Generative AI and Insurance Fraud: The Deepfake Threat Across Insurance Lines

As long as there has been insurance, there has been insurance fraud. Today, it costs the industry up to USD 300 billion every year in the US alone, and generative AI is making it easier for fraudsters to perpetrate. The deepfake technology is rapidly advancing, and its democratization has made it extremely easy for a layperson to generate doctored images, videos, and audio.

To generate doctored media capable of convincing insurance agents took significant effort and technical expertise. Now, easy-to-use AI tools allow bad actors to supply fake evidence with ease.

The result is an onslaught of AI-assisted insurance scams. Industry investigators in the UK, for example, reported a 300% increase in claims involving manipulated photos and documents from 2021 to 2023. These deepfakes pose big risks to consumers and insurers alike. Consumers also need to be worried because such scams can drive up the cost of the premiums.

Let’s examine how generative AI and deepfakes are accelerating fraud across major insurance categories.

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Auto Insurance Fraud: Deepfakes and Doctored Crash Evidence

Auto insurance is on the front lines of the deepfake fraud wave. Insurers are alarmed by a surge of falsified accident claims where scammers use AI tools to forge crash evidence.

Allianz and Zurich (UK) told The Guardian that there has been a 300 percent rise in claims, and it had all the signs of becoming one of the biggest scams in the industry.

However, these insurance companies talk of ‘shallowfakes.’ These are simple edits of the images and videos using tools at their disposal, but are surprisingly good at convincing adjusters. Deepfakes, however, carry a much higher risk. A few examples of deepfakes completely terrified the world. 

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Health Insurance Fraud: AI-Generated Injuries and Medical Records

Generative AI and deepfake technology could take the long-standing method of falsifying diagnostic scans and forging fake reports for justifying claims and treatments to another level.

These advanced tools can make it easier to generate fake medical reports with much better accuracy. AI can even simulate doctors and patients on paper – something we have seen with the rise of Only Fake.

One worrying capability is the creation of fake medical images. These AI image generators can produce incredibly realistic X-rays, MRIs, lab result printouts, and other scans.

Criminals have already demonstrated how such tools can be prompted to output, say, an X-ray of a fractured bone that looks authentic.

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Life Insurance and Annuities: Identity Deepfakes and “Ghost” Policyholders

Generative AI threatens to open new avenues for life insurance abuse. One risk is the use of deepfakes to support faked deaths or to keep deceased persons “alive” on paper for financial gain. In the past, such cases have been rare. For example, a woman in Australia successfully faked her death in 2016 to claim a $700,000 payout before being caught.

With modern AI, a savvy fraudster could digitally fabricate much of the “evidence” of a death with far less risk. For instance, they might generate an official-looking death certificate or coroner’s report using AI text generation, or create a doctored photo of a body or accident scene to submit as proof.

Another emerging threat in life insurance is synthetic identity fraud. Here, criminals use AI to literally invent a person, creating a fake identity with a convincing profile, and then purchase a life insurance policy on that fake person. They pay premiums for a period to avoid suspicion, and eventually stage the fictional person’s “death” to cash out the policy’s benefit.

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Property Insurance: Fake Damage, Thefts, and Disasters via AI

Homeowners, renters, and property insurance claims are also vulnerable to AI-generated fraud, often in the form of fabricated damage or theft claims. Insurers commonly ask for photographic proof of damage or loss, and AI now allows virtually any scene to be invented or altered to order. Scammers may create fake photos showing property damage that never occurred or artificially exaggerate minor incidents into major losses.

For example, an unscrupulous homeowner could use an AI image generator to produce realistic pictures of a tree smashing through their roof or extensive fire damage in their kitchen, even if no such event happened. In one demonstrated case, a small kitchen flare-up was digitally transformed via AI into images of a charred, gutted interior, making a trivial incident look like a total house fire for a large claim.

