The financial sector is one of the most heavily regulated industries—and for good reason: it’s about trust, stability, and the protection of sensitive data. The use of artificial intelligence brings new opportunities but also significant regulatory challenges.
Transparency and Explainability
A central issue is the so-called “black box”: many ML models, especially deep learning, are difficult to understand. However, regulatory authorities require that decisions—such as those for loans or insurance—be traceable and explainable.
Non-Discrimination and Fairness
AI systems must not cause discrimination based on age, gender, or origin. This means training data must be reviewed, and algorithms regularly tested for bias.
Data Protection under GDPR
The use of AI must comply with the EU General Data Protection Regulation (GDPR). This particularly affects data minimization, consent for data use, and the “right to explanation” for automated decisions.
Liability and Responsibility
Who is liable for wrong decisions? This question remains unresolved. Financial institutions must implement clear processes for governance and control, including human intervention rights.
European AI Regulation (AI Act)
The planned EU AI Act classifies applications in the financial sector as “high-risk.” This entails strict requirements for risk assessment, documentation, auditability, and human oversight.
Conclusion
Regulatory requirements are not a barrier but a framework for responsible AI use. Financial institutions that prioritize transparency, fairness, and governance early on build trust—and gain competitive advantages.