Session Details
AI is already reshaping how institutions detect risk, investigate alerts, and meet regulatory expectations - but the gap between potential and reliable, real-world performance remains wide. The challenge is not whether to use AI, but how to build with it intentionally and use it with confidence.
This session cuts through the hype and gets practical. Our panelists will cover the questions to ask before investing in AI, where it genuinely moves the needle in financial crime compliance, and what practitioners can realistically expect day-to-day.
In this session, we'll explore:
Building Your AI Ecosystem
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Defining the problem first: is AI the right tool, and should you build, buy, or partner?
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Data readiness, model explainability, and auditability in a regulated environment
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Responsible governance: managing model drift, validation, and regulatory scrutiny over time
Where AI Makes the Biggest Impact
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Transaction monitoring, risk scoring, and screening: fewer false positives, better alerts
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SAR drafting and alert disposition support for investigators
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Faster typology recognition and automated regulatory change management
What Practitioners Should Expect Day-to-Day
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Realistic efficiency gains and the human-in-the-loop imperative
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Common failure modes: alert fatigue, training data bias, and over-reliance on outputs
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What examiners are asking about AI use, how to document it defensibly, and how to measure ROI
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