EU AI Act Impact on Insurance Fraud Detection Technology

The European Union’s Artificial Intelligence Act — the world’s first comprehensive AI regulation — entered into force on 1 August 2024, with compliance obligations phasing in through 2027. For insurers operating in the EU or serving EU residents, the Act creates binding requirements for AI systems used in fraud detection, including deepfake detection technology.

This is not a distant concern. The EU AI Act applies to any provider or deployer of AI systems whose output affects persons within the EU, regardless of where the provider is established. An Australian or American deepfake detection vendor whose technology is used by a European insurer falls within scope.

How the EU AI Act Classifies AI Systems

The Act establishes a risk-based classification framework with four tiers:

Unacceptable Risk (Prohibited)

AI systems that pose a clear threat to fundamental rights. Examples include social scoring by governments and real-time biometric identification in public spaces (with limited exceptions). Insurance fraud detection does not fall into this category.

High Risk

AI systems that pose significant risk to health, safety, or fundamental rights. This is the critical category for insurance AI.

Limited Risk

AI systems subject to transparency obligations only. Chatbots and emotion recognition systems fall here.

Minimal Risk

AI systems with no specific regulatory requirements beyond existing law.

Insurance Fraud Detection: High-Risk Classification

Annex III of the EU AI Act explicitly lists AI systems used in insurance as potentially high-risk. Specifically, Section 5(b) covers AI systems intended to be used for:

“the evaluation and classification of natural persons for the purposes of assessing their eligibility for insurance or for establishing the amount of their insurance premium”

While this language focuses on underwriting, the European Commission’s guidance and the recitals make clear that AI systems influencing insurance decisions more broadly — including claims assessment — fall within scope when they significantly affect individuals.

Deepfake detection technology used in claims processing is almost certainly high-risk under the Act. Here’s why:

It directly influences claims decisions. A deepfake detection flag can trigger claim denial, delay, or investigation — directly affecting the individual’s right to their insurance benefit.
It involves biometric data processing. Many deepfake detection systems analyze facial features, voice patterns, or other biometric markers. Biometric AI systems receive heightened scrutiny under the Act.
The consequences of error are significant. A false positive — incorrectly identifying legitimate evidence as synthetic — can result in wrongful claim denial and significant financial harm to the policyholder.

What High-Risk Classification Requires

Insurers deploying high-risk AI systems must comply with comprehensive requirements under Articles 8-15 of the Act:

Risk Management System (Article 9) A continuous, iterative risk management process throughout the AI system’s lifecycle. For deepfake detection, this includes:

Identification and analysis of known and foreseeable risks
Estimation and evaluation of risks from intended use and reasonably foreseeable misuse
Adoption of risk mitigation measures
Testing to ensure residual risk is acceptable

Data Governance (Article 10) Training, validation, and testing data must meet quality criteria including:

Relevance and representativeness
Freedom from errors
Completeness relative to the intended purpose
Appropriate statistical properties for the target population

For deepfake detection models, this means training datasets must represent the demographic diversity of EU policyholders. A model trained predominantly on one ethnic group’s facial features will not meet data governance requirements.

Technical Documentation (Article 11) Detailed documentation must be prepared before the system is placed on the market or put into service. This includes:

General description of the AI system
Detailed description of system elements and development process
Information about monitoring, functioning, and control
Risk management documentation
Description of changes made during the lifecycle

Record-Keeping (Article 12) High-risk AI systems must include automatic logging capabilities. For deepfake detection, every analysis must produce an auditable record including:

Input data (or reference to it)
Detection output and confidence level
Timestamp and system version
Any human review or override

Transparency (Article 13) Deployers must be able to interpret the system’s output and use it appropriately. Deepfake detection results cannot be black-box outputs — insurers should understand why the system flagged specific evidence and communicate that reasoning to affected individuals.

Human Oversight (Article 14) High-risk AI systems must be designed to allow effective human oversight. This means:

Humans must be able to understand the system’s capabilities and limitations
Humans must be able to correctly interpret outputs
Humans must be able to decide not to use the system or override its output
Humans must be able to intervene or interrupt the system

Accuracy, Robustness, and Cybersecurity (Article 15) Systems must achieve appropriate levels of accuracy and be resilient to errors, faults, and adversarial attacks. For deepfake detection, this includes resistance to adversarial deepfakes specifically designed to evade the detection model.

The EU AI Act does not replace the General Data Protection Regulation — it operates alongside it. For deepfake detection in insurance, this creates overlapping obligations:

Lawful Basis for Processing

Deepfake detection involves processing personal data — potentially including biometric data, which is a special category under GDPR Article 9. Insurers must establish a lawful basis for this processing:

Legitimate interest (Article 6(1)(f)) is the most likely basis for fraud detection, but requires a balancing test against the data subject’s rights
Contractual necessity (Article 6(1)(b)) may apply if fraud detection is part of the claims assessment process contemplated by the insurance contract
Legal obligation (Article 6(1)(c)) applies where fraud detection is mandated by law

For biometric data specifically, insurers need an additional exemption under Article 9(2). The most relevant is substantial public interest (Article 9(2)(g)) — which several member states have implemented through anti-fraud provisions — or explicit consent (Article 9(2)(a)), though consent is problematic in an insurance context where there is a power imbalance.

