New images show how convincing AI-generated insurance fraud has become
AI tools can now fabricate crash photos so convincing that even professionals struggle to spot fake insurance claims. Subtle clues, impossible shadows, damage that doesn’t match the impact, overly clean backgrounds and blurred plates are key red flags. Insurers are tightening evidence rules, so ATFs need high-quality, time-stamped images and robust digital records.

With insurance fraud now pushing up the average person’s annual premium by £50, new images reveal just how indistinguishable AI-generated claims are becoming, and the subtle clues we’re all missing.
A new study by data and AI leader SAS demonstrates how generative AI can fabricate convincing crash scenes in seconds, closely mirroring the tactics fraudsters and organised crime groups are already using to deceive insurers.
According to the Insurance Fraud Register, insurance fraud has now led to an average increase of £50 on consumer annual policies – while the average cost of a fake claim has now hit £84,000, with one in seven claims proven to be fraudulent, according to Adyen.
To expose how easily the human eye can be fooled, SAS asked generative AI to create doctored insurance images. Two of the three images below are fake, but are you able to tell which ones?
Answer: At first glance, Image 1 appears to be a perfectly ordinary collision scene. In reality, the entire photo is synthetic, created using a prompt for a collision on a suburban English street.
Image 2 looks even more convincing, and the image of the yellow car is real. But bystanders have been removed, number plates have been altered, and the digitally added windscreen damage is all the work of AI. By erasing contextual clues – like people and surrounding cars – fraudsters can remove the very evidence insurers rely on.
Adam Hall, Insurance Fraud Specialist at SAS, said:
“Fraudsters are exploiting generative AI tools to make fabricated damage and doctored scenes look entirely plausible. With just a few prompts, they can create, enhance or erase visual evidence to support a false insurance claim.
People should look for subtle inconsistencies – shadows that fall the wrong way, damage that doesn’t match the impact, blurred number plates, or backgrounds that appear too clean or empty. These tiny visual mismatches are often the first red flags of an AI-generated claim.
But AI isn’t just empowering fraud, it’s also helping insurers fight back. AI and machine learning can detect both one-off scams and sophisticated, organised networks. By analysing huge volumes of claims data, AI can be used to reveal anomalies and patterns that humans simply can’t, reducing losses, improving accuracy, and safeguarding customers.
As fraudsters adopt new techniques, fake identities, forged documents, digital-first scams, AI evolves too. It can review and retrain models, absorb new data sources, and deliver more accurate risk scoring to keep insurers one step ahead.”
Readers can see the full report here.
Why it matters to ATFs
For vehicle recyclers and ATFs, this kind of AI-enabled insurance fraud isn’t a distant problem, it lands directly on your desk. As images become harder to trust, insurers will tighten evidence requirements around salvage decisions, repair vs total loss calls, and green parts usage. Operators who can back every vehicle and part with clear, time-stamped, well-documented imagery and records will be much better placed to prove legitimacy, avoid being dragged into disputed claims, and protect relationships with insurers. In practice, that means viewing photo quality, metadata and traceability as core parts of your service, not just admin. As fraudsters get smarter, the recyclers who invest in robust digital evidence will be the ones insurers turn to and trust.
Methodology
SAS leveraged generative AI to simulate and analyse multiple scenarios of common insurance fraud techniques. By issuing a series of tailored prompts, the AI generated examples and insights across different types of fraudulent activity.
This approach allowed SAS to highlight how easy it can be to manipulate images, providing a comprehensive view of the key challenges facing the insurance industry today. Where existing images were doctored, they were taken from free-to-use image sites. SAS conducted a short poll to see which images people thought were doctored and real in the images provided.
About SAS
SAS is a global leader in data and AI. With SAS software and industry-specific solutions, organizations transform data into trusted decisions. SAS gives you THE POWER TO KNOW®.
Source www.sas.com
Further reading on ATF Professional
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How ABI’s Updated Salvage Code of Practice Reflects the Modern Vehicle Landscape
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A Car Written Off Every Minute: DVLA FOI Data Unveils a 46% Surge in Vehicle Write-Offs
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Understanding CoDs, NoDs and the DVLA Fleet Scheme – What ATFs Need to Know
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Record Total Loss Rates: A Green Opportunity for Recycled Parts and Sustainable Repair Strategies




