Digital Deceit: The Rising Threat of Image Alteration Fraud
Aug 7, 2025
In today’s digital claims world, a new form of insurance fraud is taking hold: media manipulation. From shallowfakes to AI-generated damage photos, falsified media is being used to support fraudulent property and casualty (P&C) claims. These tactics may seem subtle, but the financial and reputational impact on insurers is anything but.
Fraudsters are becoming more advanced. They’re not just altering images of property damage or faking car crashes. They’re also using generative AI to forge receipts and medical documents. This evolution in fraud tactics demands a stronger, more proactive response from insurers.
In this article, we’ll explore:
How fraudsters are leveraging manipulated media.
The risks this poses for insurers.
Real-world examples of this trend.
Practical ways insurers can take to stay ahead.
The Many Faces of Image-Based Insurance Fraud
Manipulated media now plays a major role in fraudulent claims. In auto insurance, shallowfakes might show digitally duplicated scratches or damage taken from unrelated accidents. In property insurance, fraudsters may reuse stock images or old photos from past claims. AI-generated imagery is also on the rise. With tools like Photoshop, ChatGPT or Midjourney, it’s easy to create fake images of storm damage, broken windows, or stolen property scenes.
These visual deceptions are no longer found just in photographs. Documents are also being targeted. Fraudsters are now submitting falsified invoices, doctor’s notes, and receipts that appear professionally created but are entirely fabricated using AI tools.
Why This Risk Is Growing Rapidly
Several trends are coming together to make image-based fraud a serious concern for P&C insurers. First, the tools to commit this type of fraud are easier to access than ever. Free or low-cost apps allow anyone to edit images convincingly or generate entirely fake media. Generative AI, once reserved for experts, is now accessible to anyone with a smartphone and a few prompts.
At the same time, claims workflows have become more reliant on virtual processes. With the rise of straight through processing and virtual inspections, insurers often depend on claimant-submitted media without an opportunity to physically verify evidence. This opens the door to undetected fraud.
Worse still, speed is now working in the fraudster’s favor. Many insurers aim to settle low-complexity claims quickly to improve customer satisfaction. But fast processing creates vulnerabilities. Fraudsters know they can fast-track multiple false claims before patterns are spotted.
Real-Life Examples of The Dangers of AI-Generated Fraud
A clear case of this new wave of fraud comes from the Netherlands. In 2025, Dutch national news outlet NOS reported a rise in fraud involving generative AI. In one case, a fraudster used AI to forge medical records supporting holiday cancellation claims and submitted them to seven different insurers. They received over €150,000 before being caught. In another case, a woman claimed €2,000 for a luxury garden lounge set with a fake receipt.
In a more recent incident reported by The Guardian, it highlights how AI-generated fraud is now even spilling into the peer-to-peer property rental space. In the U.S., an Airbnb host filed a claim for £12,000 worth of damages after a guest's stay, submitting photos that appeared to show broken furniture and general property destruction. Airbnb initially accepted the claim and issued the guest to reimburse the host a total of £5,314. However, the guest contested the charges and flagged the images as suspicious.
Upon further review, it was discovered that the photos had been manipulated, likely using generative AI or image editing tools to exaggerate or fabricate the damage. The metadata and visual inconsistencies eventually led Airbnb to reverse the decision and refund the guest’s full booking.
These claims were not flagged right away. It wasn’t until metadata inconsistencies and repeated signatures surfaced that investigators began to scrutinize the documents. By then, the damage had already been done. These stories illustrate how fraud is no longer limited to forged car photos or overstated water damage. It now includes realistic-looking PDFs, receipts, and forms that look legitimate to the untrained eye without the right tools.
What This Means for the Insurance Industry
The consequences of manipulated media in claims go beyond a few isolated cases. Industry-wide, the financial toll is staggering. Non-health insurance fraud is estimated to cost the U.S. market over $40 million each year. Image-based fraud, through inflated repairs, fake losses, and time-consuming investigations contribute to a significant portion of that total.
Beyond financial losses, there’s an operational burden. Claims teams are spending more time manually reviewing evidence. Meanwhile SIUs face growing pressure to analyze complex, AI-created documents. This not only delays claim resolution but frustrates honest policyholders caught in the backlog.
There’s also a reputational risk. Failing to catch can hurt an insurer’s credibility. But wrongly denying a legitimate claim based on bad analysis can do just as much damage. Striking the right balance between vigilance and customer trust is essential.
Spotting the Red Flags
To lower the risks, insurers must get better at identifying the signs of manipulated media. That starts with training.
Claims handlers should know how to spot:
Metadata mismatches, such as timestamps or GPS data, that don’t align with the reported incident.
Visual oddities like inconsistent lighting, duplicated patterns, or impossible reflections.
Recycled images or reused assets across multiple or past claims.
Documents with duplicate signatures, inconsistent formatting, or generic layouts.
Even basic awareness of these signs can significantly improve fraud detection rates.
Building a Multi-Layered Defense
A strong response requires more than manual inspection. Insurers should adopt a multi-layered fraud strategy that includes digital forensics, workflow integration, and human intelligence.
First, insurers need forensic tools that can analyze images and documents for manipulation. These systems examine metadata, detect reused content, and scan for pixel-level anomalies. They flag inconsistencies early in the process, so claims can be paused or escalated before payments are issued.
Second, fraud detection must be embedded into the claim's workflow. Integrating media analysis at the FNOL stage, underwriting, or payment authorization ensures suspicious content is intercepted early.
Just as importantly, analyzing media in the context of the specific claim or policy can significantly reduce false positives and increase overall detection effectiveness. For instance, understanding the type of coverage, location of the loss, or nature of the claimed damage can help focus reviews where they’re truly needed.
Contextual cues like whether the media’s metadata shows a time or date mismatch compared to when the claim was submitted can also help determine whether an image was genuinely captured for the reported event or potentially recycled from elsewhere. Automation can then route these types of innocuous anomalies in high-risk claims directly to SIU teams for deeper review.
Third, insurers must prioritize internal education. From claims adjusters to fraud investigators, every team should understand how today’s fraudsters operate. Regular training and up-to-date playbooks on AI-based fraud trends are critical.
A Tool to Support the Effort: FRISS Media Check
As part of a layered defense, insurers can benefit from using tools like FRISS Media Check. While it’s not a complete solution on its own, it adds real value. It validates images using metadata analysis, anomaly detection, and checks for reused media. It can be integrated into existing claims platforms and helps surface suspicious media faster and more reliably.
Tools like this free up SIU capacity and improve confidence in decision-making without slowing down legitimate claims.
Final Thoughts: A Call for Proactive Readiness
Image manipulation in insurance is no longer a fringe issue. It’s an evolving threat that affects every P&C carrier working in a digital environment. Fraudsters are moving faster, smarter, and more creatively than ever, often staying one step ahead of traditional defenses.
But insurers don’t have to remain reactive. With the right mix of technology, training, and process integration, they can catch fraudulent media before it turns into costly payouts. Real-world cases, like those in the Netherlands and United States, show how damaging media fraud can be, but also how detectible it is when the right systems are in place.
By proactively investing in digital fraud detection and continuously adapting to new tactics, insurers can protect their bottom line while building stronger, more trustworthy relationships with policyholders.
If your organization is looking to stay ahead of modern fraud tactics, now is the time to explore solutions that verify media, enhance detection, and support faster, fairer claims decisions.