Электронная книга: Bart Baesens «Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques. A Guide to Data Science for Fraud Detection»

Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques. A Guide to Data Science for Fraud Detection

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.

Издательство: "John Wiley&Sons Limited (USD)"

ISBN: 9781119146827

электронная книга

Купить за 3248.72 руб и скачать на Litres

Другие книги автора:

КнигаОписаниеГодЦенаТип книги
Credit Risk Analytics. Measurement Techniques, Applications, and Examples in SASThe long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house… — John Wiley&Sons Limited (USD), электронная книга Подробнее...5528.36электронная книга
Beginning Java Programming. The Object-Oriented ApproachA comprehensive Java guide, with samples, exercises, case studies, and step-by-step instruction Beginning Java Programming: The Object Oriented Approach is a straightforward resource for getting… — John Wiley&Sons Limited (USD), электронная книга Подробнее...2926.78электронная книга
Analytics in a Big Data World. The Essential Guide to Data Science and its ApplicationsThe guide to targeting and leveraging business opportunities using big data&analytics By leveraging big data&analytics, businesses create the potential to better understand, manage, and strategically… — John Wiley&Sons Limited (USD), электронная книга Подробнее...3248.72электронная книга

Поделиться ссылкой на выделенное

Прямая ссылка:
Нажмите правой клавишей мыши и выберите «Копировать ссылку»