Training overview
Anti-Money Laundering frameworks are increasingly shaped by advanced analytics, artificial intelligence and data-driven processes. At the same time, regulatory expectations around governance, accountability and data privacy continue to intensify.

This training focuses on the governance of AML in an environment where AI and data usage play a growing role. Participants gain insight into how AI is applied within AML/CFT/CFP processes, what risks this creates, and how organisations are expected to manage these risks in line with regulatory and privacy requirements.

This training does not focus on the technical design of AI models, but on governance, accountability and regulatory defensibility. The emphasis is on oversight, responsibility and control, rather than technical implementation.

Learning objectives
After completing this training, participants will:

Understand how AI and data-driven tools are used within AML/CFT/CFP frameworks
Recognise key governance, compliance and integrity risks related to AI usage
Understand the interaction between AML/CFT/CFP obligations and data privacy requirements
Gain insight into regulatory expectations regarding AI governance in AML/CFT/CFP
Be better equipped to assess and challenge AML/CFT/CFP governance arrangements

Target audience
This training is designed for professionals involved in AML/CFT/CFP governance and oversight, including:

Compliance Officers and MLROs
Senior compliance and risk professionals
Legal and privacy professionals involved in AML processes
Internal Auditors
Policy, governance and oversight functions

The training is suitable for participants with prior exposure to AML or compliance topics.

Training content
During this four-hour training, the following topics will be addressed:

AML governance and accountability in a data-driven environment
The use of AI and advanced analytics in AML processes
Risks related to transparency, explainability and bias
Data privacy and GDPR considerations within AML frameworks
Balancing AML obligations and data protection principles
Roles and responsibilities across compliance, data, IT and management
Documentation, oversight and auditability
Practical governance dilemmas and supervisory expectations

Real-life examples and cases are used to illustrate how these issues arise in practice.

Training format
The training is interactive and discussion-based, combining regulatory context with practical examples. There is ample opportunity for questions, reflection and exchange of experiences.

Practical details
Duration: 4 hours
Level: Intermediate
Format: Classroom
Language: Dutch or English, depending on participants

Why attend this training?
Regulators increasingly focus on how organisations govern the use of AI and data within AML processes. This training helps professionals understand their responsibilities, identify governance gaps and ensure that AML frameworks remain effective, compliant and defensible in an evolving regulatory landscape.

AML Governance & Oversight in the Age of AI and Data Privacy