Aviva has uncovered a record £230 million in insurance fraud claims and is using AI tools to counter the growing problem.
The battleground has changed, and the culprits are also coming armed with a new generation of tools. We’re now in an environment where AI is being used not just to defend against fraud, but to perpetrate it.
The insurance industry has long dealt with opportunistic dishonesty. A bumped car suddenly needs four new doors, or a minor slip becomes a life-altering injury. However, according to Aviva’s data, the nature of the deception is getting deeper, more sophisticated, and harder for the human eye to catch.
Aviva is fighting fire with fire, deploying its own AI to uncover these elaborate schemes.
Countering the AI-powered insurance fraud factories
Aviva reports that scammers are now using AI to generate convincing fakes of car accident scenes. These aren’t clumsy photoshop jobs; they’re detailed, plausible images that can easily fool a claims handler working through a heavy caseload.
The same generative AI tools are being used to create fake documents, from invoices for repairs that were never done, to medical reports that have no basis in fact. Fraudsters don’t need access to a network of corrupt garages or medical professionals to back up their story. They just need a subscription to an AI service and a bit of imagination. The AI handles the rest, producing official-looking documents that can pass a cursory inspection.
An individual or small group can now generate the supporting evidence for dozens of high-value claims without ever leaving their desk. How do you validate reality when reality itself can be so easily and cheaply faked?
Aviva’s response has been to build an AI-powered defence system that can operate at the same scale and speed as the threat. While the company is understandably tight-lipped about the exact architecture, you can piece together what a system like this needs to do.
At its core, the AI detective carries out pattern recognition at scale. The AI sifts through millions of data points from current and past claims, learning what a legitimate claim looks like—and, more importantly, what it doesn’t.
When a new claim comes in, the system is cross-referencing everything. Does the damage in the photo match the physics of the described accident? Do the timestamps on the documents make sense? Has this vehicle registration number appeared in other suspicious claims? Are the repair costs quoted on the invoice out of line with the thousands of other similar repairs in the database? It’s a level of forensic analysis that would be impossible to perform manually on every one of the thousands of claims filed each day.
From organised crime to exaggerated claims
It’s important to note that this isn’t all about organised criminal gangs. A portion of that £230 million figure comes from what the industry calls “claims inflation.”
Claims inflation is the more common fraud where policyholders or service providers pad the bill. For instance, a garage might add unnecessary repairs to a quote, or an individual might exaggerate the value of items stolen in a burglary.
Here, too, AI is proving to be a heavy-duty tool. By analysing vast datasets of repair costs and market values, the system can instantly flag when a quoted price is an outlier. It can compare the cost of a replacement part from one garage against the average from hundreds of others in the same region for the same make and model.
The goal of Aviva’s AI isn’t to outright deny claims, it’s an augmentation tool for their human investigators. The AI acts as a filter, sifting through the noise to surface the most likely instances of fraud. This human-in-the-loop approach is essential for ensuring fairness and preventing the system from becoming a black box that makes decisions without oversight.
What Aviva is doing provides a potential route for any customer-facing enterprise in the age of generative AI. The same technology that creates these threats is also the most effective way to combat them.
As it becomes easier to fake everything from identities to invoices, the only viable defence is an intelligent system that can learn, adapt, and spot deception at a scale that humans alone can’t match.
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