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High-risk Sector

AI Act Compliance for Financial Services

Credit scoring, insurance and fraud detection — high-risk under the AI Act

Practical guidelines for banks, insurers and other financial institutions to comply with the EU AI Act.

View the compliance checklist

Why Take Action Now?

The AI Act has major impact on the financial sector

August 2025

First obligations for high-risk AI systems come into effect

Credit Scoring = High-risk

AI for creditworthiness automatically falls under strictest rules

Fines up to €35 million

Or 7% of global annual turnover — regulators will enforce

Explainability Requirement

Customers have right to explanation for automated decisions

High-risk AI in Financial Services

These AI applications fall under strict AI Act requirements (Annex III)

Credit Scoring

AI systems that assess creditworthiness of natural persons — from mortgage acceptance to personal loans.

Credit scoring modelsMortgage acceptance AICredit limit determinationAffordability checks

Insurance Premiums & Claims

Systems assessing risks for life and health insurance, or making claims decisions.

Life insurance pricingHealth insurance risk selectionClaim fraud detectionDamage assessment AI

Anti-Money Laundering (AML)

Transaction monitoring and customer due diligence systems fall under financial supervision and AI Act.

Transaction monitoringCustomer risk scoringSanctions screeningPEP identification

Fraud Detection

Systems detecting fraudulent transactions or behavior — from payment fraud to identity fraud.

Real-time transaction monitoringAccount takeover detectionApplication fraud screeningBehavioral analytics

Specific Challenges for Financial Institutions

The AI Act brings unique compliance questions for the financial sector

Model Risk Management Integration

How does AI Act compliance fit into existing MRM frameworks? What are overlaps with SR 11-7 and ECB guidance?

Explainability vs. Black Box

Many scoring models are complex. How to meet explainability requirements without sacrificing performance?

Bias in Credit Decisions

Non-discrimination is crucial. How to test AI models for proxy discrimination and indirect bias?

Legacy Systems

Much production AI is years old. How to bring existing models in line with new requirements?

Third-party AI Vendors

What to ask from external vendors? Credit bureaus, fraud vendors, AML providers?

Regulator Expectations

How do regulators interpret the AI Act? What are expectations for financial institutions?

AI Act Compliance Roadmap

Practical steps for financial institutions

1

AI Inventory

2-4 weeks

Map all AI systems. Which models make decisions about customers?

2

Risk Classification

1-2 weeks

Determine per system if it is high-risk, limited risk or minimal risk.

3

Gap Analysis

3-6 weeks

Compare current documentation and processes with AI Act requirements.

4

Remediation

3-12 months

Implement technical documentation, bias testing, human oversight.

5

Ongoing Monitoring

Ongoing

Set up processes for continuous monitoring and periodic review.

What Makes Financial AI Different?

Sector-specific considerations

Dual Regulated

Financial AI falls under both AI Act and financial supervision

Higher Documentation Requirements

MRM frameworks already require extensive model documentation — AI Act adds to this

Consumer Protection Focus

Explainability and complaint rights are extra important for financial decisions

Sanction Exposure

Beyond AI Act fines also regulator enforcement and reputation risk

Need Help with AI Act Compliance?

We help financial institutions with practical implementation

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Updates on AI governance for financial services