AI and Machine Learning for E-Commerce Risk Management
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AI and Machine Learning for E-Commerce Risk Management

AI and Machine Learning for E-Commerce Risk Management


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About the Book

This book offers a comprehensive guide to leveraging machine learning and predictive analytics for managing the full spectrum of risks inherent in modern e-commerce platforms--from payment fraud and chargebacks to platform-specific abuses like voucher manipulation, collusion rings, and promotional gaming. Grounded in real-world practice, it shows how to transform raw transaction logs, user clickstreams, and promotional datasets into actionable risk scores that power both real-time interdiction and strategic oversight. Readers discover a suite of methods--ranging from gradient-boosted trees and deep sequence models to graph neural networks and unsupervised anomaly detectors--each chosen for its ability to detect subtle, evolving patterns of misuse.

About the Author :
Dr. Simon Liu is an experienced leader in data science and risk management, with a career spanning academia, financial services, and e-commerce. He is currently the chief data and AI officer at TrustDecision, where he oversees the company's data and artificial intelligence strategy, focusing on innovation in decision intelligence and risk analytics. Dr. Liu also serves as an adjunct associate professor at Nanyang Technological University (NTU), where he teaches graduate-level courses in natural language processing and ensemble learning within the School of Electrical and Electronic Engineering. He supervises research students and is the co-author of the graduate textbook Analytic Learning Methods for Pattern Recognition. Earlier in his career, he held leadership roles at Scotiabank in Canada, culminating as the director in AML modelling and analytics, where he pioneered Canada's first AI-powered model for human trafficking detection. Dr. Liu remains committed to advancing the integration of academic research and industrial practice.


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Product Details
  • ISBN-13: 9789819561834
  • Publisher: Springer Verlag, Singapore
  • Publisher Imprint: Springer Verlag, Singapore
  • ISBN-10: 9819561833
  • Publisher Date: 20 Mar 2026


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