Financial services
Credit scoring, fraud detection and algorithmic trading: the financial sector uses AI at scale. The EU AI Act classifies several of these applications as high-risk. With existing regulation (MiFID II, PSD2, Solvency II) on top, the compliance puzzle is complex. We solve it.
AI applications in this sector
Credit scoring
Automated assessment of creditworthiness based on financial data, payment history and behavioral patterns. High-risk under Annex III, point 5(b): systems for creditworthiness assessment.
Fraud detection
Real-time detection of fraudulent transactions using machine learning. Often falls under limited risk, but can become high-risk when impacting access to financial services.
Algorithmic trading
Automated trading strategies based on AI models. Intersects with MiFID II obligations and requires transparency about algorithmic decision-making.
Insurance risk pricing
AI-driven risk profiling for premium calculation. Explicitly high-risk under Annex III, point 5(b): systems for risk assessment and pricing of life and health insurance.
AML/KYC verification
Automated identity verification and transaction monitoring for anti-money laundering. Intersects with the Anti-Money Laundering Directive and requires human oversight for escalations.
High-risk classification
The EU AI Act (Regulation 2024/1689) classifies the following financial applications as high-risk in Annex III:
Creditworthiness assessment
Annex III, point 5(b)AI systems used for assessing the creditworthiness of natural persons or establishing their credit score. This includes all automated decision-making that influences access to financing.
Insurance risk assessment and pricing
Annex III, point 5(b)AI systems for risk assessment and pricing in life and health insurance. The regulation requires these systems to be transparent, fair and non-discriminatory.
Access to essential financial services
Annex III, point 5(a)AI systems used to evaluate the eligibility of natural persons for essential financial services, including bank accounts and basic loans.
Specific challenges
Regulatory overlap
The financial sector already has MiFID II, PSD2, Solvency II, the Anti-Money Laundering Directive and DORA. The EU AI Act adds to that. Obligations overlap but are not identical. You need an integrated compliance approach that prevents double work.
Legacy systems with embedded AI
Many financial institutions run AI models built years ago, deeply embedded in legacy systems. Inventorying, classifying and documenting these systems is an operational challenge.
Volume and velocity
Financial institutions use dozens to hundreds of AI models. The EU AI Act requires separate documentation, risk assessments and human oversight for each high-risk system. At this scale, a systematic approach is essential.
Explainability vs. performance
The best fraud detection and trading models are often black boxes. The EU AI Act requires transparency and explainability (Article 13). That demands a balance between model performance and interpretability.
Our approach for financial services
We know the financial sector and its regulatory context. Our approach accounts for existing compliance frameworks and prevents double work.
Compliance Quickscan
AI Literacy Training (Article 4)
Governance Framework
The deadline for high-risk AI is August 2, 2026.
Financial institutions have on average the most high-risk AI systems. The sooner you start inventorying and classifying, the less pressure on the organization right before the deadline. In a free 30-minute intake we map out the scope.
Book your free intakeNot satisfied after the Quickscan? You pay nothing.