Anti-Fraud Engineering for Digital Finance - Behavioral Modeling Paradigm
| Verlag | Springer |
| Auflage | 2023 |
| Seiten | 207 |
| Format | 15,5 x 1,3 x 23,5 cm |
| Artikeltyp | Englisches Buch |
| EAN | 9789819952564 |
| Bestell-Nr | 81995256DA |
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.
Inhaltsverzeichnis:
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.
