A tidy dinner with clients, some airline lounges, even a hotel stay — plausible, right? But what if the receipt you submit for reimbursement never existed?
That’s the troubling trend companies are waking up to: expense-report scams powered by generative AI that produce ultra-convincing fake receipts.
The story laid out in the recent report on fake expense claims reveals this is no longer fringe — it’s happening now, and likely more than you think.
According to one investigation, generative-AI tools helped create nearly 14% of all fraudulent expense documents submitted in September 2025.
What makes it scarier: these receipts have logos, line-items, even crumpled paper textures that fool human auditors.
The article shows how one firm flagged over $1 million in suspicious invoices in just 90 days thanks to this kind of automation.
Fake receipts made with AI are on the rise.
So what’s going on behind the scenes? First, the barrier to creating the fake document is now super low — you don’t need to be photo-editing savvy; you just need a prompt, a mouse and a few minutes.
An insight piece showed how even many accountants say they’d struggle to tell a legit receipt from an AI-made one. Detecting AI-generated receipts is a growing headache for finance teams.
Second, the pandemic-era remote work shift didn’t just change where we finance — it changed how we submit claims.
Receipts come in by mobile, from hotel stays in foreign cities, parking garages, meals on the road. That fuzziness adds opportunity.
One fintech firm found that many expense-report systems were never built to handle this scale of forgery:
Workers are scamming employers using AI-generated receipts which highlights that “do not trust your eyes” might be the new finance motto.
And third, it isn’t just about stealing a few dollars. These scams signal a broader shift in the fraud landscape: generative-AI is empowering the underdog fraudster, turning expense claims into another vector for economic crime.
AI-generated fraud and deepfakes are already reshaping cybercrime and this expense-receipt case is one of its less obvious fronts.
Here’s what I think: This is the kind of story companies will regret ignoring. Maybe you run finance at a firm and you’ve got good controls in place, but if your system still treats a submitted receipt as “just another PDF” you’re vulnerable.
The fraud isn’t sophisticated in motive — it’s clever in execution. And that’s exactly what makes it dangerous.
What can you do? Real-time validation helps. Link card transactions directly with receipt submission at the moment of purchase so you reduce the window for forgery.
More firms are pairing expense tools with AI models trained on receipt-metadata anomalies and merchant-matching outliers.
Finance teams need to treat suspicious items (late submissions, odd amounts, digital receipts with no metadata) like high-risk cases, not just mail-in expenses.
From the employee side, I’d say: you might think “I’d never do that”, but the system is changing underneath us.
What used to be manual, bespoke fraud now looks like autopilot. If you’re in a company that doesn’t audit these things well — you could be giving someone a runway for a quick claim.
Bottom line: Generative AI is not only creating “cool” images or chatbots — it’s quietly transforming how bad actors cheat legitimate systems.
Fake receipts might sound small fry, but when scaled across thousands of employees, dozens of clients and global expense programs, it adds up.
The question isn’t if your company will face this — it’s when. And being ready matters.
