Confronting insurance fraud through cross market claims data
Authored by Samantha Marsh, Director of Product Management for UK and Ireland LexisNexis Risk Solutions, Insurance
As we head into the depths of winter with the likelihood of increasing surge events and mindful of the cost-of-living crisis, speeding claims for the honest while spotting those that could be fraudulent is top of the agenda. Insurance providers have certainly been experiencing and also identifying increased levels of fraud based on data released for 2022. Last year, Zurich witnessed a 31% increase in fraudulent property claims. Just recently, Aviva confirmed a 22% rise in fraud on claims for damaged vehicles in 2022, and the number of home insurance frauds detected by Aviva jumped by 18% last year on the year prior.
There are many points during the customer journey where fraud detection data solutions can help root out fraud in a frictionless way. For example, a score for fraud can be offered based on a customer’s email address and associated personal information provided during the application process.
The next big step in fraud detection is the use of cross-market claims data, to help detect potential insurance fraud at all stages of the customer journey. In fact, with one in four young adults saying they would ‘likely’ consider an act of insurance fraud if they were struggling financially, the imminent arrival of a new contributory claims database to help mitigate fraud is well-timed.
LexisNexis® Precision Claims, due for launch in 2024 already has a wide selection of insurance providers on board allowing them to cross-check claims history across motor and home for the first time. The market-wide database will offer access to highly granular motor and home claims data for a person, property, or vehicle.
The benefits of cross-market claims data availability for underwriting are clear from market experience in the U.S. and insurance providers in the U.K. are keen to replicate these benefits. According to U.S. analysis, the application of claims data to assess risk has found for example that people with three or more motor claims incur home claims losses that are approximately 40% higher in cost than those without any motor claims.
Another practical way the contributory database can help insurance providers is to help unveil ‘career claimants’ who have made multiple claims for the same types of losses with varying providers, perhaps claiming for a piece of jewellery more than once, or accidental damage like a spill on a carpet.
With access to comprehensive claims data, insurance providers could easily uncover any claims an applicant has failed to remember or reveal – providing a more complete picture at the point of quote, or subsequently point of claim. This is fundamental in helping stamp out fraud but taking the view of the financially struggling policyholder manipulating a quote, it will also allow an insurance provider to query and correct the information provided in an application. Whilst this may increase the premium, in the event of a claim it also means the customer doesn’t need to worry about paying additional premiums along with their excess during an already stressful time, and the claim is less likely to be delayed.
Worryingly, in a 2022 survey, 12% of people said they had cancelled their home contents insurance to save money. Meanwhile the cost of fraud continues to impact the insurance sector with the value of the average scam up 20% in 2022. The more the insurance industry can do to help mitigate fraud risks using data, the more chance they have to bring premiums down for the good of all.
