Data greatly reduces the severity of claims payments, and carriers that incorporate third-party data and analytics into the claims lifecycle reduce bodily injury and property damage settlements, according to a recent study by LexisNexis.

LexisNexis analyzed more than 10 million features from A.M. Best's top 20 carriers and details the results in its “More Data, Earlier: The Value of Incorporating Data and Analytics in Claims Handling” white paper.

Acquiring more data reduces third-party bodily injury indemnity payments by 25%, the study reports. “More” data is identified as a telephone number and at least two other data elements, such as license plate, address or vehicle identification number. Data reduces the average expense by 47%, the average attorney fee by 25% and shortens the average cycle time by 14%.

When selecting a claims data and analytics provider, carriers should look for solutions that:

  • Offer a configurable, single point of access that allows adjusters to initiate searches with minimal data, such as name and address, phone number or license plate number
  • Provide sequential ordering, which streamlines the process and provides maximum information with minimum effort
  • Return data in structured format, to enable downstream analytics and maximum utility for fraud models
  • Automatically score claims at first notice of loss—and continually monitor claims for new information or indicators that they may need additional attention
  • Draw from extensive data sources that include structured and unstructured data, public records information and more, and link disparate pieces of information to derive insight
  • Provide access to industry-wide data, typically through a contributory database; access to the industry-wide dataset is critical for effective identification of organized fraud
  • Offer non-FCRA data solutions, to minimize regulatory requirements.

LexisNexis' study included data from 400,000 third-party bodily injury features and 1.8 million property damage features. Claims were reported between Jan. 1, 2011, and Oct. 31, 2012, and were closed by Dec. 31, 2012. Features were segmented by certain data: name, address, phone, plate/state or vehicle identification number.

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