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Incident 147: Hong Kong Bank Manager Swindled by Fraudsters Using Deepfaked Voice of Company Director

Description: In early 2020, fraudsters reportedly allegedly deepfaked the voice of a company's director, demanding a bank manager in Hong Kong to authorize a $35M transfer.

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Alleged: unknown developed an AI system deployed by scammers, which harmed Hong Kong bank manager.

Incident Stats

Incident ID
147
Report Count
2
Incident Date
2020-01-01
Editors
Sean McGregor, Khoa Lam
Applied Taxonomies
CSETv1, GMF, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

Incident Number

The number of the incident in the AI Incident Database.
 

147

Special Interest Intangible Harm

An assessment of whether a special interest intangible harm occurred. This assessment does not consider the context of the intangible harm, if an AI was involved, or if there is characterizable class or subgroup of harmed entities. It is also not assessing if an intangible harm occurred. It is only asking if a special interest intangible harm occurred.
 

no

Date of Incident Year

The year in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the year, estimate. Otherwise, leave blank. Enter in the format of YYYY
 

2020

Estimated Date

“Yes” if the data was estimated. “No” otherwise.
 

No

Multiple AI Interaction

“Yes” if two or more independently operating AI systems were involved. “No” otherwise.
 

no

Embedded

“Yes” if the AI is embedded in a physical system. “No” if it is not. “Maybe” if it is unclear.
 

no

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

4.3. Fraud, scams, and targeted manipulation

Risk Domain

The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
 
  1. Malicious Actors & Misuse

Entity

Which, if any, entity is presented as the main cause of the risk
 

Human

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Post-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Intentional

Incident Reports

Reports Timeline

Incident Occurrence+1
Fraudsters Cloned Company Director’s Voice In $35 Million Bank Heist, Police Find
Fraudsters Cloned Company Director’s Voice In $35 Million Bank Heist, Police Find

Fraudsters Cloned Company Director’s Voice In $35 Million Bank Heist, Police Find

forbes.com

Bank Robbers Steal $35 Million by Deepfaking Boss's Voice

Bank Robbers Steal $35 Million by Deepfaking Boss's Voice

futurism.com

Fraudsters Cloned Company Director’s Voice In $35 Million Bank Heist, Police Find
forbes.com · 2021

AI voice cloning is used in a huge heist being investigated by Dubai investigators, amidst warnings about cybercriminal use of the new technology.

In early 2020, a bank manager in the Hong Kong received a call from a man whose voice he reco…

Bank Robbers Steal $35 Million by Deepfaking Boss's Voice
futurism.com · 2021

Deep Voice

Deepfake technology has gotten incredibly sophisticated over the years, allowing us to resurrect the voices of the dead and fool Justin Bieber into challenging famous Scientologists to fights. Some folks are even using it for mor…

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

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