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Springer Anti-Fraud Engineering for Digital Finance - Behavioral Modeling

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Description

This comprehensive guide introduces anti-fraud strategies in digital finance through the lens of behavioral modeling, addressing the critical challenges of insufficient and poor-quality behaviour data. The book presents a unified framework that merges technology, scenarios, and data analytics to strengthen fraud detection without replacing existing security systems. Rather than serving as a primary defence, it functions as a sophisticated second security layer designed to complement your current anti-fraud infrastructure. By examining common vulnerabilities across various financial sectors, this work equips professionals with the knowledge to apply the behavioural modeling paradigm across diverse applications, enabling organisations to build more resilient and adaptive fraud prevention systems that respond intelligently to emerging threats.

Key Features

The book covers anti-fraud engineering strategies specifically tailored to digital finance environments using behavioural modeling techniques.

Presents solutions for improving anti-fraud performance by combining technology, scenarios, and data into a unified perspective.

Offers a non-intrusive second security layer that complements rather than replaces existing anti-fraud solutions.

Examines common weaknesses across typical financial fields to support the behavioural modeling paradigm in multiple applications.

Published by Springer, providing academic credibility and expertise in digital finance security and fraud prevention.

Addresses data quality challenges and behavioural patterns critical to understanding modern financial fraud mechanisms.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
05 December 2023
Listed Since
30 June 2023

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