On-Demand Webinar

What Is a Next-Gen AML System?

Learn how AI, machine learning and robotic process automation can help the global banking industry and financial firms transform the fight against money laundering.

 

About the webinar

As the volume of transactions continues to increase and schemes become more complex, fighting money laundering is a fast-growing problem for the global banking industry and financial firms.

Uncovering new schemes while managing increasingly sophisticated tactics continues to be problematic and requires new adaptive techniques.

The good news: The opportunity to apply AI to help defeat financial crime is here. AI, machine learning and robotic process automation can take AML programs to the next level to combat these financial crime threats while increasing your organization’s efficiency and effectiveness.

Join our SAS industry experts as they discuss how advanced analytics capabilities can transform operations in a next-gen AML system.

Learn how:

  • AI and machine learning (ML) can be applied within compliance programs.
  • ML enables professionals to focus on valuable, complex activities – not every alert.
  • Advanced analytics can slash the cost of fighting financial crime across the enterprise.

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About the Experts


Wallace Chow, Senior Business Solution Manager and Greater China AML Practice Lead, SAS  

Wallace Chow is an experienced anti-money laundering (AML) and fraud specialist who has worked in banking, securities and telecom to help organizations comply with regulations by implementing AML systems. Chow has been involved in numerous AML solution projects for major banks in Hong Kong and has experience in project management, system design and development, implementation and testing. He is also experienced in SSAMD (Structured Systems Analysis and Design Method) and project management using PRINCE2 (PRojects IN Controlled Environments).
 


Amith Satheesh, Principal Solutions Architect for Fraud and Security Intelligence Solutions, SAS

Amith Satheesh is a financial crimes domain consultant who uses advanced analytics and industry best practices to optimize AML behavior monitoring and associate conduct risk. He was previously a director for a top US bank on the wholesale banking financial crimes analytics team, where he spearheaded the rollout of a front-line monitoring program. Satheesh also worked at a top risk advisory firm helping clients in scenario development and optimization, AML model validation, false-positive reduction, AML program remediation, AML lookbacks, sanctions screening optimization, trade-based money laundering and brokerage surveillance.

He is a Certified Anti-Money Laundering Specialist (CAMS) and has more than 19 years of experience in the financial services industry.
 


Beth Herron, Security Intelligence Practice, Americas AML Team Lead, SAS

Beth Herron has more than seven years of experience supporting the financial crimes space, specializing in anti-money laundering analytics, detection strategies and case management. She leads a team of subject-matter experts who support financial institutions with pre- and post-sales support. Prior to joining SAS, she worked within the financial intelligence unit of a top five global financial institution. Herron holds a master’s degree in industrial organizational psychology. She has been accredited as a Certified Anti-Money Laundering Specialist (CAMS) and currently serves on the board of the ACAMS Carolinas Chapter.
 


David Stewart (moderator), Business Director of Security Intelligence Solutions for Banking, SAS

David Stewart leads strategy development, drives product management and provides key marketing counsel for fraud and compliance solutions worldwide. In addition to working closely with many of the world’s leading financial institutions and regulatory agencies, Stewart collaborates with SAS R&D and delivery teams to deploy industry best practices for financial crimes solutions.

During the past 10 years, Stewart has hosted SAS’ annual Counterterrorism and Financial Crimes Forum co-sponsored by the US Department of Justice and a number of global financial institutions. He has collaborated extensively to bring data mining and machine learning capabilities to market for credit analytics, customer intelligence and financial crimes applications.  

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