Fraudsters are turning to AI and deepfakes to create unreliable photos of insurance claims. Can YOU tell them apart?

A growing number of Brits are using fake images and documents to make fraudulent insurance claims – many of which are impossible to spot with the naked eye, This is Money can reveal.

According to the Association of British Insurers, the average insurance fraud was worth £15,000 in 2023, with insurers uncovering £1.1 billion in false claims.

Each fraudulent claim increases the cost of insurance for honest households, and an emerging technique is the use of digitally altered photos and documents to try to cheat insurers out of money.

This can take the form of photos of cars that have been altered to look as if they have been in a serious accident, or photos of home contents that have been altered to look damaged, according to insurance risk and data company Verisk.

Some of the photos below, provided exclusively to This is Money by Verisk, show just how convincing these fake images can be.

Spot the difference?: In an example of how convincing fake photos can be, the real photo of the car on the left was edited using AI to get damage marks that could mislead an insurer

Similar techniques are used on insurance documents, including insurance policies and car insurance no-claim discounts, which are modified using computers to defraud insurers.

This digital deception began to gain momentum in 2017, according to Kaye Sydenham, anti-fraud product manager for Verisk.

In the first cases, fraudsters made false insurance claims using photos they found online.

But digital photo manipulation has only accelerated since then for a variety of reasons.

One is that technology has improved to the point where highly compelling photos and documents can be digitally altered at home – often with free programs and AI software.

Another is that the cost of living crisis has made many people poorer, and therefore with more incentives to commit fraud.

Bureau of Investigation: Once again, free AI software quickly made sure that the real photo on the left showed scorch marks from a non-existent fire – enough to catch an unwary insurer

But much insurance fraud is committed not by those who are struggling financially, but by criminals, often with ties to organized crime, who insurers see as easy targets.

That has been exacerbated since the pandemic, when many insurers have increased remote working and started using automated claims systems.

Many insurers are using online, automated systems for low-value claims, and this is an area ripe for deepfake claims fraud, Sydenham said.

Low value claims are often processed through automated systems. The exact definition of ‘low value’ varies between insurers, but as a rule of thumb it is £2,000 or less.

Taking people out of the system makes it easier for fraudsters to smuggle through a false claim.

Opinion poll: Could you tell that the roof damage in the right photo is fake and caused entirely by software? The real photo of the roof is on the left

The exact number of digitally altered claims is unknown, but Sydenham says one in 10 of lower value claims analyzed by Verisk have a red flag for this type of fraud.

Although building and motor insurance have the most image fraud, other insurance sectors are also susceptible to it.

“Every industry is open to this,” Sydenham said. ‘It is more common in claims on cars and domestic property as these have a lower value. But I think it will be widespread in travel and pet insurance.

‘There could be AI videos, such as dashcam videos of fake crashes. It can be a bit of a crazy thing, chasing fraudsters and what they can do next.”

Verisk has developed smart technology that allows insurers to detect this type of digital image manipulation.

This software can detect when images have been modified and usefully highlight any changes.

It also monitors the metadata of photos: the underlying data that explains how and where a photo was taken.

Verisk can check this metadata for signs that a photo may not be real, such as a location that doesn’t match the rest of the claim data.

The software can also perform a similar anti-fraud task with documents, for example by tracking changes made.

It can even unlock changes to documents step by step, so insurers can pinpoint exactly where the fraud attempt is taking place.