The Anti Money Laundering (AML) landscape in 2021 will face a significant change in operations due to the US government’s passage of the National Defense Authorization Act, and with it, the enactment of the Anti-Money Laundering Act of 2020 (“AMLA”). The AMLA is the most comprehensive set of reforms to the anti-money laundering laws in the United States since the USA PATRIOT Act was passed in 2001. Join our panel of speakers in a discussion about the impacts and technology approaches and strategies to ensure your organization complies with the AMLA in 2021.
The focus of this webinar is to identify Machine Learning, Visualization, and Graph technology trends in 2021 that can increase the accuracy and output of systems, and how including the ‘Human in the Loop’ can get you ahead of AML legislation.
This event is designed as a 'Speed Dating' format, focusing on key topics for under 15 minutes in order to maximize the insights. During this online meetup, you'll learn from our experts on how Expero can unlock the potential in your organization.
Key Learning Topics:
- What Are the Key Challenges for 2021 in AML - discuss the Anti-Money Laundering Act of 2020 and other AML process changes; impact areas of audit & compliance and what is to be expected in 2021
- Technology Innovations - how new technologies like master data matching, graph analytics, and ML are assisting in the reduction of false positives and increasing accuracy
- AML Working Group - discuss available resources and what AML practitioners are doing to create solutions for new processes and how they are using technology; process trends in how banks and other institutions are preparing for 2021
- Empower the Investigator - 2021 capabilities in visualization technology and human processes that increase throughput and provide valuable human intelligence, creating quicker and more efficient outcomes for different roles like Fraud Management, Investigators, and Data and Analytics teams
- Rise of ML & AI with ‘Explainable’ ML - how to implement practical uses and methods of fraud identification, complex dependency and case management with ‘humans-in-the-loop’ for higher accuracy and process streamlining
