Enhancing risk prediction with cross market claims data
Authored by Carla McDonald (pictured), director of insurance claims product management, LexisNexis Risk Solutions, UK and Ireland
Insurance providers are already feeling the effects of the cost-of-living crisis through a rise in the number of bogus insurance claims being detected. Aviva recently revealed a 45% surge in fake home insurance claims and Zurich uncovered £4.2m worth of fraudulent property claims this year, equivalent to £40,000 a day. LexisNexis Risk Solutions has also found that people have become more willing to manipulate the information they provide for a motor insurance quote to obtain a cheaper deal, this includes deliberately mis-stating or omitting past claims.
While the environment for fraud both at application and claim is ripe, making accurate detection critical for the market, insurance providers also need to ensure that they price customers accurately and fairly and can justify those pricing decisions to the regulator. It makes sense that in building the picture of risk at all points of the customer journey, a granular understanding of their full claims history across both home and motor would tick a number of boxes – more accurate pricing, enhanced fraud detection, a smoother customer journey and faster claims settlement.
Granular claims data gathered from across the market is far from a new idea – U.S. insurance providers have been using a contributory claims database for around forty years now, allowing those involved, access to an illuminating 360 degree view of historical motor, household and commercial claims data.
As well as the obvious fraud detection advantage; helping the industry flag undisclosed claims at application and spot patterns of behaviour at claim, the vast stores of rich granular data on past claims enables users to make far more finely tuned underwriting decisions. Risk decisions can be made on the totality of an individual’s claims history, enabling insurance professionals to segment consumer risk profiles, charge more attractive premiums and offer customers a high degree of flexibility. It stands to reason that if an insurance provider knows a person’s claims history up front, they are in a far better position to determine the right product for their needs and offer advice on measures they may want to take to reduce the risk of another claim in the future.
Insurance providers across the U.K. can now access their own UK market-wide contributory claims database with cross search functionality. The first two sets of claims data uploaded onto the LexisNexis® Precision Claims database come from the home and motor markets.
Those insurance providers who are part of the contributory database can access home and motor claims data for a person, a property and a vehicle including the type of claim, the circumstances and the settlement. Vitally, they can cross-check an individual’s claims history across motor and home, something that has not been possible until now, outside of their own claims data. The power of this total view of claims is evident from U.S. analysis which found people with three or more motor claims incur home claims losses that are approximately 40% higher in cost than those without any motor claims.
The LexisNexis® Precision Claims database enables insurance providers to dig deeper into the claims surrounding the asset such as the home or car. Traditionally, an insurance provider would only be able to quote on their customer’s prior claims experience yet market wide claims data will open up the claims history for the asset and what remedial action has been taken to rectify any past claims. This allows for full disclosure on the property, vehicle and individual alike – a data gold-mine when it comes to assessing risk and accurate pricing.
As the contributory claims database takes on data from across the U.K. general insurance market, it is exciting to know that granular claims data can now help fill in the missing pieces of the jigsaw when assessing risk, from quote through to claim.
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