Need for Next Generation Fraud Detection is Huge: Applying Purpose-Built Analytics to Spotlight Fraud in Real Time

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This report discusses how some types of fraud have grown more sophisticated. It also explains how the escalating number of advanced methods used by would-be perpetrators¯to gain ill-gotten revenue and/or to create mayhem for the organizations they target¯is capturing CSP attention. The report further explains how new generation fraud management tools, using big data concepts tied to data collection from data lakes and real-time machine learning analysis, are becoming a more effective means for identifying communications fraud. Through the machine-learning approach, initiated by companies such as Argyle Data, advanced forms of communications fraud can be identified faster, and new forms of fraud can be discovered more easily.

Table of Contents

Need for Next Generation Fraud Detection is Huge: Applying Purpose-Built Analytics to Spotlight Fraud in Real TimeSPIE 2016 #30 - August 19/2016IntroductionWhat is Communications Fraud Management?Today's Revenue Threat ChallengesWhy Fraud Detection and Identification Matter So MuchHow the Magic Happens: Fraud Management Machine-Learning StyleWhy Real-Time Fraud Detection and Why Argyle Data?Stratecast - The Last WordAbout ODAMAbout StratecastAbout Frost & Sullivan




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