How AI images fuel Automotive Warranty fraud

AI just threw a wrench into the claims process. The recent image-generation model improvements in ChatGPT and other generative AI platforms now make it possible to create photorealistic images of anything—including car damage. For the automotive warranty industry, that presents a new challenge: if images are a core part of validating a claim, how do you know the damage is real?

We decided to test that question.

The visual test

Below are a few side-by-side images. One is real. One is AI-generated. Can you spot reality? 

Click on what you think is the real image to see if you're right.

1. Which car is real?

2. Which odometer is accurate?

3. Which car crashed?

4. Which VIN is real?

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Chances are you were able to identify a few of the fakes, but would you be able to spot them without the real image next to it? That is the challenge your claims adjudicator faces right now and making the wrong call will be expensive.

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Why the risk is real

Fraud is nothing new in automotive claims, but generative AI lowers the barrier to entry. Today, anyone can fabricate convincing photos of a cracked rim, a dented hood, or a spidered windshield in seconds. Yet warranty administrators that rely on images to verify condition are now vulnerable to what experts call "deepfake" fraud: fake evidence for real payouts.

The insurance industry is already raising the alarm. Zurich Insurance has reported cases of scammers using AI-generated damage and photoshopped license plates to stage total losses. Industry analysts expect image-based fraud to rise as more claims become touchless and remote—70% of all insurance claims are expected to be fully automated by 2025.

Auto warranties may face the same fate.

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Which claims are most vulnerable to AI image fraud?

The most common extended warranty claims involve engine, transmission, and electrical failures. Those claims are hard to fake with a photo, because they usually require diagnostic tools or teardown reports.

For all other claims, warranty companies started requesting photos and videos to process claims faster, but now that approach is no longer viable. Every visual claim is now at risk for fraud:

• Exterior body damage - dents, scratches, bumper cracks
• Tires and wheels - bent rims, blowouts, defects
• Windshields and glass - cracks, chips
• Interior damage - torn upholstery, damaged infotainment systems

These claims are often submitted with only a few photos—photos that AI can now convincingly fake.

Additionally, the most common form of fraud is adding parts that were not damaged. A dealer often might suggest that while your vehicle is getting one tire replaced for a defect, you might as well replace all four. Often customers do not know or do not think of this as fraud. 

One Truepic Vision customer observed,

“They submit a claim for one tire, but they tell the customer, ‘come back in 30 days and I'll replace the rest of your tires.’ So we see multiple claims per R.O. (repair order), or multiple claims over a period of time for the same VIN. They just try to circumvent the system as much as possible. The Service Department is always what keeps the lights on in the dealership. But some that don't care if their people are participating in fraud. It's disgusting but it's the industry we're in unfortunately.”

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What does this mean for warranty providers?

Auto warranty providers are already navigating a perfect storm of operational pressure and vulnerability:

• Rising claim volumes stretch teams thin
• Short-staffed adjudication units face mounting review queues
• Organized fraud rings are exploiting gaps in oversight

This growing complexity creates the perfect opening for generative AI to slip through unnoticed—especially in photo-based claims where human review is limited or inconsistent.

Generative AI makes it even easier for bad actors to exploit the system. A photo of a damaged wheel might not be what it seems. A crack in a windshield could be pixels, not reality. Without safeguards, fraudulent claims can slip through—costing money and slowing down legitimate claims.

A Claims executive put it bluntly,

“We call it anomalous behavior, but let's be real, it's fraud. Our data is pretty extensive.”

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How Truepic Vision helps claims teams separate fact from fake

Truepic Vision provides a secure, virtual way to verify vehicle condition, location, and possession in minutes—whether it’s during underwriting or at first notice of loss (FNOL).

Our platform is purpose-built to stop image-based fraud:

• Controlled capture - photos are taken through a secure link, with no access to the camera roll
• Tamper detection - each image undergoes over 35 fraud checks to detect manipulation
• Contextual metadata - VIN, timestamp, location, and device integrity are verified
• Custom workflows - repair shops or customers can initiate inspections themselves—no need to wait for an inspector

For high-risk claim types like tire, wheel, or appearance protection, Truepic ensures the damage you see is damage that’s real. We’ve already saved auto warranty companies millions of dollars in claims. 

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Real-world results

Truepic Vision has already helped major warranty providers:

• Old Republic enabled same-day inspections to get cars back on the road faster
• Ford reduced their need for on-site inspections by 24%

The COO of an extended warranties provider summed it up best,

‍"We literally shut down a fraud ring. We saw claims drop in that area by 70%. That alone paid for Truepic for the next five years."

As generative AI evolves, so must the tools used to validate claims. In a world where anyone can generate a cracked bumper or a busted rim with a few prompts, trust in your claims process matters more than ever.

Truepic Vision gives warranty administrators the ability to verify reality before paying for fiction.

Experience Truepic Vision yourself with our test inspection demo.