Practical Approaches to Apply Machine Learning to AML

Webinar Recording

Complimentary Resource

Want to learn practical approaches to apply artificial intelligence (AI) and machine learning (ML) to your anti-money laundering (AML) program? In this webinar recording, Catherine Lu from DataVisor and Keith Furst from Data Derivatives delved into real applications of how AI and ML help AML programs. They also demystified why traditional transaction monitoring system (TMS) are struggling to keep up, and the real strengths and limitations of AI and ML.

In This Webinar You Will Learn:

  1. Different types of machine learning, and what their strengths are when applied to AML programs
  2. Practical applications of how AI and ML can be applied to AML programs, including the Financial Crimes Enforcement Network’s (FinCEN) advisory on human trafficking
  3. Strategies of how to implement AI and ML that still keep regulators comfortable
About DataVisor

Bots attacks cost companies roughly $80 billion a year. How do they work, and how can you stop them? In our latest ebook, DataVisor CTO and co-founder, Fang Yu, explains why coordinated bot attacks are so difficult to detect and prevent, and shares proactive strategies for protecting your organization.