AIPolicyTracker

AI incident ·

Reported AI-Cloned Voice Used to Deceive Hong Kong Bank Manager in Purported $35 Million Fraud Scheme

6 news reports Snapshot 7 Sep 2026

In brief

An AI system built by Deepfake Technology Developers and Synthetic Audio Generation Technology Developers and deployed by Cybercriminals, Scammers and 1 other allegedly harmed Unnamed Japanese Firm, Unnamed Hong Kong Based Branch Manager Of Unnamed Japanese Firm and 2 others.

Risk domain
Malicious Actors & Misuse Fraud, scams, and targeted manipulation
Occurred
Coverage
6 reportsOct 2021 - Feb 2022

What happened

In January 2020, a Hong Kong-based bank manager for a Japanese company reportedly authorized $35 million in transfers after receiving a call from someone whose voice matched the company director's. According to Emirati investigators, scammers used AI-based voice cloning to impersonate the executive. The fraud allegedly involved at least 17 individuals and reportedly led to global fund transfers that triggered a UAE investigation. U.S. authorities were reportedly later asked to help trace part of

Laws that address this harm

Policy angle: Classified under Malicious Actors & Misuse (Fraud, scams, and targeted manipulation) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case in China.

Matched from the record's risk domain and country to the instruments recorded here. A reviewer can correct the match in the repository (data/external/incident_overrides.yaml).

News reports (6)

Titles link to the original publisher; report text is not reproduced here.

  1. Deepfake Audio Nabs $35M in Corporate Heist
    darkreading.com · Robert Lemos

Who was involved

Alleged harmed party
Unnamed Japanese Firm, Unnamed Hong Kong Based Branch Manager Of Unnamed Japanese Firm, General Public Of The United Arab Emirates, Centennial Bank

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Intentional
Timing
Post-deployment
Harm level
AI tangible harm event
Sectors
financial and insurance activities, other
Countries
CN

Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 4.3.

  • Cheating/plagiarism

    "Cheating/plagiarism - Use of another person’s or group’s words or ideas without consent and/or acknowledgement."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • IP/copyright loss

    "IP/copyright loss - Misuse or abuse of an individual or organisation’s intellectual property, including copyright, trademarks, and patents."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Financial and business

    "Financial and Business - Use or misuse of a technology system in a manner that damages the financial interests of an individual or group, or which causes strategic, operational, legal or financial harm to a business or...

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Impersonation/identity theft

    "Impersonation/identity theft - Theft of an individual, group or organisation’s identity by a third-party in order to defraud, mock or otherwise harm them."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Dehumanisation/objectification

    "Dehumanisation/objectification - Use or misuse of a technology system to depict and/or treat people as not human, less than human, or as objects."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Defamation/libel/slander

    "Defamation/libel/slander - Use of a technology system to create, facilitate or amplify false perception(s) about an individual, group, or organisation."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Misinformation and Manipulation

    "Recent studies have demonstrated that LLMs can be exploited to craft deceptive narratives with levels of persuasiveness similar to human-generated content (Pan et al., 2023b; Spitale et al., 2023), to fabri- cate fake n...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

  • Cybersecurity

    "LLMs may exacerbate cybersecurity risks in various ways (Newman, 2024). Firstly, LLMs may significantly amplify the effectiveness of deceptive operations aimed at tricking people into disclosing sensitive information or...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

Incidents in the same risk subdomain

All incidents in this subdomain

Source record: incident #147 on the AI Incident Database · all 6 reports