| ISBN13: | 9789819952595 |
| ISBN10: | 981995259X |
| Binding: | Paperback |
| No. of pages: | 207 pages |
| Size: | 235x155 mm |
| Language: | English |
| Illustrations: | 20 Illustrations, black & white; 75 Illustrations, color |
| 677 |
Anti-Fraud Engineering for Digital Finance
EUR 171.19
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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.
Overview of Digital Finance Anti Fraud Vertical Association Modeling: Latent Interaction Modeling.- Horizontal Association Modeling: Deep Relation Modeling.- Explicable Integration Techniques: Relative Temporal Position Taxonomy.- Multidimensional Behavior Fusion: Joint Probabilistic Generative Modeling.- Knowledge Oriented Strategies: Dedicated Rule Engine.- Enhancing Association Utility: Dedicated Knowledge Graph.- Associations Dynamic Evolution: Evolving Graph Transformer.
