AI & AML - Practical Implementation, Governance & Risk

Introduction

Artificial Intelligence (AI) is rapidly reshaping Anti-Money Laundering (AML) frameworks across the financial services and professional services sectors. From transaction monitoring and customer due diligence to sanctions screening and alert optimisation, AI and machine learning are transforming how organisations detect, assess and manage financial crime risk.

This live, interactive virtual classroom provides a comprehensive and practical update on AI-driven AML. Designed specifically for AML compliance professionals, MLROs, legal and risk teams and fintech/regtech specialists, this session explores regulatory expectations, implementation challenges, governance considerations and best practices for responsible AI adoption.

It will provide you with actionable insights, case examples and practical tools to help strengthen AML frameworks while meeting evolving regulatory and ethical standards.

What You Will Learn

This live and interactive session will cover the following:

• The AI & AML Landscape
• Key developments in AI and AML
• How AI and machine learning are reshaping financial crime prevention
• Where AI adds value - and where it introduces new risk
• Regulatory & Supervisory Expectations
• Regulatory highlights across the UK, EU and key international jurisdictions
• Supervisory expectations around model risk, governance and accountability
• Preparing for regulatory scrutiny of AI-enabled AML systems
• AI in Core AML Controls
• AI applications in Customer Due Diligence (CDD) and Enhanced Due Diligence (EDD)
• Improving transaction monitoring and suspicious activity detection
• Reducing false positives while maintaining effective controls
• Case examples of AI-driven monitoring in practice
• Data, Governance and Explainability
• Data quality, privacy and security considerations
• Model explainability and auditability for compliance and regulators
• AI model governance, validation and ongoing oversight
• Managing AI-Specific Risks
• Bias, fairness and ethical considerations
• Managing false positives and false negatives
• Human oversight, accountability and escalation frameworks
• Implementation in Real-World Environments
• Integrating AI into legacy AML systems: challenges and solutions
• Practical implementation roadmaps: from pilot to scaled deployment
• Vendor selection, third-party risk and regtech partnerships
• Change Management & Stakeholder Engagement
• Gaining buy-in from compliance, legal, IT and senior management
• Training AML teams to work effectively with AI tools
• Aligning AI adoption with organisational risk appetite and culture

Recording of live sessions: Soon after the Learn Live session has taken place you will be able to go back and access the recording - should you wish to revisit the material discussed.