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    Home»AI & Cybercrime»AI Expense Fraud Exploding As Nearly Half of Finance Pros Say Colleagues Are Faking Receipts

    AI Expense Fraud Exploding As Nearly Half of Finance Pros Say Colleagues Are Faking Receipts

    By Henry KanapiOctober 27, 20252 Mins Read
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    A new survey shows that AI-powered fraud in US and UK firms is spreading fast, and many finance teams can’t spot it.

    A survey by software automation firm Medius polled 1,000 finance professionals across two countries about fraud and generative AI.

    Medius finds that nearly a third (32%) of finance professionals in the US and UK admit they wouldn’t recognize a fake expense report if it landed on their desk. The research warns that the launch of OpenAI’s GPT 5.0 could make detecting false receipts even harder.

    Since early 2024, when GPT 4.0 went live, three in ten finance workers have already noticed a rise in fabricated receipts. Additionally, 42% of respondents suspect a coworker of faking a receipt, while 34% say they’ve been pressured to approve dubious expenses.

    “And it’s not just theoretical – when asked to share the most questionable expense they’ve ever seen approved, respondents revealed claims including a diamond ring, a luxury car, fees for a Japanese school, and even expenses for a strip club.”

    Gary Hall, chief product officer at Medius, says finance departments are now facing a frontier challenge.

    “We’re at a tipping point. GPT-5.0 promises even more realism, more precision and more ease for the user. That’s great for innovation, but it’s also a gift to fraudsters. When AI-generated documents are indistinguishable from the real thing, legacy finance systems simply can’t cope.” 

    Despite 92% of professionals saying their company’s expense policies are clear, 66% believe employees ignore them. The problem, Medius finds, is cultural: expense management has become so painful that some staff treat it as a game to beat rather than a rule to follow.

    “Forty-five percent of respondents cite chasing receipts as a major pain point, followed by approval delays (44%) and manual data entry (40%).”

     

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