Webinar Description
Key Takeaways
- Examines 150 scam prevention controls across 35 countries based on Outseer’s 2026 Consumer Scam Controls report
- Focuses on proven strategies from the UK, Singapore and Australia for reducing scam-related losses
- Covers behavioral intelligence, transaction intervention, mule detection and intelligence sharing
- Designed for fraud prevention, risk management and compliance professionals at financial institutions
About the Event
This webinar from Outseer presents findings from the company’s 2026 Consumer Scam Controls report, offering a comparative analysis of how different markets approach scam prevention. The session features the report’s authors alongside industry experts discussing which controls have demonstrated measurable effectiveness in reducing fraud losses.
Layered Controls and the Scam Attack Chain
A central theme of the webinar is the application of layered controls across what Outseer terms the Scam Attack Chain. Rather than relying on single-point defenses, the discussion explores how financial institutions can deploy multiple interventions at different stages of a scam’s lifecycle. Topics include behavioral intelligence for early detection, transaction intervention to halt suspicious activity, and mule account detection to disrupt the movement of stolen funds.
Global Benchmarking
The report’s analysis spans 35 countries, with particular attention to markets that have implemented coordinated scam prevention frameworks. The UK, Singapore and Australia feature as case studies where specific controls have contributed to measurable reductions in scam losses. Intelligence sharing between institutions emerges as a recurring element in successful national approaches.
Who Should Attend
The webinar is aimed at mid-to-senior professionals working in fraud prevention, risk management, compliance and security operations within banks, payment providers and fintech organizations. Those responsible for developing or implementing scam detection strategies will find the global benchmarking data and control comparisons particularly relevant.