ACAMS Mid Tennessee Examines the Convergence of Fraud and AML
ACAMS Mid Tennessee Chapter will hold a virtual session on August 13, 2026 focused on the growing convergence of fraud prevention and anti-money laundering controls.
The session, Fraud meets AML, It is Complicated, will examine how fraud and AML functions are increasingly dealing with the same criminal activity, particularly as deepfakes, synthetic identities, social engineering and Crime-as-a-Service make fraud schemes easier to scale and their proceeds easier to move across financial systems.
From separate teams to integrated financial crime controls
According to the event programme, the discussion will cover red flags that become more visible when fraud and AML data are assessed together. Examples include mixed real and fictitious identity profiles, rapid split transactions followed by volume spikes, deepfake indicators during onboarding, circular fund movements and activity involving higher-risk jurisdictions.
The programme also highlights due diligence issues such as verifying true originators and beneficial owners, distinguishing source of funds from source of wealth, and understanding complex ownership structures.
Technology will be another focus, including detection of deepfake-enabled fraud and laundering techniques involving mixers, tumblers and chain-hopping. The session is aimed at BSA/AML officers, fraud investigators, compliance professionals, risk managers, internal auditors and board members responsible for financial crime risk.
Speakers include Jason Chorlins, Principal in Risk Advisory Services at Kaufman Rossin, and Raymond Villanueva, Director of Risk Advisory Services and a former senior Homeland Security Investigations executive.
The broader shift toward integrated fraud and AML operations reflects a practical reality: the fraud event, movement of proceeds and subsequent laundering activity increasingly form a single financial-crime chain. Institutions that keep fraud and AML data, investigations and governance completely separate may therefore lose important signals that only become clear when activity is viewed across functions.
