From Pattern Recognition to Predictive Intelligence: The Future of Insurance Fraud Detection

26 March 2026 / 3 min read

future-of-fraud-detection

Do you underestimate the creativity of insurance fraudsters? Consider the true story of the frozen feline.

A cat owner took her apparently deceased pet to a veterinarian to confirm its death, then submitted a claim on her pet insurance policy. But rather than burying the cat, she placed it in a freezer. She then insured the cat with a different carrier, defrosted it, took it to another vet, and submitted another claim. After several cycles of freeze, insure, defrost, and claim, and thousands paid out in claims, the scheme was exposed by natural processes. The last vet to see the now-decomposing cat called a fraud tip line.

Kaye Sydenham, Senior Product Manager for anti-fraud at Verisk Claims UK, offered this case as a lesson in the strange and surprising ways fraud can ensnare insurers—and the importance of continually refining detection capabilities. Sydenham spoke at Insurance Ireland’s Annual Fraud Conference 2025 in Dublin in a session titled “A New Frontier in Anti-Fraud Intelligence”.

Two worlds of fraud

Anti-fraud teams now find themselves in overlapping worlds of insurance crime: the old, where low-tech scammers run real-life schemes such as staged crashes, and the new, where high-tech trickery powered by generative artificial intelligence (GenAI) drives false or inflated claims with a few mouse clicks. At times, these worlds converge around digital efforts to fabricate more convincing documentation for old-fashioned, analog fraud.

The world of fraud prevention and investigation runs in parallel. Traditional methods that rely on human judgment and intuition are augmented by a growing digital toolbox for extracting intelligence from vast volumes of data. Sydenham cited one flurry of motor claims around Birmingham and Manchester that raised suspicions of organized fraud. There was an uptick in rear-end crashes caused by sudden braking, resulting in collisions with following vehicles.

Even as the police joined the inquiry, “nothing could link them until we had this phone number,” said Sydenham, who at the time worked for the UK’s Insurance Fraud Bureau. “And it wasn’t a phoner number linked to the claims. It was a phone number on the policy side.” That connection led to a scheme involving about 150 claims, resulting in multiple arrests and jail sentences.

The pattern recognition that set the case in motion—in this case, human-based—is a staple of anti-fraud, guiding investigators on where to focus their energies. The other ingredient was collaboration based on data sharing among insurers, and the outcome was a landmark moment in driving the industry toward a common intelligence platform, Sydenham said.

This pooling of knowledge is at the heart of what Verisk seeks to facilitate for insurers. Verisk continuously improves its intelligence platform to help the industry centralise, visualise, and act upon information that insurers and investigators use to identify and disrupt fraud more effectively.

Uniting against a common adversary

For Insurance Ireland, Verisk hosts the Insurance Link database, a shared repository for validating underwriting data that can also be a powerful resource to help insurers capture fraud signals at point of quote.

Early detection, before would-be fraudsters can act, is a critical capability. The challenge, whether at point of quote or claim, is detecting anomalies and suspicious behavioural and network patterns at scale. This is where it becomes imperative to fight AI with AI—to match the new weapons in the fraudster’s arsenal with anti-fraud measures using the same technology.

The threat and promise of LLMs

Large language models (LLMs) are an example of the risks and opportunities facing insurers as AI becomes more pervasive.

Insurers, on the other hand, can use LLMs for analysis, automation, pattern detection, and other functions that support investigators. LLMs can:

Read through data to summarise, categorise, and flag potentially suspicious patterns
Cross-reference information among sources such as claims systems, intelligence reports, and accident descriptions to make connections humans might miss
Act as a knowledge assistant to instantly explain fraud typologies, legislation, or internal policies

As fraud quickly evolves—from bizarre individual scams to AI-powered deception—insurers need better shared data, modern intelligence tools, and continued reliance on human expertise, supported by the responsible deployment of AI. Verisk, backed by half a century of experience with trusted stewardship of contributory databases, is uniquely positioned to offer the platform of choice for anti-fraud intelligence.

To explore how the latest in anti-fraud technology can help you stay ahead of claims schemes, contact your Verisk representative.