This webinar that will present the preliminary findings of an ongoing Marie Skłodowska-Curie Actions (MSCA) Industrial Doctoral project under DIGITAL.

Drawing on interviews with central bankers worldwide, Patricia Marcella Evite will show how regulatory authorities operationalize the requirements for Explainable Artificial Intelligence (XAI) in finance.

The participants report AI use cases ranging from Large Language Models (LLMs) to predictive Machine Learning (ML). For LLMs used in policy drafting and regulatory analysis, explainability strictly means accurate source-linking and verifiable citations to prevent hallucinations. Conversely, predictive ML models face adoption friction: senior policymakers often reject complex technical visualizations (such as SHAP plots) in favor of intuitive, causal narratives.

Registration: https://mariecuriealumni-eu.zoom.us/meeting/register/EwI6fAacTiOOR8mSMlLX6A#/registration

Format: 30-40 min presentation followed by Q&A.

MSCA DIGITAL project: https://www.digital-finance-msca.com/