? With enough data, everyone pays truly “their own share.” That’s the upside.
But Dahl’s experience highlights the darker side of connected-car insurance: questions of privacy, consent, and control. The data that empowers personalized pricing also empowers unprecedented surveillance. In Dahl’s case, the fine print of his car’s telematics service (GM’s “OnStar Smart Driver”) enrolled him by default in a driving data program that he didn’t even realize existed. GM later said the program was optional and that drivers can opt out, but Dahl and others were stunned to discover their cars had essentially been “snitching” on them to data brokers and insurers without explicit consent. Many automakers have similar systems: Kia, Subaru, Mitsubishi, Ford, Honda, and others feed driver data into telematics exchanges run by firms like LexisNexis and Verisk. Often pitched as safety or “smart driving” features, these services can end up funneling information to insurers (and who knows who else) if the owner opts in – and sometimes even if they are only “opted in by default.” The result is that a driver might be diligently installing a seatbelt for safety while their car quietly transmits a dossier of their every driving habit to a third-party cloud.
It’s often said that in today’s economy, data is the new oil – a lucrative resource fueling industry power. In the auto insurance arena, we’re witnessing a three-way tussle for that resource between insurers, automakers, and consumers. Insurers see telematics data as a goldmine: more data can refine their risk assessments, reduce claims costs, and give them an edge in a brutally competitive market. Automakers, meanwhile, realize they now own the pipeline that generates this oil. A connected car continuously produces valuable information, and the car’s manufacturer can decide how to share it – or not. This has led to growing friction: insurance companies (and other service providers like repair shops) have been lobbying regulators to force open access to vehicle data, arguing that drivers – not manufacturers – should decide who gets their driving info. If automakers alone hold the keys, an official with Insurance Europe warned, they could effectively choose which insurers are allowed to compete for a car owner’s business. Put plainly, if your car’s data is captive to the manufacturer, you might also be captive to that manufacturer’s preferred insurance deal.
Where does this leave consumers? Potentially with more choices, but also new trade-offs and power imbalances. On one hand, a driver could enjoy ultra-personalized coverage: hop in your connected car, drive gently, and watch your insurer (whether traditional or automaker-backed) trim next month’s bill. On the other hand, refusing to share data may increasingly carry a penalty. If all the best rates go to those willing to be monitored, those who opt out might be assumed “high risk until proven otherwise.” In a data-driven market, opting out of surveillance could mean paying a premium for privacy. There’s also the concern of transparency: the algorithms scoring drivers are often proprietary. Drivers might get a vague grade or “driving score,” but the exact formula is a black box. If your premium goes up, was it because of that one late-night run to the store? Or a few too many hard brakes when a squirrel ran into the road? Insurers aren’t obligated to tell you in detail. Dahl, for instance, only discovered his risk score after demanding his LexisNexis report; most drivers would never go that far.
Fairness is another contentious issue. Insurance has long held a quasi-social role: the risk of a few is shared by the many. In technical terms, it balanced individual fairness (you pay for your own risk) with solidarity fairness (we’re all in this together)6. The advent of big data tilts that balance decisively toward the former. Modern algorithms increasingly pursue a “scientific adjustment of premiums to actual individual risks,” effectively dismantling the old notion of solidarity. Instead of the collective smoothing of fortunes, we get a precise (if unforgiving) personalization. To a safe driver, that sounds great: why should I subsidize bad drivers? But society might ask a broader question: what do we do about the drivers deemed “bad” or high-risk? If constant monitoring identifies a small subset of chronically risky drivers – be it due to aggression, distraction, or just bad luck – their premiums could skyrocket beyond reach. In the past, those drivers were partly buoyed by the pool; now they must sink or swim on their own data. The social contract of insurance is subtly shifting. We may eventually view auto insurance less as a shared safety net – smoothing out the random misfortunes of driving – and more as a direct scorecard of personal responsibility (or irresponsibility). For better or worse, the moral calculus of the road is becoming individualized.
All the while, regulators are scrambling to catch up. Privacy advocates worry about the lack of consent and disclosure in how driving data is collected. Some U.S. states have begun enacting laws to require that insurers clearly inform customers if a device or app is tracking them and what data is being gathered. New EU laws are in the works to ensure “fair access” to vehicle data for all market players, aiming to prevent monopolies and give drivers the right to share (or not share) their car’s data as they please7. Lawmakers are trying to redraw the rules of the road for data, to keep pace with a world where cars have become smartphones on wheels.
As profound as the changes have been so far, an even bigger upheaval looms around the bend: the rise of autonomous vehicles. If today’s connected cars are reshaping insurance by scrutinizing drivers, tomorrow’s self-driving cars could upend it by removing drivers from the equation entirely. What happens to auto insurance when humans are no longer behind the wheel? We are about to find out, and the stakes are enormous.
The fundamental premise of motor insurance – that a driver is responsible (financially and legally) for accidents they cause – will be challenged once a car’s software does the driving. Liability is already starting to shift from individuals to manufacturers and software developers. Experts predict that in a fully autonomous future, personal car insurance may become almost obsolete, replaced by product liability coverage carried by the car makers themselves8.
