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Hypothetically Speaking about Making Money with Telematics

The idea that a single approach to usage-based insurance (UBI) can solve any problem great or small ignores some simple realities: All insurers aren’t the same. All telematics technology isn’t the same. And all UBI programs aren’t the same. Every business faces a unique set of issues, and designing a UBI program with the right fit involves careful specification of business objectives.

Hypothetically speaking, one insurer may want to reduce large volumes of unprofitable business by using telematics to authenticate basic underwriting information. It may spend $50 per “dongle” device for very basic capabilities, and $2 per month for wireless data transmissions. Assuming a three-year useful life for the devices (that is, each unit can be deployed for one year each in three different vehicles before it goes kaput), technology costs represent approximately 2.5 percent of premiums collected.

Another insurer believes that policyholders who demonstrate safe driving patterns should be able to earn substantial discounts, and those who don’t should be given feedback and the opportunity to improve their safety record. That may likely require a little more technological horsepower: The insurer may spend $75 per device and $3 per month in wireless — which may consume approximately 4 percent of its premiums collected.

A third insurer may lay out $100 per unit and $5 per month for wireless. Insurer number three also plans to offer policyholders one year of value-added services, such as roadside assistance and access to an online portal where they can view their driving habits and seamlessly post routes and locations to social media. It believes the market for new premium is drying up but anticipates consumers will pay $8 per month for those services, meaning its customers could generate new income. But the costs of the technology to support the plan may almost completely negate the new revenues.

With technology costs consuming new revenues, the savings from better driving should offset the costs of any telematics-based discounts (say, 10 percent for the average vehicle) for insurer number three to break even. The loss ratios would have to drop 15 percent to justify a permanently installed dongle.

One way to make the economics better might be to move the dongle to a new vehicle every three months rather than one year. That’s presumably enough time for long-term driver behavior to improve, but at lower cost per vehicle. Using the same assumptions, loss ratios would likely have to fall 11.5 percent to break even, making the economics more workable.

So how do new UBI methods compare with the old? Traditional rating factors such as the age of a vehicle operator do an acceptable job of estimating riskiness. For example, younger drivers are typically thought of as being higher risk, with riskiness decreasing as a driver ages — until, ultimately, a driver reaches a point where his or her reaction time decreases, and he or she again can become riskier. By comparison, basic telematics can track signs of inattentive driving, such as frequent application of moderate pressure to a vehicle’s brakes. Telematics research actually helps reaffirm conventional wisdom by providing evidence that younger operators, on average, brake more frequently, with incidence rates decreasing as operators age — until around age 60, when drivers again appear to brake more often. However, using multivariate modeling approaches, a rating plan can achieve much more significant “lift” than a naïve approach such as shown here. According to vehicles’ telematics-based scores, Verisk Analytics research has found the riskiest 20 percent of operators’ expected claim costs were 10 times higher than those of the least risky 20 percent — even after the effects of a traditional rating plan were considered. That means, using telematics, significant risk differences may be identified even among operators who, in a traditional sense, may appear to be “the same” (for example, belong to a similar age group or garage in similar areas).

It’s true the cost of telematics technology required to support UBI can ­significantly exceed even innovations such as insurance credit scoring, which decreases insurers’ margin for error. Costs include technology, program discounts, and logistics. But analyzing each of those factors and their interdependencies can provide a useful road map for the business decisions necessary to make money on UBI through loss reduction, reduced premium leakage, and new revenue streams

Jim Weiss

Jim Weiss is the director of analytic solutions for ISO, where he helps develop and implements the ISO Risk Analyzer® suite of predictive modeling products and services. Mr. Weiss is also leading new efforts to use social media and wellness analytics in property/casualty insurance. His articles have been published in Carrier Management, Telematics Wire, and Verisk Review, and he often presents insights at insurance industry events such as those sponsored by the Property Casualty Insurers Association of America and the Society of Insurance Research. Jim graduated with a bachelor of science in mathematics degree from Manhattan College and has earned the designations of Fellow of the Casualty Actuarial Society (FCAS), Member of the American Academy of Actuaries (MAAA), and Chartered Property Casualty Underwriter (CPCU).

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