Mr. Arpit Mathur

AI And Machine Learning in eCommerce Fraud Detection

Abstract:

As eCommerce continues to scale, fraudsters are leveraging advanced tactics—ranging from synthetic identities to AI-generated deepfakes—to exploit online marketplaces. Traditional rule-based fraud detection methods are no longer sufficient to keep pace with these evolving threats. In this session, we explore how AI and ML are transforming fraud prevention in eCommerce. We will discuss how machine learning models, real-time risk scoring, behavioral biometrics, and graph-based fraud detection are enabling businesses to identify and mitigate fraudulent activities more effectively. Through real-world case studies, we will examine how AI-driven fraud prevention systems balance security and seller experience, reducing false positives while ensuring a frictionless marketplace for legitimate users. We will also look ahead to emerging threats and innovations, including the role of generative AI in fraud, and adaptive AI models that evolve alongside fraudsters. This will help gain actionable insights into the future of fraud prevention and how businesses can stay ahead in this ever-changing landscape.