Aviva detects record £230m in bogus insurance claims as fraudsters deploy AI
Aviva identified more than 18,400 suspect claims worth £233m in 2025, a record for the insurer. Scammers increasingly used artificial intelligence to fabricate accident scenes, forge documents, and exaggerate damage claims.
The figure includes claims across Aviva's brands and the Direct Line portfolio acquired last summer. Motor insurance fraud accounted for more than seven in 10 suspect claims in Aviva's UK general insurance business alone.
Shift toward exaggerated claims
Fraudsters are moving away from staged collisions toward inflated damage and repair claims, Aviva said. They cite wider cost pressures to justify higher payouts for vehicle damage, credit hire, and injury claims.
The value of motor fraud detected rose 39% year-on-year. Scammers are using AI tools to generate fake images of accident scenes and manipulated documents to support their claims.
Pete Ward, head of claims counter fraud at Aviva, said fraud "isn't a victimless crime - it drives up the cost of insurance for everyone." He added: "We're seeing fraud become more sophisticated, from exaggerated claims to the use of AI-generated documents."
Detection and response
Aviva uses AI tools and advanced analytics, overseen by human investigators, to identify suspicious claims faster. The company secured 37 years of custodial and suspended sentences in 2025 for serious fraud offences across its brands.
In one case, fraudsters deliberately caused a collision to claim £470,000 in inflated injury and vehicle replacement costs. Video evidence showed none of the witnesses presented in court were present at the incident. Two sisters were convicted of conspiracy to defraud, with one receiving an immediate prison sentence.
Rising fraud across home and travel insurance
Fraud in home insurance rose 15% in 2025, with customers exaggerating the value of damage, repairs, or contents. Aviva also detected growing opportunistic fraud within genuine travel insurance claims.
When fraud is uncovered, insurers reject entire claims. This approach protects the integrity of the claims process but means legitimate elements of a claim are lost once dishonesty is detected.
For insurance professionals, the trend underscores the need for updated fraud detection capabilities. Understanding how generative AI and LLM tools are being misused - and how to counter them - is becoming essential to the role. AI for Insurance applications now extend beyond customer service to active fraud prevention.
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