Leveraging technology for proactive fraud prevention

Carla McDonald, director, product management, claims, U.K. and Ireland, LexisNexis® Risk Solutions, insurance.

 

Trends in claims fraud

The Association of British Insurers (ABI) reported in August 2023 that while the volume of claims fraud decreased significantly in 2022, the total value of claims fraud only fell by 4%. The report said opportunistic fraud increased by 2% with the average case of a fraudulent claim rising to £15,000, up 20% since 2021. Data enrichment at the claims stage could be the market’s ally in tackling fraud, without detriment to the claims experience for the vast majority of honest policyholders. 

Insurance providers work hard to remain on the front foot at first notification of loss (FNOL), looking for red flags that may warrant further investigation. In motor, those red flags could be the involvement of specific organisations like credit hire firms with questionable reputations. Lower velocity incidents causing injuries can also raise alarm bells, for example, a bumper-to-bumper kiss that caused the claimant to be “severely injured”. When cars involved in accidents have several occupants, this may warrant further investigation to establish if phantom passengers could be at play.

 

“Data enrichment at the claims stage could be the market’s ally in tackling fraud, without detriment to the claims experience for the vast majority of honest policyholders.”

 

But, relying on the investigative nous and expertise of fraud teams will only go so far. When dealing with large volumes of claims, insurance providers need a robust safety net, a system that raises the red flags automatically while speeding the claims journey for genuine claimants.

 

Leveraging data intelligence

Email address intelligence through solutions such as LexisNexis® Emailage® Rapid, can be a great indicator of the potential risk of fraud. In one test we ran on 150,000 first-party records, which were all verified before being originally onboarded, we processed their email addresses to see if we could find any prior links to fraud. The results revealed that 1% of those records had a high-risk score, which means those claimants had previously been connected to an act of fraud.  

 

“We are seeing a real desire from insurance providers for insights from their claims data, not just to uncover someone’s behaviour in home and motor, but also the asset itself.”

 

While 1% might not seem significant, it is important to note that this result was produced following all the usual policy onboarding checks that the insurance provider had applied and been using for years.  

Email intelligence can also help us understand if there has been an account takeover, synthetic identity, fraud rings, and historic claims.  

The frequency of claims themselves can often raise suspicion. This is where knowledge of the claiming history of an individual as well as the asset can be so valuable. For example, if an insurance provider can see the claims from a property from further back than when the current claimant lived there, they might be able to build a better understanding of whether the new claim is fraudulent. In motor, historical claims data might reveal if a car has had a history of claims behind it.   

A cross-search of historical claims can bring further insights not just for claims but to support pricing too.  For example, based on U.S. analysis, the application of claims data to assess risk has found that 14% of consumers have at least one motor and one home claim indicating a link between both lines of business. In addition, people with three or more motor claims incur home claims losses that are approximately 40% higher in cost than those without any motor claims. 

We are seeing a real desire from insurance providers for insights from their claims data, not just to uncover someone’s behaviour in home and motor, but also the asset itself.  It is good to know that this will soon become possible through the launch of LexisNexis® Precision Claims in 2024, the insurance market’s first cross-market claims contributory database. 

 

Improving claims decision making

Another area that insurance providers are keen to understand in a claims scenario is the safety features in a vehicle. Cars are becoming safer, reducing the number of collisions on the road. But if a vehicle is fitted with safety features designed to prevent a certain type of accident, and that accident occurs, insurance providers know they must look further and ask why.

 

“There is a growing appreciation in the insurance community that the type of data enrichment that happens at the policy stage can also support insurance providers during the claims process.”

 

Our own research shows that ADAS features can reduce claim frequency by up to 31%. Where ADAS features warn the driver or automatically take over braking or steering functions, an accident may be avoided or at least the severity mitigated. That said, most ADAS features, which have improved over the years and become more intuitive than earlier models, can be turned off by the driver. A lack of familiarity or appreciation of the clear benefits is an issue the industry needs to address through improved awareness and perhaps even driver training. So, has the driver overridden the safety technology or was this a staged accident? Calling on vehicle-centric data solutions typically used at the quote stage, such as LexisNexis Vehicle Build, could help in this regard.  

In fact, we are seeing a move towards non-typical datasets such as vehicle-centric data to investigate fraud. There is a growing appreciation in the insurance community that the type of data enrichment that happens at the policy stage can also support insurance providers during the claims process.  It is not just a matter of enrichment at FNOL, re-checking and re-enriching data can bring different results. There may not be a fraud flag now, but there could be one in a couple of months.   

By ingesting more data into the claims process, insurance providers can make swift and informed claims decisions that can help cut fraud, stem avoidable losses and ultimately protect their honest policyholders from those that choose to be dishonest. 

 

This post is sponsored by LexisNexis Risk Solutions.

Image of Carla McDonald provided by LexisNexis.

Image: Canva.