As companies integrate autonomous AI, they face a new “agentic” attack surface where agents can bypass traditional security controls and trigger cascading risks, from account takeovers to identity manipulation. This session examines real-world threats, the evolving regulatory landscape—including California’s transparency mandates and the EU AI Act’s downstream liabilities—and why static defenses are insufficient against autonomous systems. Attendees will explore how unplanned automation creates hidden risk and gain a practical roadmap for shifting from simple human oversight to resilient, objective-based governance that secures both technology and its users.

Early-stage and/or high-growth companies face fraud risks long before they have the budget, tooling, or headcount of mature platforms. This panel explores pragmatic, resource-conscious approaches to fraud prevention, detection, and response, drawing on real-world experience from companies scaling rapidly under operational constraints. Panelists will discuss how to prioritize risks, make build-versus-buy decisions, and evolve fraud programs responsibly as companies grow.

Every platform runs investigations. Almost none retain what those investigations produce. The findings go into reports, Slack threads, and the heads of analysts who eventually leave. The next team that hits the same pattern starts from scratch. This talk draws on 12 years of running investigations at platform scale. I'll walk through how investigation knowledge disappears, what that costs operationally, and what a system designed to retain and compound investigative learning would actually look like. Not a new dashboard. Infrastructure that governs what happens after the report.

Digital marketplaces are facing increasingly sophisticated fraud, from coordinated identity networks to promo abuse and account takeovers. Traditional rule-based systems are struggling to keep pace, often increasing false positives and customer friction. This session explores how marketplaces can transition to AI-native risk systems powered by machine learning, graph analytics, and real-time decisioning. Drawing on LatentView’s experience, we will discuss building unified trust scores, enabling real-time fraud detection, and augmenting fraud operations with GenAI copilots. Attendees will gain practical insights on balancing fraud prevention with customer experience while moving toward scalable, continuously learning risk and trust ecosystems.

Fraud is never just external; for modern marketplaces, risk exists across the entire ecosystem—in internal tools, outsourced operations, and the platform’s edges where external actors continuously test controls. Vendors and partners may also be exposed due to commercial pressure, turnover, or incentive misalignment, creating additional vulnerability points. This panel examines fraud as an end-to-end ecosystem challenge rather than a point solution or isolated Trust & Safety issue, exploring how it surfaces across three layers: in-house employees with privileged access, outsourced vendors and BPOs handling critical workflows, and external bad actors ranging from organized fraud rings to opportunistic users and toolkits probing for weaknesses.