Towers Watson, a global professional services company, has launched of DriveAbility 2.0 Score, a new analytical scoring model designed for the automobile insurance industry.
DriveAbility 2.0 Score includes a GPS version with location-specific factors in the risk model and a non-GPS version. T
he DriveAbility 2.0 Score GPS uses telematics data in conjunction with the actual insured losses to develop and validate the structure and weights of the algorithm for converting policyholders’ driving data into meaningful metrics. The resulting vehicle operation score leads to demonstrable price segmentation for the auto insurance industry.
"The new DriveAbility scoring model enhances automobile insurers’ knowledge about expected losses associated with insured vehicles," said Robin Harbage, Towers Watson’s global leader for its usage-based insurance (UBI) consulting practice. "The new offering also captures specific driver behaviors not previously available and adds predictive power to claim models."
DriveAbility 2.0 Score uses granular, second-by-second data, which allows for a continuous study of driving behaviors rather than predefined events that occur at a single point in time. It also enables the use of historical data to study newly defined driver behaviors, as these behaviors can be programmed on top of the historically collected data, and maps insurance claims to the exact moment they occur, leading to scores reflecting driving behaviors that actually cause claims.
DriveAbility 2.0 Score was developed based on an analysis of pooled telematics and insurance data collected from the Towers Watson UBI program. Towers Watson has been aggregating these data since 2010, compiled from the enrolled insureds of multiple insurers in the U.S.
"By aggregating this large pool of data and using our proven analytic techniques, we have created a vehicle operation score that we believe has pricing segmentation more than three times greater than rating variables typically developed," said Harbage. "This is the only vehicle operation score created by analyzing telematics data in conjunction with actual insured losses collected from multiple independent insurers. It provides a clear, cost-effective way for insurers to go to market with a UBI product and will benefit policyholders, too, by helping improve their driving habits."