Data tells all: consumers who own and subscribe to vehicles show similar risk profiles
When we sought out to improve insurance premiums for car subscription companies, we combined forces with Clutch Technologies and turned to the only source that could provide concrete answers—the data. Leveraging our roots steeped in risk assessment from an insurer’s perspective, we made a plan, made a model, and got to work.
Vehicle Subscription Services
As vehicle subscription services grow in popularity, insurance carriers are figuring out how to provide the most accurate insurance premium for these companies. But, with no historical data to provide insight on the best approach, carriers are left wondering how to measure the exposure for this relatively new model.
As one would guess, this lack of understanding can lead to more conservative pricing, a challenge for those who want flexibility in how they own cars.
But, working with Clutch, the Atlanta-based technology company specializing in subscription and mobility products, we had an idea. Could we combine resources to change the way insurers evaluate the risk of vehicle subscription drivers, and potentially reduce the uncertainty in underwriting and pricing?
Putting the Hypothesis to the Test
We proposed that the risk of people who use subscription services could actually be similar to those who have a personal auto insurance policy, a.k.a. everyday people who own and drive their own cars. And to test this idea, we turned to our very own proprietary model, Arity PreQualSM.
PreQual ranks drivers from safest to riskiest, based on the expected relative risk for a driver. The model was developed by analyzing the statistical relationship between a driver’s profile and expected loss.
Clutch, in their Atlanta lab, applied a set of screening technologies during the initial subscription registration process to identify consumers who were more likely to be good custodians of subscription vehicles. The research was then conducted, using our proprietary model, PreQual to score a sample set of 1,456 subscribed drivers across 228,000 driving days of data.
After analyzing the sample set, we found key similarities between the risks that vehicle subscription and personal lines drivers present on the road.
From the study, we learned that …
- The risk profiles of Clutch’s Lab customers and traditional car owners are similar. We found key similarities in their distributions of risk, meaning that these groups may have more in common that we’ve yet to explore. And more to the point, there is an opportunity to keep exploring data that can improve the accuracy of matching premiums to exposures in subscription offerings.
- Commercial and personal lines auto insurance carriers can use PreQual to evaluate driver risk. We used PreQual to analyze the risk of Clutch’s Lab customers as an insurer would, through observed pure premium and exposure. We found that the model appropriately ranked the risk of their drivers, which means that our predictive model can offer insights on the risk of drivers who use car subscriptions and potentially other types of sharing economy.
Needless to say, these were results that Clutch could immediately put into action.
Here at Arity, we’re working with sharing economy companies and insurance carriers to create solutions fit to meet the needs of an evolving transportation industry—and we think the findings discovered through partnering with Clutch is only the beginning!
To dig into the data details and find out what else Arity PreQual revealed about the risk of Clutch’s Lab drivers, download the case study today!