FLS NOV EU 2026

Attendees Peer-to-Peer Roundtable Discussions

• Map the real intervention points across grooming, payment and exploitation stages and see where the right fraud prevention tools can stop losses earlier.
• Deepfakes, synthetic identities and cross-channel scams are accelerating. Are your layered controls built for that level of sophistication?
• Examine what practical coordination across all institutions, both public and private, looks like.

• As APP fraud continues to evolve, what are the most effective ways to stop scams without adding unnecessary friction for genuine customers?
• How can banks use behavioral intelligence and AI to detect manipulation before customers authorise payments?
• What does best-in-class scam prevention look like, and how can collaboration between banks, regulators and technology providers help disrupt organised scam networks and money mule activity?

hosted by Feedzai

• As fraud becomes more sophisticated and interconnected, how should organisations evolve their fraud strategies, teams and operating models?
• What does effective collaboration between fraud, risk, compliance and investigations look like, and how can breaking down organisational silos improve outcomes?
• Which technologies, intelligence and skills will define the next generation of fraud prevention while balancing security with customer experience?

hosted by NICE Actimize

• See three emerging solutions put under pressure by senior industry judges and your peers. Cut through the marketing and decide which innovation genuinely moves the needle on fraud prevention.
• Walk away with insight into new approaches, fresh thinking and the trends shaping the next wave of fraud technology, as one standout earns recognition and a trophy.

• Deep dive into why fraud losses appear stable but underlying risk is increasing. Covering how attackers are using AI to scale sophistication and volume and the rise of synthetic id’s, deepfakes, and multi-step social engineering.
• Are your current approaches falling short? Explore why manual reviews and “gut feel” don’t hold up at scale and where the shift from single checks to continuous, multi-signal decisioning can strengthen your prevention.
• What needs to change now to avoid being exposed over the next 12–24 months? Stay ahead of pressure from leadership and regulators by learning how leading fraud teams reduce cost while improving detection.

• What signals does AI analyse in real time to distinguish genuine customers from fraudsters?
• How can financial institutions stop sophisticated fraud without adding unnecessary friction to the customer experience?
• What measurable business outcomes can AI driven fraud prevention deliver across fraud losses, operational efficiency and customer trust?

hosted by Feedzai

• What do criminals reveal when they think they've found a victim? How an army of AI agents infiltrate active scam campaigns across voice, SMS, WhatsApp, Telegram and email.
• The intelligence haul: mule accounts, crypto wallets, scripts, impersonated brands, and emerging typologies extracted in real time.
• Case studies on what three leading global banks did with it; and why the fraud landscape looks very different from behind enemy lines.

• Fraudsters don’t break systems, they exploit them as designed. Learn the role of human behaviour, from end-users and employees, in how fraud actually works.
• Explore how gaps between controls and channels create the real vulnerabilities and why focusing on detection alone leaves key risks untouched.
• Come away with practical questions and behavioural insights that help identify where organisations may unintentionally create fraud vulnerabilities.

• How is fraud evolving from generative AI and deepfakes to autonomous agents that can adapt attacks, bypass controls and scale synthetic identities and mule networks at machine speed?
• If attackers are operating autonomously, how can defensive AI combine identity, behavioural, device and network signals to detect and respond to threats in real time without creating unnecessary friction for genuine customers?
• As AI agents begin opening accounts, initiating payments and transacting on behalf of humans, what new frameworks are needed to verify human and agent identity, establish authority and maintain regulatory accountability?

• What new skillsets (beyond traditional compliance and investigation) are fraud teams building to stay ahead?
• Are conventional team structures holding you back? Explore how integrating fraud, cyber, behavioural science and intelligence functions can create more adaptive, future-facing operating models.
• What unconventional tactics are actually working? Learn how organisations are shifting from reactive controls to intelligence-led disruption.

• As AI makes synthetic identities and automated fraud increasingly convincing, why are traditional and single point checks struggling to distinguish genuine customers from sophisticated fraud?
• How can behavioural, device, session, identity and digital footprint signals be connected to expose inconsistencies, hidden relationships and wider fraud networks that individual checks may miss?
• What does mature, multidimensional risk decisioning look like, and how can organisations use deeper intelligence to improve fraud detection without adding unnecessary friction to the customer journey?

hosted by Seon

• How can data sharing, consortium intelligence and connected data help organisations identify sophisticated fraud patterns that would otherwise remain hidden?
• Why is uncovering fraud networks becoming just as important as detecting individual fraudulent transactions?
• How can connected intelligence improve fraud decision-making, reduce false positives and strengthen customer protection?

hosted by LexisNexis Risk Solutions