Ways to tackle economics-driven insurance application fraud

Nick Jackson, partnerships director of CDL, explains how to detect quote manipulation or misrepresentation among those feeling the pinch.

With the worsening cost-of-living crisis, evidence is growing that consumers are finding it increasingly tempting to try to recoup savings on items such as insurance, in ways that are not always legitimate.

This includes ‘tweaking’ key rating factors when generating insurance quotes online in a bid to obtain a favourable premium.

While this has long been a feature of online trading, there is more that insurance providers can be doing to detect application fraud before it happens.

It is possible to highlight when people are generating multiple quotes while making changes to key risk factors, and implement actions to stop fraud before it happens.

A recent survey of Insurance Fraud Investigators Group (IFIG) members found that more than half said they have witnessed an uptick in insurance fraud in the past year, with nearly all expecting this volume to further increase as a result of the cost-of-living crisis.

Allianz’s latest figures showed an 11.2% increase in fraud in 2022, equating to £7.1m, and while traditional motor fraud, such as cash for crash scams, is down, application fraud is on the up.

Part of the problem is quote manipulation or misrepresentation, where consumers generate multiple insurance quotes, often through different channels, with key risk details, such as occupation or annual mileage, amended between quote requests until they obtain what they believe to be a more acceptable price.

Real-time insight

Fortunately, technology is now providing a real-time fix to this problem in the form of the latest generation of ultra-fast data intelligence solutions, which include syndicated solutions that bring insurance brands together to share insights gathered.

These are capable of conducting a range of complex searches and analysing millions of records sub-second to deliver insight and inform actions in real time.

Using this technology, it is possible to highlight when people are generating multiple quotes while making changes to key risk factors, and implement actions to stop fraud before it happens.

Bringing together insurance retailers to pool data and share insights garnered through these solutions is helping the industry to better understand consumer behaviours associated with quote manipulation.

With this knowledge, it is possible to provide some tips for using data insights to tackle what has become an increasingly challenging industry issue.

Quote matching routines

When attempting to detect quote manipulation, sophisticated consumer matching routines are vital, as people frequently adjust personal details, such as their name, address or age, to reduce premiums and, sometimes, to mask their identity whilst experimenting with application details.

Combining insights with other sources, such as MOT history or credit reference data, can assist in verifying the accuracy of declared annual mileage or driver identity.

By identifying multiple quotes involving different lead drivers, it also becomes possible to highlight potential instances of ‘fronting’, where quotes are requested in different names, in an effort to obtain the lowest price.

Visualisation tools also make it easier to spot suspicious patterns of behaviour.

Geo-mapping, for example, can help where people declare they keep their vehicle overnight at a different location to their contact address.

This analysis has highlighted unusually high volumes of quote requests involving remote areas that are typically low rated for insurance purposes, often considerable distances away from the main address.

Define suspicious behaviour

Using these insights, insurance retailers can set their own parameters for what constitutes suspicious behaviour. To reduce false positives, these typically factor in the type, extent and combination of changes made.

Finally, it’s necessary to determine the appropriate course of action in the event of suspicious behaviour. In extreme cases, retailers may decline to quote altogether.

However, many use these insights to enable more focused customer conversations, helping to ensure the correct risk is covered for the right premium and protecting consumers who otherwise risk their policies being later invalidated at point of claim due to misrepresentation.

Verified results

By following these steps and avoiding ‘toxic’ risks, insurance intermediaries are demonstrating to their insurer partners that they are taking action to develop better quality business and, in return, able to negotiate more competitive deals and drive growth in an extremely price-driven sector.

They also typically realise a range of secondary benefits from upfront automated checks, including reductions in post-sale cancellations, service costs and chase communications, reducing bad debt levels and operational costs.

Ultimately, experiences are improved for the vast majority of genuine consumers, who enjoy smoother onboarding, as well as benefitting from a fairer price for their insurance policy.

Nick Jackson is partnerships director of insurance software provider CDL

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