A call that sounds exactly like your CFO used to be reassuring. Now it is just a call.
It is late on a Friday before a long weekend. The CFO calls, sounding rushed but unmistakably like herself, and asks you to push out an urgent payment to a new supplier before the bank cutoff. She mentions the deal by name. There is even a short video meeting where a familiar face nods along. Everything checks out, except that none of it was real.
Generative AI has made voices and faces cheap to fake, and finance teams are an obvious target because they are the people who can move money. If you read our guide to business email compromise, this is the same attack in a new disguise. The defense is the same too: a process that does not depend on anyone recognizing a fake.
The term covers any scheme that uses AI-generated audio, video, images, or text to impersonate someone you trust and get money moved. In practice, it shows up in a few forms.
In December 2024, the FBI issued a public service announcement warning that criminals are using generative AI to commit fraud on a larger scale and make their schemes more believable. It describes AI-generated audio used to impersonate public figures and personal contacts to get payments, AI-generated video used in real-time video chats, and AI-written text that removes the usual warning signs of a scam.
A month earlier, FinCEN, the Treasury bureau that combats financial crime, issued an alert on fraud schemes involving deepfake media. Its main focus is fake identity documents used to open accounts at financial institutions, and it reports an increase in suspicious activity reports describing deepfakes since 2023. It also notes that deepfakes can be used to impersonate trusted people in scams aimed at businesses. The message from both is the same: realistic synthetic media is now a routine part of fraud, not a novelty.
These schemes lean on the same pressure points as any payment fraud: authority, urgency, and secrecy. A request appears to come from someone senior, it has to happen now, and it should stay quiet because of a confidential deal or a sensitive supplier issue. Timing helps the attacker too. End of quarter, year-end, and holiday weeks are when approvers are out and people are trying to clear their queues.
Here is the uncomfortable part. A lot of awareness training still tells people to listen for a robotic tone or watch for odd lip movement on video. The FBI does mention tone and word choice as possible clues, and they are worth noticing. But that advice has a short shelf life, because the tools keep improving. A team that relies on spotting the fake will eventually meet one it cannot spot.
None of these prove a request is fake. Each is a reason to slow down and verify.
The routine below does not need new software. It needs agreement from leadership that everyone follows it, including the executives being impersonated.
The routine above depends on people. The stronger defense is a system where one convinced person cannot complete the payment alone.
That is the job of the maker-checker process: one person initiates a payment and a different person approves it. On Xtrm, approval policies let you designate approvers for transfers to a linked bank, wallet-to-wallet moves, mass payment files, and linking new banks, with an optional second approver for files and amount-based approval levels for transfers. Approvers are notified when a payment file is submitted, and it is not processed until they approve. A deepfake might fool the person who receives the call. It now has to fool a second person too, through a separate step. Our help center guide to approval policies walks through the full setup.
The second control takes away a frequent goal of these schemes. When payees maintain their own payee record behind their own login, a caller asking finance to "just update the bank details" is asking for something finance does not hold. Our guide to payout controls covers how these checks fit together.
It is a scheme that uses AI-generated audio, video, images, or text to impersonate someone the victim trusts, such as an executive, colleague, or vendor, in order to get a payment sent or payment details changed. It is an evolution of business email compromise that reaches beyond email to phone and video calls.
It can be convincing, especially on a short call under time pressure. That is why the defense should not depend on recognizing a fake. A callback to a known number, a code phrase, and a second approver all work regardless of how good the imitation is.
Confirm it through a channel you already trust, such as a callback to a number in your own records, and never one supplied in the request. Require a separate, documented process for any change to payment details, and use dual approval so no single person can release a payment alone.
Yes. Reporting attempts to the FBI's Internet Crime Complaint Center at ic3.gov helps investigators connect related cases. If any payment or account details were shared, tell your bank as well.
Deepfakes change what counts as evidence. A familiar voice, a recognizable face, and a well-written email used to be good signs. Now they are just inputs, and any of them can be manufactured. The teams that hold up are not the ones with the sharpest ears. They are the ones where verification is routine, payment details cannot be changed by a phone call, and no single person can move money alone.
If you want to see how approval policies and payee-managed details would fit your payout process, we are glad to walk through it with you.
Last updated: October 19, 2026