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    Anti-Fraud Engineering for Digital Finance: Behavioral Modeling Paradigm

    Anti-Fraud Engineering for Digital Finance by Wang, Cheng;

    Behavioral Modeling Paradigm

      • GET 8% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 171.19
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        72 618 Ft (69 160 Ft + 5% VAT)
      • Discount 8% (cc. 5 809 Ft off)
      • Discounted price 66 809 Ft (63 627 Ft + 5% VAT)

    72 618 Ft

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    Availability

    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Springer
    • Date of Publication 6 December 2024
    • Number of Volumes 1 pieces, Book

    • ISBN 9789819952595
    • Binding Paperback
    • No. of pages207 pages
    • Size 235x155 mm
    • Language English
    • Illustrations 20 Illustrations, black & white; 75 Illustrations, color
    • 668

    Categories

    Short description:

    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.

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    Long description:

    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.

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    Table of Contents:

    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.

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