How can I prevent deepfake wire fraud on a call? CEO-fraud payment scams and how Diopter AI stops them

What is deepfake wire fraud?

Deepfake wire fraud is when an attacker uses a cloned voice or synthetic video likeness to authorize or redirect a payment on a call.

Diopter frames the risk around where the money actually moves. It takes two common forms. The first is a redirected closing or treasury wire, where bank, treasury, or closing instructions are changed through impersonation and a last-minute instruction change. The second is a vendor or invoice change, where banking details are altered under urgency on an accounts-payable or vendor-onboarding call.

In Cllimber's assessment, the reason this is so hard to stop with training alone is that the fraud arrives inside a call that looks legitimate: a familiar face or voice, a plausible deal, and enough time pressure that the verification which would normally catch a redirect gets skipped. Once the transfer settles, the funds leave for an account that does not come back.

Why this is growing now

The scale of the losses is why security and fraud teams have started to own payment calls. The figures below are drawn from their primary sources and linked so you can verify them.

How can I prevent wire fraud on a call?

A cloned voice or a deepfaked executive can pass a single call, so confirming the face or voice "looks right" is no longer verification. The checks that actually stop a fraudulent transfer are the ones tied to the money and the pattern of the call:

• Identity and payment verification — confirm who is on the call and validate the wire instructions against your records, flagging fraud signals like a brand-new email domain or a SIM-swapped number.

  Verifying the payment details matters more than judging whether the face looks real.

• Pressure and policy checks — detect the urgency and out-of-policy framing that accompanies a redirect, and catch asks that skip your approval controls.

  Manufactured urgency is the tell that a legitimate approval would not need.

• Impersonation detection — score the call for synthetic voice and video used to authorize the transfer, live rather than from a clip afterward.

  A convincing executive on one call is no longer proof the approval is real.

The honest limitation: any one of these checks can be beaten in isolation. In Cllimber's assessment, the dependable defense is to score all three together, in real time, on the call where money moves, which is what a dedicated wire-fraud tool does and a rushed approver cannot.

How a wire fraud attack unfolds

Diopter models these attacks as a recognizable sequence, and scores that sequence while the call is still in progress:

• Authority — a cloned CFO, a title agent, or a known vendor establishes a believable reason to move money.
• Urgency — the deal closes today, and time pressure compresses the verification that would normally catch a redirect.
• Isolation — instructions arrive off the usual path: a new email domain, a private call, a different contact.
• Escalation — one approved wire normalizes the next, the way multiple transfers cleared on the Arup call.
• The ask — the wire clears, and the funds leave for an account that does not come back.

How Diopter AI stops a fraudulent transfer

Diopter AI is a real-time call verification tool that scores the call where money moves and raises a single verdict. On this use case it looks for three things: identity and payment verification, pressure and policy checks, and impersonation detection across voice and video.

When those signals combine, Diopter raises a verdict on the pattern. In its own example, a call with an unconfirmed identity, a new payment account, rising urgency, and an out-of-policy ask produces a Hold the wire verdict, routing the transfer to a second approver before funds move. In Cllimber's assessment, the distinguishing strength is that it reads the whole conversation rather than one clip: a clone can imitate your CFO, but it cannot reproduce a real approval with the right people, the right channel, and instructions that match your controls.

Why single-clip detectors miss it

Point-in-time detectors answer one question: is this video or voice fake? A good clone passes that test. Diopter scores the whole call, including the authority claims, the manufactured urgency, the push to go off-channel, and the escalating ask, then raises a verdict on a pattern a single frame cannot show.

Most tools check one clip. Diopter reads the whole call.

Deployment and trust

Diopter is designed to pilot in days and roll wider through device management, while keeping sensitive call media inside your perimeter.

• On-prem and hybrid deployments supported.
• No caller-side install; bot or bot-free capture.
• Configurable retention, including zero data retention (ZDR).
• MDM rollout via Intune and Jamf.
• SOC 2 Type II in progress.

Who should care about wire-fraud detection

• Finance, treasury, and accounts-payable teams who authorize transfers and change vendor banking details.
• Security and fraud teams at large enterprises and private equity firms, who own the risk once a payment leaves.
• Organizations moving closing, treasury, or vendor wires on calls, where a redirect is one approval away.

For the full picture of how Diopter handles deepfakes beyond payments, including candidate fraud and help-desk social engineering, see our Diopter AI review. For the hiring-side risk, see how to detect fake candidates in remote interviews.