Data Can Help Achieve The ABI’s Aims on Insurance Fraud

Following on from the ABI’s comments earlier this week regarding insurance fraud, here are some insights from Kajal Vakas, Senior Vertical Market Manager Claims, at LexisNexis UK and Ireland. 

Any method of fraud detection needs to find a balance between spotting fraud and delivering a streamlined, friction-free quote or claim journey for the vast majority of customers who are genuine. Fortunately, the data and technology now exist to flag the signs of fraud without impacting the honest customer’s experience.  

For example, email address intelligence can be used to score the insurance application for the risk of fraud. Ghost brokers will often supply their own email address for documentation from an insurance provider. It therefore makes sense to check that email address and its digital footprint as early in the application process as possible.  

Quote manipulation is another big problem in motor insurance. In a recent UK study, 48% of motor insurance buyers thought it was completely or somewhat acceptable to deliberately misstate information to obtain a lower quote. Responding to this issue, shopping behaviour data can be used to help flag if information for a quote is being manipulated to get a cheaper price.

Detail on the vehicle itself such as mileage, MOT and valuation can also be verified for prevention of deliberate misstatements using vehicle centric data enrichment solutions.   

Finally, a message that comes out loud and clear from the ABI’s report is the importance of collaboration.  It is through industry collaboration that both insurers and consumers alike will enjoy a more streamlined quote and bind journey. By giving insurers access to high quality historical claims data through LexisNexis® Precision Claims, a cutting-edge market-wide contributory claims database offering a cross–market view of home and motor claims history for the first time, for both the person and the asset, insurers can reduce their reliance on the consumer to provide detailed claims history.  Insurers can therefore better assess the risk and price more effectively during the quote journey as well as improve fraud detection during the claims journey.