The CEO of a UK energy firm was tricked into wiring €220,000 (~$243,000) to a Hungarian account in March 2019 after a phone call using AI-cloned audio of his German parent company's own CEO's voice, marking the first widely reported criminal use of AI voice-cloning technology, disclosed by insurer Euler Hermes.
Social Engineering Examples·5 sources
In March 2019, the CEO of a UK energy subsidiary received a call from someone impersonating the CEO of its German parent. Reporting attributed the convincing voice, including the executive's accent and speaking style, to AI voice-cloning software. The caller directed the UK CEO to urgently wire €220,000 to a Hungarian account for a purported supplier payment. The target later became suspicious when a claimed repayment did not arrive and a further call came from an Austrian number. Contact with the genuine executive confirmed the fraud. Reporting says the funds were moved through additional accounts, including Mexico, making recovery difficult. This was described as one of the first known scams of its kind.
The scheme combined CEO-fraud social engineering with AI voice imitation. The UK subsidiary CEO was directed to send €220,000 to a purported Hungarian supplier. After a claimed repayment failed to appear, subsequent calls and the Austrian caller ID prompted verification with the genuine German executive, exposing the fraud. The supplied reporting describes the funds as subsequently moved through additional accounts, including Mexico, making recovery difficult.
The lure: a phone call carrying the parent-company CEO's voice, accent, and speaking style, followed by an email with concrete payment details. The tell: the promised reimbursement had not arrived, the caller ID showed an unexpected Austrian number, and separate contact with the genuine parent-company CEO exposed the discrepancy.
The initial €220,000 transfer to Hungary was completed. Reporting says the funds were subsequently moved through further accounts, including Mexico, making recovery difficult. A later request for another transfer is described, but the supplied sources do not establish that it was completed or stopped. No named suspect or legal proceeding is identified in the supplied sources.
This was described as one of the first known scams in which AI voice imitation was used to defraud a company. It demonstrated that familiarity with an executive's voice was not sufficient to authenticate an urgent payment request, supporting the need for independent verification of such requests.
The case supports practical controls for urgent payment requests: verify through a known independent contact method rather than relying on the incoming call or caller ID, and require additional review for unusual or new payees. Voice familiarity alone should not be treated as authentication.
Provenance. This case rests entirely on secondary reporting of an account the insurer Euler Hermes gave to journalists. The insurer's own document has never been published, the victim company has never been named, and no court filing or police record is cited here.
Social Engineering Examples. “UK Energy Firm AI Voice-Clone CEO Fraud (Euler Hermes Case)”. Accessed 3 November 2026. https://socialengineeringexamples.com/uk-energy-firm-ai-voice-clone-ceo-fraud-2019
The actors likely researched the relationship between the German parent company and its UK energy subsidiary, and identified both CEOs by name and role, plausibly using public corporate filings, company websites, press coverage, and professional-networking sites, gathering enough detail to know that an urgent call from the parent-company CEO to the UK CEO would be procedurally plausible.
Public corporate structure and executive identity information is intentionally public and cannot realistically be hidden at the scale a company operates; the practical control is to assume attackers already have it and to harden the payment-approval process that this information could be used against, rather than trying to suppress org-chart or leadership visibility.
Building a convincing clone of the parent-company CEO's voice typically required a training corpus of his real recorded speech; commercial voice-cloning tools of that era needed such samples, plausibly drawn from publicly available material such as earnings calls, conference talks, webinars, or media interviews featuring the executive.
Reducing the volume of a senior executive's unscripted public speech available online (fewer open-access recorded webinars or conference talks) can modestly shrink the training material available to an attacker, but this is a weak, largely impractical control against a motivated actor and does not eliminate the risk on its own.
Using AI voice-synthesis/voice-cloning software consistent with the commercially available tools researchers pointed to at the time, the actors generated synthetic audio intended to reproduce not just the target's general vocal timbre but distinctive attributes such as his accent and speech rhythm, aiming to defeat a listener's intuitive sense of a familiar voice.
Voice-clone production happens entirely outside the victim organization using tools and infrastructure it does not control, so there is no realistic technical interdiction at this stage; the effective response is downstream, at the point where a caller's voice is used to authorize action (Stage 4).
The attacker placed a phone call to the UK CEO using the synthetic voice, impersonating the parent-company CEO and instructing an urgent wire transfer to a purported supplier account in Hungary, leaning on authority and time pressure to discourage the target from pausing to verify.
Treat any phone-only request for an urgent wire transfer as unverified regardless of how convincing the caller's voice sounds, and require a callback to a known, previously-established number before acting, never a number supplied during the call itself.
A follow-up email supplied payee and bank-account details, giving the verbal instruction the appearance of routine, already-agreed business correspondence and reinforcing the pretext with documentary backup.
Apply the same skepticism to a supporting email as to the call it accompanies; verify new or changed payee bank details directly with the purported recipient through an independently known contact channel rather than trusting details supplied within the same interaction that requested the payment.
The UK CEO wired the requested funds, roughly 220,000 euros, to the Hungarian account, completing the attacker's primary financial objective for this stage.
A dual-approval or maker-checker control requiring a second authorized approver for wire transfers above a set threshold, or to new and first-time payees, would have required independent sign-off before the funds left, creating a second chance to catch the fraud before money moved.
The fraudster called again, falsely claiming the funds had already been reimbursed, an approach that both delayed suspicion and built apparent trust ahead of a further ask.
Treat any unsolicited call claiming a prior payment issue has been resolved as an event requiring independent confirmation, not as confirmation itself; verify directly with your own finance team or bank rather than accepting the caller's assurance.
The caller said the first payment would soon be repaid. When it did not arrive, subsequent calls, including one from an Austrian rather than German number, prompted suspicion; contact with the genuine executive confirmed the fraud.
Formalize caller-ID or origin-country anomalies on financial-request calls as an automatic trigger for escalation or a transaction hold; in this case an unexpected country code was the detail that ultimately raised suspicion, and making that check a required step rather than a matter of individual alertness generalizes the defense.
The stolen funds were reportedly moved onward from the Hungarian account through further intermediary accounts, including one traced toward Mexico, consistent with typical mule-account layering used to frustrate tracing and recovery before the fraud was fully identified.
Once funds are released and layered across cross-border accounts, recovery becomes largely a law-enforcement and banking-network problem outside the victim's direct control; the real leverage remains upstream, at Stage 6's transaction controls and Stage 4's pre-transfer verification, though rapid fraud reporting to the sending and receiving banks within hours can occasionally freeze funds before layering completes.
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