Newswise – Insurance companies have been encouraging consumers to lower their premiums using monitoring technology for 25 years now, but consumers have been slow to embrace the idea.
First introduced in 1998, the technologies monitor various aspects of customer behavior so that the insurer can better determine their level of risk. For example, drivers install sensors in their cars to monitor their driving habits or wear Fitbit-like devices to track their physical activity. Insurance companies collect the data, analyze it and, using data analysis, offer premium discounts to safe drivers or people who keep themselves in better condition.
According to economic theory, people should be more than happy to purchase these usage-based insurance (UBI) contracts. According to the theory, the devices combat moral hazard, which is the idea that insurance will encourage riskier behavior on the part of an insured because they have insurance to bail them out if something goes wrong. They can also save consumers money. But customers have been resistant. Automotive monitoring devices, for example, have only about 5% global market penetration.
“These were supposed to be the wave of the future, but they didn’t catch on,” said Richard Peter, a finance professor at the Tippie College of Business and insurance expert, who wondered why so many customers missed the chance to save. money on car insurance. In a recently published study, he presents a theoretical model that suggests the algorithm used by insurance companies to determine discounts is too confusing for most people to understand. Since they cannot understand what is going on in the algorithm’s “black box”, policyholders fear being wrongly classified as a bad driver even if they do not take unnecessary risks. The fact that some companies often outsource these algorithms to third parties only further confuses consumers.
Since the whole process seems so mysterious, they take a pass.
“Consumers are saying forget it, I don’t need this technology, I’m sticking with the old contract that I always had,” Peter said.
The sensors also don’t understand the context of what might at first glance appear to be dangerous driving. For example, a driver may have to swerve sharply to avoid an accident. The algorithm could ring the driver based solely on the fact that the driver did something erratic. He will not see that the action was necessary to avoid a crash.
Peter said this was causing further problems for the insurance company, citing a German company that piloted UBI car contracts. He eventually scrapped the initiative because customer service reps were inundated with phone calls from drivers trying to explain why they shouldn’t be penalized for something.
Peter’s study, “Mitigation of moral hazard with usage-based insurance,” was co-authored by Julia Holzapfel and Andreas Richter of the Ludwig Maximilian University of Munich. It will be published in a future issue of the Journal of Risk and Insurancethe flagship journal of the American Risk and Insurance Association.