EU AI Act in Financial Services: Credit, Fraud, and AML Systems

Financial services teams rely heavily on AI for credit decisions, fraud prevention, risk scoring, and operational automation. Under the EU AI Act, many of these use cases can trigger high-risk obligations, especially when outputs materially affect individuals’ access to services.

Credit scoring and eligibility models deserve immediate attention. If an AI system influences who gets approved, rejected, or repriced, transparency and governance standards rise significantly. SMEs should document feature sources, explainability boundaries, and human override controls for contested outcomes.

Fraud and AML systems are equally important. Even when tools are framed as "internal risk controls," they may still impact customers through account restrictions or transaction decisions. Keep detailed logs, define escalation criteria, and ensure false positives are reviewed by trained staff.

The AI Act also intersects with existing financial regulation. That means your compliance stack cannot live in a silo. Coordinate with risk, legal, security, and product teams so monitoring and documentation are consistent across frameworks.

For SMEs, the practical sequence is clear: inventory systems, classify risk, document intended purpose and controls, test for bias and drift, then formalize oversight. This approach turns compliance into a repeatable process rather than a last-minute audit scramble.