Fraud is an ongoing headache for the insurance industry. The
Association of British Insurers reported that the industry detected 113,000 dishonest insurance claims in 2017, equating to a value of £1.3bn. The total number of detected insurance frauds, which also accounts for practices such as lying when applying for
cover or ‘ghost broking’, was over half a million at 562,000.
Efforts to combat the problem have been laboured at times. New government legislation in the UK that was designed to tackle fake whiplash claims, one of the biggest sources of insurance fraud, was
postponed until April 2020, with some even doubting if that will
Meanwhile, the Department for Business, Energy & Industrial Strategy
recently announced funding for a number of projects under the auspices of the
Next Generation Services Industrial Strategy Challenge Fund. However, with £13 million in funding split between 40 projects, it is fair to say that much more investment is needed if the initiative is going to produce any meaningful results.
Nevertheless, despite this legislative inertia, insurers are fighting back. Allianz recently announced that their counter fraud efforts have resulted in an
increased saving of £64.75m in 2018, up from £62m in 2017. However, their data also showed that there has been a rise in fraudulent activity in the casualty space, where claims are historically higher in value and thus more lucrative; resulting in insurers
investing more heavily here in fraud prevention.
As insurers continue to explore new ways to fight fraud, one thing they might consider is turning the models for identifying fraudulent claims on their head. That is to say, insurers could apply more intelligent white-listing of customers, instead of black-listing
those they find to be bad eggs. Such an approach draws parallels with practices in
cybersecurity. White-listing would benefit insurers because it narrows the focus of claims handlers as they try to identify fraud. Claims from customers who have a history of non-fraudulent behaviour
can be processed quickly, whereas claims from customers who have not been white-listed can be checked more thoroughly to ensure that they are honest.
Many insurers are turning to technology to help them identify patterns of criminal behaviour – either amongst individuals or by organised crime syndicates. For example, Belgian insurer P&V recently announced that they have deployed French insurtech
Shift Technology’s anti-fraud solution. These solutions are tackling fraud by using artificial intelligence and machine learning techniques to look for patterns of behaviour and other red flags that point to the
possibility of a fraudulent claim.
Regardless of how insurers go about fighting fraud, one thing they need to ensure is that fraud and claims functions are brought together by an intelligent core so they work seamlessly together. Systems that do not complement one another will just produce
a swamp of data for their fraud fighting force to flounder in. Intelligent systems that prioritise the most crucial insights and deliver them at the point of need to claims handlers can, will, and do help insurers tackle fraud whilst reducing premiums and
improving customer service for honest customers.
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