Fraud Analytics Using Descriptive, Predictive, And Social Network Techniques: A Guide To Data Science For Fraud Detection Bart Baesens | Download (PDF/Epub)

[Book] Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection -Bart Baesens

 

Book information:

Title : Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection
Author : Bart Baesens
Publisher : Wiley
Print Length : 72 pages

Book Descriptions:

Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention.It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak.Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.

fraud analytics using descriptive predictive and social. library of congress cataloging in publication data baesens bart fraud analytics using descriptive predictive and social network techniques a guide to data science for fraud detection bart baesens veronique van vlasselaer wouter verbeke pages cm wiley sas business series includes bibliographical references and index.

fraud analytics using descriptive predictive and social. b detect fraud earlier to mitigate loss and prevent cascading damage fraud analytics using descriptive predictive and social network techniques is an authoritative guidebook for. fraud analytics using descriptive predictive and social. detect fraud earlier to mitigate loss and prevent cascading damage fraud analytics using descriptive predictive and social network techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution early detection is a key factor in mitigating fraud damage but it involves more specialized techniques than detecting fraud at the more advanced stages. fraud analytics using descriptive predictive and social. fraud prevention relies on early and effective fraud detection enabled by the techniques discussed here fraud analytics using descriptive predictive and social network techniques helps you stop fraud in its tracks and eliminate the opportunities for future occurrence. fraud analytics using descriptive predictive and social. detect fraud earlier to mitigate loss and prevent cascading damage fraud analytics using descriptive predictive and social network techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution early detection is a key factor in mitigating fraud damage but it involves more specialized techniques than detecting fraud at the mo. fraud analytics using descriptive predictive and social. detecting fraud at an early stage though is more difficult than detecting it later and requires specific techniques fraud analytics provides you with a comprehensive overview of fraud detection analytical techniques and provides implementation guidance for an effective fraud prevention solution to help you detect fraud early.

 

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