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1st July, 2026 Workshop Crypto & Blockchain Fundamentals

What you'll learn

  • Introduce Blockchain Fundamentals, Distributed Ledgers, Consensus Mechanisms, and Network Structures.

  • Explain Crypto-Asset Taxonomies, Issuance Models, Valuation Drivers, and Market Dynamics.

  • Analyse Key Crypto Use Cases, Tokenisation Trends, and Financial Sector Implications.

  • Examine Regulatory Landscape Evolution, Focusing on EU Frameworks and MiCA Scope.

  • Explore MiCA Objectives, Classifications, and Supervisory Expectations for Crypto-Assets Regulation.

  • Assess MiCA and MiFID II Interactions for Financial Instruments.

  • Evaluate Stablecoins Frameworks, Risks, Reserve Requirements, and Supervisory Oversight Considerations.

  • Identify CASP Obligations, Governance Standards, Conduct Rules, and Risk Management Expectations.

17th July, 2026 Workshop Spotting AI System Vulnerabilities

What you'll learn

  • 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.

29th July, 2026 Workshop MiCA & Supervising CASPs

What you'll learn

  • Explain the Scope and Key Requirements of MiCA for CASPs.

  • Identify Different CASP Business Models and Activities.

  • Evaluate CASPs’ Governance, Controls, and Risk Management Frameworks.

  • Discuss the MFSA’s Supervisory Expectations of CASPs.

  • Identify Emerging Trends and Resulting Inherent Supervisory Risks in the Crypto Sector.

14th October, 2026 Workshop AI in Trading & Operational Systems

What you'll learn

  • 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.