As has been the case for retailers, the medical profession, and financial services, the last few years have been incredibly disruptive for the once staid insurance industry. From competing with insuretech startups to managing the impacts of a changing climate on underwriting homeowner policies. But there’s even more disruption coming down the pike for car insurers according to Greg Donaldson, Senior Analyst at Aite Group.
“Telematics is a rapidly developing field that’s not only fueled by our ability to analyze and apply data through Artificial Intelligence and Machine Learning, but also because we have so many more devices able to capture and communicate data in real-time from the vehicle to the insurer,” Donaldson said. For him, the current telematics-driven programs, like Snapshot from Progressive, are just the beginning and there are “many more aspects to be explore and applied” to the extent that “telematics will be the bridge between the insurance industry of the past and what it will become in the future.”
Traditionally, the insurance industry has relied on static information about a driver or a vehicle in order to write a policy. Donaldson shared that his has resulted in a barely adequate system that not only irritates consumers but creates risk exposure for insurers. “The way policies have always been written is based on the age of a driver, their gender, how far they drive each year, and other factors that are documented in actuarial tables,” he noted. “Based on this information, my 23-year-old daughter, should have higher insurance rates than my 19-year-old son, but, as we all know, my son – who despite all the accrued data is the more careful driver – pays more.”
But two things are working to up-end this traditional static model to deliver more accurate and actionable information to insurers. The first is the increase in the number of data gathering and transmitting devices – like smart phones, OEM equipment, and aftermarket tools — in the hands of consumers and the second is that thanks to the surge of development in AI and ML there’s both the capacity to process, analyze, and apply the data that is being generated.
“All of this data becomes actionable,” said Donaldson. “It can be used immediately at the site of an accident to help the driver get the claims process started immediately. It can be used in accident reconstruction to enable insurers to build a more accurate assessment of what actually happened, rather than relying on witness testimony. And finally, it can be used to develop a more complete and personalized risk profile, which will ultimately have an impact on insurance rates for consumers.”
As Donaldson shared during our conversation, though, consumer adoption of telematics has been slow particularly in the United States. “At the consumer-level I’m seeing more adoption in the European Union,” he said, “but in the U.S. dynamic insurance is favored by owners of fleet vehicles who are looking to minimize risk and manage costs.”
Donaldson attributes part of this lag in adoption in the consumer market thus far with poor messaging and positioning of the value of dynamic insurance. “Insurers have been backwards in coming forwards with the value proposition, but that is beginning to change,” he said. “It’s not enough to offer a consumer a 10 percent discount for installing a device in their car, but when insurers try different tactics, such as encouraging drivers to enable all of their built-in safety devices, like blind spot indicators, adaptive cruise control, or automatic braking, the reaction from consumers is different.”
In many ways this new technology is a bridge to the future for both the insurance industry and the automobile industry. “Understanding human behavior via telematics and the data it produces is paving the way for more autonomous driving features on vehicles,” Donaldson explained.
“Insurers understand driving behavior and its risks, as well as accidents and their causes, much more thoroughly. By feeding this data back to vehicle manufacturers they can incorporate more autonomous functionality into vehicles of the future. This, in turn, leads to more data being generated by the driver and the vehicle, which will ultimately result in better underwriting, better policies, and better outcomes for both consumers and insurers,” Donaldson concluded.
