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Incident 564: Voice deepfake targets bank in failed transfer scam

Description: In spring 2023, Florida investor Clive Kabatznik became the target of an advanced scam attempt involving a voice deepfake mimicking his own voice. The fraudulent caller, using AI-generated speech, contacted Kabatznik's Bank of America representative in an unsuccessful attempt to deceive the banker into transferring funds to a different account.

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Alleged: unknown developed an AI system deployed by scammers, which harmed Clive Kabatznik and Bank of America.

Incident Stats

Incident ID
564
Report Count
1
Incident Date
2023-08-30
Editors
Sean McGregor
Applied Taxonomies
CSETv1, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

Incident Number

The number of the incident in the AI Incident Database.
 

564

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
 

2023

Date of Incident Month

The month 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 month, estimate. Otherwise, leave blank. Enter in the format of MM
 

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

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

+1
Voice Deepfakes Are Coming for Your Bank Balance
Voice Deepfakes Are Coming for Your Bank Balance

Voice Deepfakes Are Coming for Your Bank Balance

nytimes.com

Voice Deepfakes Are Coming for Your Bank Balance
nytimes.com · 2023

This spring, Clive Kabatznik, an investor in Florida, called his local Bank of America representative to discuss a big money transfer he was planning to make. Then he called again.

Except the second phone call wasn’t from Mr. Kabatznik. Rat…

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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