AI claims dominate marketing, social feeds, and news headlines. What actually works in production versus what remains aspirational? Hear from banks at different maturity stages discussing where AI delivered measurable value in fraud, AML, and KYC - and where projects failed or stalled. Examine gaps between proof-of-concept and production deployment: data quality barriers that killed projects, governance challenges, user adoption resistance, and executive expectations divorced from reality. This session separates AI capabilities proven in production from vendor promises, helping institutions invest in what works versus what sounds impressive.

Understand why remediation keeps repeating — and how to break the loop. Explore sustainable models for perpetual KYC and stronger data governance.

Are you measuring the right metrics? In this session, discuss what metrics actually measure financial crime program effectiveness beyond false positive rates: detection rates, time from alert to disposition, investigator productivity, SAR quality, coordination between fraud and AML teams, and customer harm prevented. Examine which metrics matter to regulators versus operations, what leading institutions track, and how to measure if your program is improving at stopping crime and processing alerts more efficiently.

Modern sanctions evasion goes far beyond list‑matching. Explore operating and governance models that enable cross-domain coordination.

Digital identity is often positioned as a fraud silver bullet—but does it reduce risk or introduce new vulnerabilities? This panel debates centralised versus decentralised models and draws lessons from Nordic digital ID schemes for the UK.

AI is transforming investigative operations as alert volumes rise and resources tighten, redefining FCC operating models around measurable efficiency and effectiveness. This panel explores how to deploy AI responsibly to control costs, strengthen governance and build more resilient compliance functions.

Financial crime rarely happens in isolation—mule accounts at one bank, fraud at another, layering at a third. Network intelligence connects these fragments so no bank fights fraud or AML in isolation. This session explores what network intelligence is, why it matters, global sharing models, what can be shared, and the legal frameworks that enable it and regulatory perspecitives.

Crypto has long been a favored cash‑out channel for fraud. Now stablecoins, CBDCs, and tokenized deposits are entering mainstream finance—bringing new movement patterns, instant settlement, and different monitoring needs. This session explores how tokenized payments impact fraud and AML detection, whether current controls can adapt, and what changes for transaction monitoring and sanctions screening.

Your case management system holds valuable investigative intelligence. See how institutions use this data to train models, surface typologies, and accelerate investigations.

Explore how trade surveillance expectations are evolving, including growing product complexity, cross-market behaviors, and the need for scalable, analytics-driven monitoring.

Mule networks are infrastructure for scams, fraud, and money laundering. Each domain sees fragments: fraud sees small transactions, AML sees layering patterns, KYC could prevent account opening. In this session panelists discuss coordination gaps and integrated detection approaches.

Europe’s AML overhaul is reshaping financial crime prevention. This session examines what AMLR, AMLD6, and AMLA supervision mean in practice—and where innovation fits.

See how AI-powered solutions are supporting surveillance teams by streamlining investigations, improving consistency, and reducing manual effort—without sacrificing control or accountability.