17th July, 2026 09:00 Workshop Spotting AI System Vulnerabilities
About this Training
The workshop aims to equip supervisory staff and policy specialists with the analytical tools necessary to identify, assess, and respond to vulnerabilities in AI systems deployed within the financial sector. As AI becomes increasingly embedded in credit scoring, transaction monitoring, algorithmic trading, onboarding, RegTech, and risk management processes, vulnerabilities may arise not only at the technical level but also within governance structures, compliance frameworks, outsourcing arrangements, and cross-border infrastructures.
In light of the EU AI Act, GDPR (including Article 22), DORA, and sectoral financial legislation, supervisors must develop the capacity to detect weaknesses related to model opacity, data bias, explainability gaps, insufficient human oversight, vendor concentration risk, and systemic synchronization effects. The workshop therefore bridges regulatory obligations with prudential realities, focusing on how AI-related failures may translate into conduct risks, operational risks, reputational exposure, capital adequacy concerns, and broader financial stability implications.
Particular attention will be given to high-risk AI systems under the AI Act, the interaction between horizontal AI regulation and sector-specific financial supervision, and the evolving role of supervisory technology (SupTech). The overarching purpose is to strengthen MFSA’s preparedness to supervise AI-driven financial innovation while safeguarding market integrity, consumer protection, and systemic resilience.
About the Lecturer
Maria Lucia Passador
Assistant Professor of Corporate Law and Financial Markets Regulation, Bocconi University
Assistant Professor of Corporate Law and Financial Markets Regulation, and attained the National Qualification as Associate Professor in the IUS/04 (Corporate Law) field in May 2022. In 2025, I was awarded the Feltrinelli Prize (under 40) in Legal Sciences by the Accademia Nazionale dei Lincei, and I am currently a member of the Centro Linceo Giovani. I hold a Master of Laws (LL.M.) from Harvard Law School, a Ph.D. in Business Law, and a Combined Bachelor and Master of Science in Law summa cum laude from Bocconi. Throughout my academic career, inter alia, I served as a John M. Olin Fellow in Empirical Law and Finance at Harvard, a Fellow in the Harvard Law School’s Program in Corporate Governance, and a Postdoc Researcher at the University of Luxembourg. I was appointed Visiting Professor at Sciences Po (2025) and the University of Notre Dame (2024), and have been a Visiting Scholar at SMU (2025), the Max Planck Institutes in Luxembourg (2023) and Hamburg (2018), the University of Oxford, Columbia Law School, and Harvard Law School.
Learning Objectives
Identify Legal Vulnerabilities in High-Risk Financial AI Systems.
Assess Prudential Risks Arising from AI Model Failures.
Evaluate Explainability and Human Oversight Compliance Mechanisms.
Detect Data Bias and Discriminatory Algorithmic Outcomes.
Understand AI Act Obligations Impacting Financial Institutions.
Analyse Systemic Risks from AI Monoculture Dependencies.
Strengthen Supervisory Tools for AI Incident Monitoring.
Enhance Cross-Authority Coordination on AI Governance Oversight.
Delivery Method
In-Person
MFSA Conference Room
Entry Requirements
Financial Supervisors and Regulators
Central Bank and Public Authority Professionals
Banking and Financial Services Professionals
Risk, Compliance and Regulatory Professionals
Policy, Legal and Advisory Professionals
Duration
4 Hours
Date & Time
17th July, 2026 09:00
What's Included
Detailed Presentation
Reading Materials
Case Studies
