Do insurance companies really have enough driving data to justify pricing and risk rating for usage-based insurance? Or are they guesstimating? In the first of a two-part series, Susan Kuchinskas investigates.
In the world of usage-based insurance (UBI), Progressive is a rare exception: Its massive amount of driving data – 110 terabytes covering some two million vehicles, 1.5 billion separate trips and more than 10 billion miles driven – allows it to quickly test new rating factors, and to do so with a great degree of accuracy.
"We continue to test new ideas all the time,” says David Pratt, Progressive's general manager of usage-based insurance. “Our research team will come up with a theory for what would predict safe driving. With our big data set, we can test those quickly."
Few other UBI providers are as fortunate. Octo Telematics, which launched its first UBI product in 2002, also has tons of data: 194 billion kilometers of driving performance from two million drivers globally. But most other companies are making educated guesses based on more limited data combined with more traditional ratings factors.
As Nino Tarantino, CEO of Octo Telematics North America, points out, "Today, there is no data standard and no clear understanding of which data and how much is required."
For example, Octo works with seven insurers in the United States and Canada, and each one asks for a different data set to be collected – everything from hard braking and acceleration to how many trips a driver takes and how long the trips are, as well as when and where they occur.
Actuarial guidelines often cite 100,000 earned car years as the threshold for model credibility, says Dwight Hakim, vice president telematics, Verisk Insurance Solutions, a provider of underwriting data and tools for UBI. An earned car year is equivalent to one car being insured for one year.
In traditional motor vehicle insurance, the number of earned car years is used to show state regulators that an insurer’s pricing decision is based on plenty of evidence. This helps reassure regulators, but it also helps agents selling the insurance and potential customers.
"Credibility is particularly important when insurers are constructing a rate plan that might increase premiums," Hakim says. "Regulators need to see a model with high credibility if that model might result in rate increases. Assuming the insurer has a good financial position overall, modest rate decreases are easier to justify."
While using earned car years – or the equivalent in telematics driving data – may be critical when an insurer asks regulators to approve a price hike, it may not be strictly necessary in order to see how different UBI rating characteristics perform, according to Hakim.
Trial first, price later
And in more than one way, that is what many UBI insurers in need of beginning to test or launch UBI programs are betting on.
The assumption that good drivers are self-selecting for UBI programs comes up first as a possible way around the need for a large data set. "Chances are [that] the people who try it are more likely to be safe drivers,” says Thomas Hallauer, research and marketing director for telematics consultancy Ptolemus Consulting Group. “So you know you can offer some kind of discount anyway. You also know they will probably stick longer to your contract."
Another strategy, according to Hallauer, is for UBI insurers to collect an initial data set through trials, and to then revise their ratings as more data comes in. Coming up on one full year of offering UBI in the United States, American Family Insurance used just this approach.
"We feel like we got enough to launch, but as we see the data, we know we need to refine it," says Pete Frey, personal lines UBI program and product manager, American Family Insurance.
Combining telematics data with traditional rating factors, such as age and location of residence, is yet another strategy. The Hartford is one of many U.S. insurance companies to do just that, saying it makes for finer segmentation for its consumers.
"Almost all programs in the United States augment telematics data with other carrier-specific rating factors,” Hakim says. “Assessing the degree of overlap among rating factors to avoid double-counting takes a significant amount of work, but carriers are implementing telematics because they know doing so will help them stay competitive and win market share."
But the benefit of adding more data must equal the cost, Progressive’s Pratt warns. While he agrees that UBI rating will continue to evolve and become more sophisticated, "if it costs a lot to get the information, it's maybe not worth it," he says.
Consumer acceptance is another sticking point. "Everything we use has to be something the customer thinks is fine," Pratt says. "We have to be able to explain to people why it makes sense, why it's actually fair that we do it that way."
Finally, insurers can source larger data sets from third-party telematics data providers, such as Verisk Insurance Solutions, Towers Watson and Octo Telematics.
Verisk offers what it calls “Driving Behavior Database for Modelers,” which makes available to statistical modeling applications data from telematics devices; exposure, premium and loss information on insured drivers; and third-party data including weather conditions, road type and traffic flow.
Towers Watson has a pooled data offering that collects telematics data and claims, policy, vehicle and driver information. And it uses this pooled data to score drivers and to provide those scores to insurers. Also available from Towers Watson are models that take into consideration third-party information like maps and weather, road type, population density, weather and angle of the sun.
Octo’s Insight Centre collects global, real-time data gathered from its installed base of Clearbox telematics devices, which customers can then interrogate in order to inform their UBI offerings.
However, there are caveats when it comes to using pooled data.
Hakim, for example, warns that while amassing large quantities of data is critical, not all data is equally valuable. Its utility depends on its accuracy and completeness; how frequently it's sampled; and the source – whether OBD2 outputs, GPS or accelerometers in cell phones.
"Knowing how each device works and the manner in which the different technologies interact is key,” he says. “The complexities of reading the car’s diagnostic information, appending accelerometer data and then transmitting [it] wirelessly require a deep bench of experience.”
American Family Insurance’s Frey makes a similar point. The availability of aggregated, third-party data is not the issue, he says. While there are plenty of companies offering to provide data to insurers, "carriers are just trying to figure out how to use it,” he says. “The data is almost overwhelming."
Susan Kuchinskas is a regular contributor to Telematics Update.
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