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Manav

Kapoor

Senior Tech Product Manager

Amazon

Manav Kapoor is a Senior Technical Product Leader at Amazon's Selling Partner Trust and Store Integrity, where he leads enterprise-scale risk detection systems, protecting global marketplaces across the full spectrum of risk: from identity and seller verification to sales abuse, counterfeit, non-fulfillment, restricted products, and product safety. His work supports Amazon's mission to be the safest and most trusted place to shop and sell online, operating at massive scale to protect 300 million+ customers and 2 million+ selling partners through advanced ML and agentic AI, augmented by expert human judgment. With 15+ years across e-commerce, fintech, and digital banking, Manav translates complex risk challenges into scalable, customer-first solutions. Previously at Goldman Sachs, he led fraud prevention for Apple Card, consistently ranked #1 in J.D. Power customer satisfaction, and helped launch Apple's High-Yield Savings Account, which reached $10B in deposits within four months. Earlier, at Barclays, he led fraud prevention and mitigation for major co-branded credit card portfolios. Manav is a recognized product leader in AI-driven trust and safety, sought out keynote speaker, advisor, and author on building risk systems at scale. He also serves as a peer reviewer for leading academic journals and actively mentors founders and emerging leaders through global programs and professional networks.

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18 June 2026 13:45 - 14:15

The Wrong North Star: Why Trust Is a Flywheel and Non-Disruption Is the Metric That Matters

Every risk team chases the same north star: how many bad actors it catches. Manav argues that's the wrong metric. The real driver of marketplace growth is trust, and trust behaves like a flywheel: good actors build confidence, confidence builds liquidity, and liquidity attracts more good actors. Every false positive, every legitimate customer wrongly blocked or honest seller wrongly suspended, is a crack in that flywheel. Drawing on 15 years building risk and fraud products across banking and e-commerce, Manav makes the case for a new north star: not how many bad actors you catch, but how many good ones operate without ever being disrupted. He shows how holistic, cross-signal detection and proactive enforcement protect the flywheel, where agentic AI newly helps, and where human judgment stays essential, and why the companies that treat trust as a growth engine, not a cost center, are the ones that win. What You'll Learn - Why catch rate is a misleading north star for risk teams, and what to measure instead. - How trust compounds like a flywheel, and why every false positive quietly slows growth. - The hidden cost of false positives: why a wrongly-blocked good actor often costs more than a missed bad one. - How proactive, agentic enforcement protects good actors while still stopping genuine threats. - Where human judgment remains essential as risk systems become more autonomous.