Towers Watson has launched DriveAbility 2.0 Score, an analytical scoring model designed for application in the automobile insurance industry. This product offering includes a GPS version with location-specific factors in the risk model, as well as a non-GPS version.
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. According to Towers Watson, the resulting vehicle operation score leads to demonstrable price segmentation for the auto insurance industry.
"The new scoring model enhances automobile insurers' knowledge about expected losses associated with insured vehicles," explains 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 claims models."
The product uses granular, second-by-second data, which is designed to allow 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.
Towers Watson developed DriveAbility 2.0 Score based on an analysis of pooled telematics and insurance data collected from its UBI program. The company has been aggregating these data since 2010, compiled from the enrolled insureds of multiple insurers in the United States.
"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," says 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."
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