
This course, developed entirely from scratch using the latest generation of AI research applications, provides a concise overview of the legal, ethical, and professional responsibilities accountants face in detecting and preventing money laundering in modern financial systems. Participants will examine how illicit funds are disguised through the classic stages of placement, layering, and integration, and why accountants are often targeted as professional gatekeepers in these schemes.
The program explores the major anti-money laundering (AML) laws and regulatory frameworks in both the United States and Canada, including the Bank Secrecy Act, the Anti-Money Laundering Act, and Canada’s Proceeds of Crime (Money Laundering) and Terrorist Financing Act.
Through practical examples and real-world scenarios, the course highlights common red flags in financial statements, client onboarding, and unusual transaction patterns. Participants will also learn how AML responsibilities intersect with professional ethics, risk management, sanctions screening, and reporting obligations. The session concludes with a forward-looking discussion of how emerging technologies, artificial intelligence, and global regulatory trends will reshape AML compliance by 2030.
Topics Covered:
Understanding money laundering and its three stages: placement, layering, and integration
Key U.S. AML laws, including the Bank Secrecy Act and Anti-Money Laundering Act
Key Canadian AML laws, including PCMLTFA and FINTRAC requirements
Identifying red flags and suspicious financial transaction patterns
Client onboarding, KYC, and beneficial ownership verification
Reporting obligations, including STRs, SARs, and large cash transaction rules
The future of AML enforcement and AI-driven financial crime detection
Target Audience:
This course is designed for CPAs, accountants, auditors, and financial professionals who want to strengthen their understanding of anti-money laundering risks and their role as ethical gatekeepers protecting the integrity of the financial system.
This course includes: