Versatile AI Risk Assessment

AI threat catalogue Malicious Use for Attacks, Fraud and Disinformation Production

Fraud

Criminals use AI to commit fraud at greater scale and with greater credibility: through fake reviews, invented identities, forged documents, and cloned voices and videos.

As of: October 2026 · Catalogue version 2026.10.24.2 · 5 mitigations · 6 verified sources

Description

Generative AI gives fraudsters the building blocks of a credible deception. Language models write convincing scam messages and fake product reviews; image generators create profile photos, identity documents and entire invented identities used to set up fictitious accounts and social media profiles in bulk. Voice clones and deepfakes (AI-generated image, audio or video content that convincingly resembles real people) impersonate relatives, business partners or well-known figures to trigger payments. Points of attack include payment and ordering processes, customer channels, and identity checks such as video identification, whose biometric controls can be defeated with deepfakes.

Possible impact

Companies face direct financial losses from fraudulently obtained payments and accounts opened under false identities. Fake reviews and fraudulent appearances in the company’s name damage the brand and customer trust. Where identity checks are defeated, legal and regulatory risks follow, for example around anti-money-laundering and customer identification duties (know your customer).

Example

Fraudsters open accounts with a financial services provider using AI-generated ID photos and pass the video identification with a deepfake face injected in real time. They then route fraudulent payments through the accounts opened this way.

Recommended mitigations (5)

Compare effects and implementation levels. Expand each entry for the additional classification and rationale.

  • Fraud detection models in workflows

    Technical
    Effect
    Detective
    Implementation level
    Model & training, Application, API & agents
    Classification and rationale

    Primarily technical: Software or analytical tools systematically produce and evaluate measurements, deviations, or attack indicators.

  • Identity and document verification

    Technical
    Effect
    Preventive, Detective
    Implementation level
    Application, API & agents, Use & operations
    Classification and rationale

    Complementary control typeOrganizational & process-based

    Primarily technical: Machine-enforced identity, permission, or scope rules constrain unauthorized access and actions; complemented by binding workflows.

  • Anomaly detection in transactions

    Technical
    Effect
    Detective
    Implementation level
    Application, API & agents, Use & operations
    Classification and rationale

    Primarily technical: Software or analytical tools systematically produce and evaluate measurements, deviations, or attack indicators.

  • Refusal for fraud-facilitating requests

    Technical
    Effect
    Preventive
    Implementation level
    Application, API & agents
    Classification and rationale

    Primarily technical: System-enforced inspection, transformation, or blocking rules stop or neutralize disallowed content before further processing.

  • Forensic audit trails

    Technical
    Effect
    Detective
    Implementation level
    Application, API & agents, Use & operations
    Classification and rationale

    Complementary control typeOrganizational & process-based

    Primarily technical: Software or analytical tools systematically produce and evaluate measurements, deviations, or attack indicators; complemented by binding workflows.

Framework mappings

Verified locations in OWASP, NIST AI RMF, MITRE ATLAS, the EU AI Act and further frameworks. The mappings are taxonomic, not evidence of compliance.

NIST AI RMF Section 2.8MITRE ATLAS AML.T0048.002EU AI Act Article 5(1)(a) · Article 55(1)(b)BSI R10 · R11

Verified references (6)

Every reference states the framework, the exact location and the publishing organisation.

EU AI Act obligations related to this threat

The obligations from the obligations compass whose articles the catalogue maps to this threat. Each leads to its entry with core, action step and evidence; whether it applies to you depends on role and risk class.

  • Refrain from the prohibited practices Art. 5 Abs. 1 · applies from 2 February 2025

    Statutory roles: Provider, Deployer, Importer, Distributor, Authorised representative, Product manufacturer, Provider of a general-purpose AI model. Classes: Prohibited practice.

    These prohibitions have applied since 2 February 2025 and are unaffected by the deferral of the high-risk obligations. Infringements carry the highest fine bracket of the regulation.

    This reference is a review prompt. A threat match alone does not establish applicability.

  • New prohibition: intimate depictions without consent Art. 5 Abs. 1 UAbs. 1 Buchst. ba, Art. 5 Abs. 1a, 1b · applies from 2 December 2026 · amended by Reg. 2026/1744

    Statutory roles: Provider, Deployer, Importer, Distributor, Authorised representative, Product manufacturer, Provider of a general-purpose AI model. Classes: Prohibited practice, System subject to transparency obligations.

    This prohibition is new and was inserted by Regulation (EU) 2026/1744. It applies from 2 December 2026. For deployers, the prohibition applies only where the system is used for that very purpose.

    This reference is a review prompt. A threat match alone does not establish applicability.

  • New prohibition: child sexual abuse material Art. 5 Abs. 1 UAbs. 1 Buchst. bb · applies from 2 December 2026 · amended by Reg. 2026/1744

    Statutory roles: Provider, Deployer, Importer, Distributor, Authorised representative, Product manufacturer, Provider of a general-purpose AI model. Classes: Prohibited practice.

    Also newly inserted by Regulation (EU) 2026/1744, applying from 2 December 2026.

    This reference is a review prompt. A threat match alone does not establish applicability.

  • Evaluate and mitigate systemic risks Art. 55 · applies from 2 August 2025

    Statutory roles: Provider of a general-purpose AI model. Classes: Model with systemic risk.

    This reference is a review prompt. A threat match alone does not establish applicability.

All 62 obligations by role, risk class and deadline in the obligations compass

More entries from the topic group Malicious Use for Attacks, Fraud and Disinformation.

Social Engineering Attackers use AI to produce deceptively authentic, personally tailored scam messages, calls and pretext stories at scale. Malicious Software Attackers use AI models to generate or improve working malware and attack tooling. Disinformation AI makes it possible to mass-produce false or misleading content of convincing quality: fabricated news articles, manipulated images and …

Matching use cases

This list shows where to review this threat, rather than how high the risk is.

Typical for:

For 6 further use cases, relevance depends on the system design, for example whether it generates new content from open-ended requests or generates its own text. Show these use cases

Frequently asked questions

What is Fraud?
Criminals use AI to commit fraud at greater scale and with greater credibility: through fake reviews, invented identities, forged documents, and cloned voices and videos.
Which mitigations help against Fraud?
The catalogue lists 5 mitigations, each with control type, effect and implementation level. First among them are Fraud detection models in workflows, Identity and document verification and Anomaly detection in transactions.
Which EU AI Act obligations does Fraud touch?
The catalogue maps this threat to Art. 5 Abs. 1, Art. 5 Abs. 1 UAbs. 1 Buchst. ba, Art. 5 Abs. 1 UAbs. 1 Buchst. bb and Art. 55 of the EU AI Act. In the obligations compass this leads to: Refrain from the prohibited practices, New prohibition: intimate depictions without consent, New prohibition: child sexual abuse material and Evaluate and mitigate systemic risks. Whether an obligation applies depends on role, risk class and deadline.

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Cite this entry

For reports, policies or internal documents; the link leads directly to this entry.

“Fraud”. Versatile AI Risk Assessment, AI threat catalogue, as of October 2026.
https://www.versatile-ai-risk-assessment.com/en/wissensbasis/threats/fraud/

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