14th October, 2026 09:00 Workshop AI in Trading & Operational Systems
About this Training
This workshop aims to provide participants with a rigorous and operational understanding of how Artificial Intelligence (AI) is reshaping trading systems and financial operational infrastructures, and how these developments interact with prudential supervision and horizontal AI regulation. The programme is designed to bridge the gap between technical model deployment and regulatory accountability, focusing specifically on algorithmic trading, liquidity optimisation, risk modelling, compliance automation, and supervisory analytics.
The purpose is not merely to describe AI use cases, but to analyse their structural implications for market integrity, financial stability, operational resilience, and fundamental rights protection. Participants will examine how the EU AI Act interfaces with MiFID II, DORA, CRR/CRD, and supervisory practices under the ECB and national authorities. Particular emphasis will be placed on systemic synchronization risk, AI monoculture, vendor concentration, and cross-border governance challenges.
By the end of the workshop, attendees will be equipped to assess AI-driven trading and operational systems through a dual lens: technical robustness and regulatory coherence. The workshop promotes forward-looking supervisory thinking, encouraging participants to anticipate crisis scenarios and design
resilient AI governance architectures for complex financial ecosystems.
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
Understand AI architectures in trading and operational systems.
Analyse systemic risks arising from AI-driven market behaviour.
Distinguish AI Act obligations from financial regulatory requirements.
Evaluate prudential implications of high-risk AI deployments.
Assess vendor concentration and AI monoculture systemic risks.
Apply explainability standards to trading and operational models.
Design supervisory responses to AI-induced liquidity shocks.
Integrate RegTech, SupTech, and policy coordination frameworks.
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
14th October, 2026 09:00
What's Included
Detailed Presentation
Reading Materials
Case Studies
