Acceleration through adversity: The state of AI and machine learning adoption in AML compliance

AI and machine learning are gaining serious momentum in AML compliance, with good reason. They help reduce false positives, ease caseloads, streamline reporting and lower operational costs. And yet, some have been slow to change despite the promising results and billions spent annually on basic regulatory compliance tasks.

Why do we continue to see a dichotomy in adoption of AI and ML for AML compliance when the benefits are significant? Specifically, what has been the state of adoption over the past 24 months, how has COVID-19 affected uptake, and how are compliance teams using these technologies today?

To help answer these questions, SAS, in partnership with ACAMS and KPMG, surveyed more than 850 compliance professionals and ACAMS members from across the globe to better understand AI and ML adoption in the field of AML compliance, the challenges and the untapped opportunities.

Read the report results, including:

• Fast adopters and innovators vs. late adopters.
• Factors that are accelerating AI and machine learning adoption.
• Forms of AI and ML that offer the most value.
• Primary reasons for technology adoption.
• Financial firm case studies and how they succeeded.