LexisNexis Risk Solutions, a provider of data, analytics and technology for the insurance industry, has announced the launch of a new LexisNexis Drive Metrics scoring model, a telematics-based scoring model for the auto insurance industry.
The new scoring model will be available for testing through LexisNexis Telematics OnDemand. It is designed to flow seamlessly into insurers’ existing auto insurance ratings programs to improve segmentation, pricing risk and profitability.
Telematics OnDemand will be the first LexisNexis Telematics Exchange product to offer scores using the new Drive Metrics scoring model. The scores, arrived at through analysis of driver behavior data, can help carriers form a more accurate risk assessment, both at point of quote and renewal. It also helps carriers with no prior experience in telematics to quickly leverage a large volume of driving behavior data accrued from more than 29 billion driving miles and hundreds of thousands of recorded claims.
LexisNexis Risk Solutions said the new scoring model is compatible with carrier-specific ratings plans and delivers a 79% additional lift above standard rating factors – with the potential to increase future performance of the model even more as additional driving behavior attributes are added.
“Adding Drive Metrics to our Telematics OnDemand solution represents the next stage in the [usage-based insurance] evolution,” said Adam Hudson, vice president and general manager, Connected Car, at LexisNexis Risk Solutions. “Insurers want as much information as possible about all of the variables that comprise a true picture of risk propensity, while consumers expect a more streamlined and personalized experience for sharing their telematics data. The level in which we’re able to normalize telematics data and deliver actionable driving behavior insights in the form of both scores and attributes in seconds is not only an exciting prospect, but one of greater possibility as we look to extend this powerful new scoring model to other exchange-based solutions.”
