Auto-insurance experts are falling into two camps regarding the future of telematics: good drivers will choose telematics policies that will ultimately be cheaper than classic policies, or bad/new drivers will choose telematics policies to build or improve their experience before switching to a classic policy.
Celent outlined these two hypotheses, termed "self-selection hypothesis" (good drivers opting for telematics) and "null hypothesis" (bad drivers choosing telematics) in a recent report, "Innovation in Focus: The Great Telematics Experiment."
According to the report, the null hypothesis assumes that drivers and car owner will prefer classis auto-insurance policies. "Here, we assume that customers don't want insurers spying on their movements, that capturing the data is expensive and that the data doesn't provide significant advantages in pricing and underwriting," Celent states.
The firm adds that telematics policies would, in this case, be a "stepping stone" for some to ultimately get a classic policy at a reasonable cost. Drivers with poor history, or who need to build up experience to prove they can be good risks, would use telematics policies as "a first rung on the ladder" toward a classic policy.
Classically insured drivers, too, may opt for a telematics policy if they have an at-fault accident and want to prove they can be a better driver.
Meanwhile, the self-selection hypothesis contends that bad drivers will fail to get rewards from telematics policies and will ultimately opt for cheaper classic policies. "The classic policies then become less profitable over time due to the population of bad drivers," Celent says. "The premiums for classic policies necessarily increase over time as the book of business increases in risk and the good drivers self-select to the telematics policies."
Which side is correct? Celent says it is still up in the air. "Actually this is the beauty of this great experiment: the answer isn't clear yet," the report states.
Celent offers comments on two factors that could tip the scale toward one hypothesis over the other: the cost of telematics-based insurance, and people's willingness to share their data.
Regarding the costs, Celent notes, "The devices cost money. Transmitting the data captured in this process costs money. Storing the data costs money. Analyzing the data costs money. In short, there are an array of costs associated with capturing and leveraging this data."
But Celent adds that these costs are dropping over time as technology evolves. Advances in both consumer and auto technologies "offer routes to low-cost, effective telematics-based solutions," Celent says, noting that over the next decade, newer, cheaper models for delivering telematics-based insurance should come to market.
As for sharing data, Celent says, "Recent concerns over NSA activities in America, over the use of drones and the deployment of closed circuit TV and road cameras have highlighted privacy issues and concerns in the general populace."
However, Celent notes that the rise of social networks and the "trend of 'checking in' to locations on Facebook and Foursquare suggest that some people don't mind sharing information for the right rewards—whether financial or non-financial."
The key for insurers, according to Celent, is to offer rewards and benefits to customers that they would be willing to accept in exchange for less privacy. Regulators, meanwhile, would be tasked with protecting consumers in this new environment while not stifling innovation in this space.
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