Join this free webinar on December 2, 2025 (11:00 AM CT) to see how artificial intelligence is changing the game in anti-money laundering efforts. Experts from BAI, SureStep and SAS will demonstrate how AI can sharpen detection accuracy, cut false positives, and streamline compliance workflows — all while preserving regulatory trust.
The speakers for this session are:
Robert Wright — Strategic Advisor, SureStep: Robert leads enterprise-wide strategy and large-scale transformation initiatives at SureStep. He combines regulatory, operational, and technological disciplines to turn complex compliance requirements into data-driven, actionable solutions, with strong expertise in governance, risk management, and software development.
Denny White — Senior Manager, SMB Sales – Mid-Market Financial Services, SAS: Denny serves as North American Financial Services Sales Leader for SMB and channel at SAS, supporting banks, insurers and capital markets firms in unlocking value from their data. With prior industry experience at institutions such as Wells Fargo and Fidelity Bank, he brings firsthand insight into the regulatory, data and competitive dynamics shaping financial services.
The session will explore real-world use cases from financial institutions that have successfully deployed AI-powered AML tools, outline practical steps for implementation, and highlight lessons learned. Expect actionable insights into integrating AI responsibly, optimizing alert triage, and scaling AML operations without compromising governance.
- How AI reshapes AML programs by reducing analyst noise, enhancing detection precision, and strengthening financial-crimes governance without introducing operational risk.
- Practical steps institutions can take to operationalize AI responsibly — feature engineering, model governance, risk controls, and human-in-the-loop oversight.
- Real-world scenarios showing how banks can streamline investigations, accelerate alert triage, and elevate case quality without expanding headcount.
- Key regulatory considerations: transparency, auditability, and how to align modern ML techniques with supervisory expectations while avoiding “black-box” pitfalls.
- The path forward for mid-market institutions adopting AI — where to start, how to scale, and what an achievable, sustainable target-state AML model looks like.
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