ACAMS Singapore Event to Examine AI-Powered Financial Crime Detection and Governance
The ACAMS Singapore Chapter will hold an in-person event on 22 September 2026 examining how artificial intelligence is being deployed in financial-crime detection and how governance expectations are evolving alongside those deployments.
The session, titled AI-Powered Financial Crime Detection: Hype, Reality & Governance, will run from 6:00pm to 8:30pm SGT at the 80RR Fintech Hub, 80 Robinson Road, Singapore. Eligible attendees will receive one ACAMS credit.
Cross-bank AI and compliance governance
According to ACAMS, the discussion will consider a cross-bank proof-of-value involving the Monetary Authority of Singapore, five banks and the Singapore Police Force that pools transaction data to identify scams before funds move. The event will also examine the practical implications of MAS’s AI Risk Management Toolkit for financial institutions, including model governance, explainability and agentic AI.
The panel is designed to focus on what AI-enabled financial-crime controls are actually deployable, where governance can lag implementation, and how financial institutions can build evidence-ready infrastructure rather than treating AI as an experimental compliance layer.
Another theme is the integration of on-chain intelligence into financial-crime models. ACAMS notes that the discussion will cover how blockchain intelligence can support the broader compliance lifecycle, including onboarding, transaction monitoring, regulatory reporting and incident response.
Speakers and audience
Published speaker information includes Adriel Wong, Head of Institutions, Private Sector at TRM Labs, whose work covers financial institutions, VASPs, crypto exchanges and fintech companies across Asia-Pacific.
The event is aimed at compliance and financial-crime professionals assessing how AI can be used in production environments while remaining explainable, governable and aligned with supervisory expectations.
For Singapore institutions, the significance is less about whether AI will enter financial-crime controls and more about how quickly governance, documentation and data-sharing arrangements can mature alongside deployment.
