In opening remarks at the European Supervisor Education Initiative Conference, Czech National Bank board member Jan Kubíček outlined how the CNB is using artificial intelligence in supervision and across the institution, and how it expects supervised firms to manage AI. He said the bank has moved from testing to practical deployment through a dedicated AI and Data Science programme, with AI intended to streamline routine work, free up expert capacity for more complex tasks, and operate within strong governance and data protection controls. The CNB has introduced tools ranging from generative AI assistants for staff to more advanced models used by specialist teams. AI is already being used to process large volumes of regulatory documentation and flag inconsistencies or missing information in licensing work, including more than 200 applications for crypto-asset service provider licences under MiCA in 2026. The bank is also developing AI tools for handling complaints and inquiries from clients of financial institutions and for monitoring financial influencers, while exploring AI in economic analysis and research. This use is being supported by investment in internal computing capacity and by a cross-institutional coordination group. For supervised institutions, the CNB expects robust governance, a clear understanding of the models they use, and outcomes that are explainable, fair and consistent with regulatory expectations.
Czech National Bank2026-05-21
Czech National Bank outlines practical AI use in supervision and governance expectations for firms
At the European Supervisor Education Initiative Conference, Czech National Bank board member Jan Kubíček outlined the CNB’s shift from AI testing to deployment under an AI and Data Science programme to streamline routine work under strong governance and data protection. The CNB uses generative AI and specialist models to process regulatory documentation, support licensing including MiCA crypto-asset applications, handle complaints and inquiries, monitor financial influencers, and enhance economic analysis. Kubíček said supervised institutions must maintain robust governance, understand their models, and ensure outcomes are explainable, fair and aligned with regulatory expectations.