Artificial intelligence (AI) and machine learning (ML) have been touted as a means to improve the efficiency and effectiveness of traditional financial crimes compliance practices. While fraud practitioners have utilized these technologies for decades, the anti-money laundering (AML) industry has been slow to change, plagued by high false positive rates and manual processes intended to meet the letter and spirit of regulatory expectations.
SAS in partnership with ACAMS and KPMG, surveyed more than 850 compliance professionals and ACAMS members from across the globe to build a picture of AI and ML adoption in the field of AML compliance, its challenges and where untapped opportunities may still lie.
This report: Acceleration through adversity: The state of AI and machine learning adoption in anti-money laundering compliance is due to be released in June 2021.
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