Automated Decision-Making (Article 22)

GDPR Article 22 provides that individuals have the right not to be subject to decisions based solely on automated processing that produce legal effects or similarly significantly affect them. Deepfake detection that triggers automatic claim denial without human review would likely violate this provision.

The practical requirement: deepfake detection must feed into a human-reviewed decision process, not replace it. This aligns with the EU AI Act’s human oversight requirements and with responsible deployment practices.

Data Protection Impact Assessment

Under GDPR Article 35, processing that is likely to result in high risk to individuals’ rights requires a Data Protection Impact Assessment (DPIA). Deepfake detection in insurance claims will almost always trigger this requirement because:

It involves biometric data processing
It involves evaluation or scoring of individuals
It may result in denial of a service (insurance benefit)

The DPIA must assess the necessity and proportionality of the processing, the risks to individuals, and the measures to mitigate those risks.

Data Subject Rights

Individuals retain their GDPR rights when subject to deepfake detection:

Right to information — Claimants must be informed that deepfake detection is used in claims processing
Right of access — Claimants can request the data processed and the detection results
Right to rectification — If detection results are inaccurate, claimants can request correction
Right to explanation — When subject to automated decision-making, individuals can request meaningful information about the logic involved

Compliance Timeline

The EU AI Act’s obligations phase in over several years:

Date	Requirement
2 February 2025	Prohibited AI practices take effect
2 August 2025	Obligations for general-purpose AI models
2 August 2026	High-risk AI system obligations take effect
2 August 2027	Certain product-specific high-risk AI obligations

For insurers using deepfake detection, the critical deadline is 2 August 2026. By this date, all high-risk AI system requirements must be met, including risk management systems, data governance, technical documentation, and human oversight mechanisms.

Penalties for Non-Compliance

The EU AI Act imposes significant penalties:

Prohibited AI practices: up to €35 million or 7% of global annual turnover
High-risk AI system violations: up to €15 million or 3% of global annual turnover
Incorrect information to authorities: up to €7.5 million or 1.5% of global annual turnover

For large insurers, 3% of global turnover represents billions of euros. The Act also empowers national authorities to order the withdrawal of non-compliant AI systems from the market — effectively shutting down the insurer’s fraud detection capability.

Practical Steps for Compliance

For Insurers (Deployers)

Classify your AI systems under the Act’s risk framework. Document why each system receives its classification.
Conduct a gap analysis against Articles 8-15 requirements. Most insurers will find gaps in documentation, monitoring, and human oversight.
Implement conformity assessment processes. High-risk AI systems must undergo conformity assessment before deployment.
Align GDPR and AI Act compliance. Integrate AI Act requirements into existing GDPR compliance programs rather than treating them separately.
Engage your deepfake detection vendor. Require providers to supply the technical documentation, risk assessments, and conformity evidence needed for compliance. Solutions like deetech that are designed for regulatory environments can provide this documentation as part of the service.
Train claims staff. Human oversight is only meaningful if the humans are trained to understand AI outputs and empowered to override them.

For AI Providers

Providers of deepfake detection technology have their own obligations:

Establish a quality management system
Conduct conformity assessments
Register high-risk AI systems in the EU database
Provide deployers with comprehensive technical documentation
Implement post-market monitoring

Cross-Border Complexity

European insurers operating across member states face additional complexity. While the EU AI Act is directly applicable in all member states, implementation may vary:

National competent authorities will differ in their supervisory approach
Existing national insurance regulations may impose additional requirements
Data localisation requirements vary by member state
National transpositions of the GDPR’s insurance-specific provisions differ

Insurers should establish compliance programs at the group level while accounting for national variations. The European Insurance and Occupational Pensions Authority (EIOPA) is expected to issue sector-specific guidance, which will help harmonize interpretation across member states.

The Strategic Opportunity

The EU AI Act is often framed as a compliance burden. It is also a competitive opportunity. Insurers that invest in compliant AI fraud detection — with robust governance, transparent processes, and demonstrable fairness — differentiate themselves in a market where consumer trust is paramount.

European consumers increasingly expect ethical AI practices from their insurers. The EU AI Act provides a framework for demonstrating that expectation is met.

Conclusion

The EU AI Act creates substantial obligations for insurers using deepfake detection technology. High-risk classification is near-certain, triggering comprehensive requirements for risk management, data governance, documentation, transparency, and human oversight. The intersection with GDPR adds further complexity, particularly around biometric data processing and automated decision-making.

The August 2026 compliance deadline is approaching. Insurers that have not yet assessed their deepfake detection systems against the Act’s requirements need to begin immediately. The penalties for non-compliance are severe, and the operational disruption of having a fraud detection system ordered off the market would be far worse.

For insurers seeking deepfake detection solutions built for EU regulatory compliance, deetech’s platform provides explainable outputs, comprehensive audit trails, and technical documentation packages designed to support conformity assessment under the EU AI Act.

This article is for informational purposes only and does not constitute legal, regulatory, or compliance advice. Insurers should consult qualified legal and compliance professionals for guidance specific to their circumstances and jurisdiction.