1.

Record Nr.

UNINA9910768442003321

Autore

Wang Cheng <1370-1415, >

Titolo

Anti-Fraud Engineering for Digital Finance : Behavioral Modeling Paradigm / / by Cheng Wang

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023

ISBN

981-9952-57-3

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (213 pages)

Collana

Economics and Finance Series

Disciplina

910.5

Soggetti

Social sciences - Data processing

Economics - Psychological aspects

Computer Application in Social and Behavioral Sciences

Behavioral Finance

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

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.

Sommario/riassunto

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.