Leveraging AI tools to improve AML operational functions

Troy La Huis, Tamara Kolb, Ryan Roxbury, Lucas Chapin
7/25/2024
In this webinar recording, our panel discusses strategies for the adoption and use of AI technology for anti-money laundering (AML) operations, including how to manage associated risks.

Presenters

  • Troy La Huis, Principal, Financial Crime and Digital Security Leader, Crowe
  • Tamara Kolb, Principal, Consulting, Crowe
  • Ryan Roxbury, Firm Innovation Leader, Crowe
  • Lucas Chapin, Head of Data, Hummingbird

Webinar topics

  • AI tools can help financial intelligence units save time and improve the quality of investigations. AI can summarize documents, generate narratives, and provide recommendations to analysts. This allows analysts to focus on analysis and decision-making rather than data gathering.
  • Organizations should evaluate AI model risks like bias, explainability, and reliability. Testing strategies like parallel runs, benchmarking against other models, and comparing outputs can validate AI model performance for compliance use cases.
  • Data security and privacy are critical when implementing AI. Organizations should vet vendors carefully and have strict data governance. AI models should use only anonymized data.
  • Most organizations are still early in exploring AI for AML programs. But many see benefits in efficiency, detection, and adapting to evolving threats. Integrating AI will require changes to technology infrastructure.
  • Specialty AI agents trained on compliance frameworks can assist with workflows and help automate repetitive tasks. Chaining prompts and agents together can create more seamless handoffs between automated and human tasks.
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Troy LaHuis - social
Troy La Huis
Principal, Financial Crime and Digital Security Leader