Anti-Fraud Engineering for Digital Finance

Beschreibung

This book offers an introduction to the topic of anti-fraud in digital finance based on the behavioral modeling paradigm. It deals with the insufficiency and low-quality of behavior data and presents a unified perspective to combine technology, scenarios, and data for better anti-fraud performance. The goal of this book is to provide a non-intrusive second security line, rather than replaced with existing solutions, for anti-fraud in digital finance. By studying common weaknesses in typical fields, it can support the behavioral modeling paradigm across a wide array of applications. It covers the latest theoretical and experimental progress and offers important information that is just as relevant for researchers as for professionals.

This book offers an introduction to the topic of anti-fraud in digital finance based on the behavioral modeling paradigm. It deals with the insufficiency and low-quality of behavior data and presents a unified perspective to combine technology, scenarios, and data for better anti-fraud performance. The goal of this book is to provide a non-intrusive second security line, rather than replaced with existing solutions, for anti-fraud in digital finance. By studying common weaknesses in typical fields, it can support the behavioral modeling paradigm across a wide array of applications. It covers the latest theoretical and experimental progress and offers important information that is just as relevant for researchers as for professionals.

Autor*in

Cheng Wang

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Learning Automata Fraud detection Online Payment Services Online Social Networks Behavioral Modeling System Integration Network representation learning Decision Explainability Fraud Prediction Online Lending Services

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