AI is fundamentally transforming how organizations detect risk and prevent fraud at scale. In high-stakes digital ecosystems - where customers include buyers, sellers, partners, and the platform itself - balancing security, precision, and fairness in automated decisions has become one of the defining CX challenges of this decade.
In this session, we'll be joined by Manav Kapoor, Senior Technical Product Lead for Selling Partner Trust & Store Integrity at Amazon, as he explores how trust and integrity are being rebuilt through advanced AI and machine learning, from fraud detection and identity verification to dispute resolution and enforcement. Manav will share how leading organizations are evolving from predictive ML models to generative, agentic systems that can explain, justify, and adapt their decisions in real time. This shift doesn't just improve accuracy, it humanizes the experience for legitimate users while proactively identifying and neutralizing threats from bad actors.
Attendees will learn:
- How AI-driven Risk management systems are reshaping customer experience in complex digital ecosystems—and what that means for fairness, transparency, and responsible AI.
- The evolution from static ML models to agentic AI that can interpret context, explain decisions, and take autonomous action with human-in-the-loop governance.
- How to architect dispute resolution and enforcement processes that protect customers, businesses, and brand integrity without compromising trust or creating friction.
- Best practices for A/B testing risk prevention mechanisms to continuously optimize detection effectiveness while preserving seamless experiences for legitimate users.