We are already seeing early signs of this shift. Consider the legal aftermath of an accident involving a car on Autopilot or a driverless taxi service: courts and insurers have to determine whether the human (who might have been inattentive) or the machine (the AI driving system) is at fault. Increasingly, arguments tend toward seeing advanced driver-assistance systems as taking on responsibility. If a software glitch or sensor failure causes a crash, it starts to look less like a driver’s negligence and more like a defective product issue. In Europe, regulators have mused that traditional notions of driver liability might need revamping – perhaps even requiring autonomous vehicles to have built-in “black box” recorders and specialized insurance held by manufacturers. Car companies might become their own insurers in practice, self-insuring their autonomous tech or purchasing policies that cover entire fleets of robo-taxis.
But one thing is certain: data will remain at the heart of the issue. Autonomous vehicles will generate exponentially more data than even today’s connected cars – not just about driving behavior, but about the performance of sensors, the decisions of AI algorithms, near-miss incidents, and more. This data will be critical for determining fault and improving safety. Insurers (whoever they end up insuring) will demand access to it, and new regulations may be needed to govern its use. We might find ourselves asking: do we need an entirely new kind of insurance system for a world where accidents are rare but potentially caused by opaque machine intelligence? And if accidents drop dramatically in frequency (as many hope with autonomous tech), how do we ensure the insurance industry – which provides an essential cushion when things go wrong – remains viable and ready to respond on the occasions it is needed? These are not just technical questions but societal ones, touching on legal liability frameworks that have been in place since the dawn of the automobile age.
In the span of a generation, auto insurance is moving from analog to digital, from statistical to individualized, and soon from human-driven to machine-driven. It’s a transformation that forces us to wrestle with big questions about privacy, fairness, and trust in a datafied society. The humble car insurance policy, once a staid paperwork ritual, is fast becoming a reflection of something much more personal – our behavior, our choices, even our consent to be monitored. Dahl’s encounter with the hidden world of driving data may have been jarring, but it won’t be the last of its kind. As connected cars proliferate, more drivers will face the choice between sharing data for savings or holding on to privacy at a cost. Policymakers, for their part, must balance innovation with consumer protection: ensuring that the brave new world of individualized insurance doesn’t devolve into a dystopia of constant surveillance or algorithmic discrimination.
At its core, insurance has always been a form of social contract – a pact to collectively support those in misfortune in exchange for a premium. That contract is now being rewritten. The rise of telematics and real-time data is nudging us toward a contract that is less social, more individual, where personal responsibility is measured to the minute and priced accordingly. This brings efficiency and accountability, but also risks leaving some behind. As we drive into this future – or let our cars drive us – we’ll need to decide what we value in the name of safety and fairness. Will we accept a world where every driver (or vehicle) truly “gets what they deserve” in insurance costs, and nothing more or less? Or will there be room for solidarity, forgiveness, and anonymity on the road?
The auto insurance industry’s shift from risk pooling to precision pricing is not happening in isolation. It is part of a larger story of technology challenging traditional norms – whether in finance, healthcare, or employment – and asking us how much of our lives we want to turn into data points. In the end, the future of insurance may be as much about ethics and power as about algorithms and premiums. Your car may soon drive itself and your insurance may quote itself, but the values steering the system are up to all of us. The road ahead, as always, will have twists and turns – only this time, the data will tell the tale.
[1] Autobody News Staff, 2024. Drivers See Auto Insurance Rates Spike Due to Secret Data Sharing. Autobody News, 12 March 2024. Available at: https://www.autobodynews.com/news/drivers-see-auto-insurance-rates-spike-due-to-secret-data-sharing.
[2] Posky, M., 2024. Driving Dystopia: Automakers Are Selling Your Driving Data to Insurance Companies. The Truth About Cars, 14 March 2024. Available at: https://www.thetruthaboutcars.com/cars/news-blog/driving-dystopia-automakers-are-selling-your-driving-data-to-insurance-companies-44505718.
[3] Soldatos, J. and Kyriazis, D. (eds.), 2022. Big Data and Artificial Intelligence in Digital Finance. Cham: Springer. doi:10.1007/978-3-030-94590-9.
[4] Reuters, 2022. EU weighs driver data rules, pitting insurers against auto giants. Reuters, 31 March 2022. Available at: https://www.reuters.com/business/autos-transportation/eu-weighs-driver-data-rules-pitting-insurers-against-auto-giants-2022-03-31/#:~:text=The%20bloc%27s%20executive%20European%20Commission,States%20and%20China%20by%202025.
[5] Barry, L., 2020. Insurance, Big Data and Changing Conceptions of Fairness. European Journal of Sociology, 61(2), pp. 159–184.
[6] Chalkias, K., 2021. That’s Not Fair! Navigating the Duality of Fairness in Insurance. European Journal of Sociology. doi:10.1111/1468-4446.13206.
[7] European Data Protection Board, 2021. Guidelines 01/2020 on processing personal data in the context of connected vehicles and mobility related applications, 9 March 2021. Available at: https://edpb.europa.eu/our-work-tools/our-documents/guidelines/guidelines-012020-processing-personal-data-context-connected-vehicles-and_en.
[8] Greenfield, S., 2024. Autonomous vehicles could render personal auto insurance obsolete by 2044, new report finds. CBT News, 4 October 2024. Available at: https://www.cbtnews.com/autonomous-vehicles-could-render-personal-auto-insurance-obsolete-by-2044-new-report-finds/.