Commercial property insurance and even specialty lines, such as crop insurance, face analogous threats. Agribusiness insurers, for instance, have warned that AI-generated aerial images could be used to falsely document crop planting or damage, for example, creating the appearance of an entire field ruined by hail when no such storm occurred.

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Emerging Trends in AI-Synthesized Claims

Across all insurance categories, several common trends are emerging as generative AI becomes intertwined with fraud schemes:

Entirely Synthetic Claims

We are now seeing the rise of end-to-end fabricated incidents – what one might call “fake claims as a service.” Criminals can use AI to generate every component of a claim (incident description, images, documents, identities) without any real-world event.

Professionalization and Scale

Generative AI lets amateur fraudsters sound and look like professionals. AI technologies contribute to the professionalization of criminal scams. Deceptions look better, sound better, and are more convincing now. Polished fake documents and perfectly worded claim narratives crafted by AI mean fewer red flags (e.g., no odd phrasing or obvious edits that might tip off an adjuster). Moreover, AI enables fraud at scale – a single bad actor or a small group can attempt dozens of simultaneous frauds across insurers by leveraging automation.

Hybrid Tactics and Evolving AI Fraud Kits

Fraudsters are combining traditional methods with AI outputs to maximize success. For instance, they might take a real claim and then exaggerate it using AI. It can submit one genuine photo of minor damage alongside one AI-altered photo showing additional damage, hoping the mix of real and fake will evade detection. They are also leveraging stolen personal data (from data breaches) in conjunction with deepfakes to navigate security checks.

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Fighting Back: Insurer and Regulator Responses

The response from the insurance industry has been strong. Most companies have begun leveraging AI for fraud mitigation and detection.

AI-Based Detection Tools

Such tools can detect deepfakes in images, video, audio, and text. For example, specialized software is being deployed to automatically analyze submitted claim photos and flag those suspected of being AI-generated or manipulated.

Voice Analytics and Biometric Checks

More robust identity and claims verification systems are being deployed. A number of insurers now employ voice recognition and audio intelligence during claim interviews or customer calls. These can evaluate whether a caller’s voice might be a recording or deepfake by analyzing unexpected audio artifacts, and even assess stress or inconsistencies in real time that could indicate lying.

Evolving Policy and Regulatory Response

Insurance regulators are aware of deepfake risks. In most jurisdictions, using synthetic media to defraud an insurer falls under traditional fraud and forgery statutes – it’s illegal regardless of the tool used.

U.S. securities regulators, for example, have warned investment firms to be vigilant about deepfake scams targeting investors. Similarly, state insurance commissioners are likely to push companies to update their fraud prevention plans to explicitly cover emerging AI threats. Some lawmakers have proposed legislation to criminalize the malicious creation of deepfakes (e.g., for identity theft or fraud) beyond existing fraud laws.

Consumer Protection

If a person is victimized by an AI fraud (say their identity is stolen and used in a synthetic claim, or they are impersonated to an insurer’s detriment), regulators want to ensure the blame doesn’t fall on the innocent consumer. Standardizing verification processes and perhaps establishing liability for companies that fail to detect blatant deepfakes could be areas of focus.

In the big picture, global forums like the World Economic Forum have flagged AI-enabled fraud and disinformation as a top societal risk, suggesting that international cooperation may eventually yield best practices or even treaties on the use of AI in crime.

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Conclusion

Generative AI is transforming the fraud landscape in insurance, creating both unprecedented challenges and catalyzing new defenses. On one hand, deepfakes and AI-generated content are enabling fraudsters to fabricate claims with alarming realism – from phantom car crashes and forged medical scans to synthetic identities and staged home disasters.

On the other hand, the industry is rising to the occasion: insurers are leveraging their own AI for fraud detection, strengthening verification protocols, and adapting policies and coverage to this new reality.

At Arya.ai, we’re helping insurance companies leverage production-ready AI solutions to arrest sophisticated fraud tactics before they invade core systems and become a severe bottleneck.
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To discuss the prospects of leveraging AI for your organization, connect with us.