The Finnish Financial Supervisory Authority (FIN-FSA) published findings from a February 2025 thematic review and survey on how supervised entities in Finland are using artificial intelligence, with the results intended to inform its forthcoming market supervision responsibilities under the EU Artificial Intelligence Act (Regulation (EU) 2024/1689). The review indicates strong interest in AI adoption, with all large and medium-sized respondents either already using AI or planning to start within the next two years. The risk-based survey covered 22 insurance companies, 10 Finnish banks and 20 Finnish branches of foreign banks, 11 other financial-sector companies, seven payment service providers and 13 consumer lenders. Banking and insurance were identified as the main users, with generative AI and general-purpose AI models the most frequently used technologies; AI is currently used mainly in internal processes, with increased customer-facing use anticipated. Respondents cited process development, improved customer experience and cost reduction as key objectives, while the most significant risks identified were data quality, data protection and lack of AI expertise; reported governance measures included AI strategies (50% of respondents), ethical AI standards (63%) and AI user rules (82%). High-risk AI systems under the AI Act have already been deployed, and respondents reported preparatory steps such as governance models or policies defining prohibited practices and use cases, staff training, and in some cases dedicated AI risk assessment models.
Finanssivalvonta 2025-06-27
Finnish Financial Supervisory Authority publishes thematic review on financial sector AI use to support EU AI Act supervision
The Finnish Financial Supervisory Authority (FIN-FSA) released findings from a review on AI usage among Finnish financial entities to guide future market supervision under the EU Artificial Intelligence Act. The review highlights widespread AI adoption, particularly in banking and insurance, with generative and general-purpose AI models used for internal processes. Key risks include data quality and protection, while governance measures such as AI strategies and ethical standards are being implemented.