[Télécharger] Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection de Bart Baesens,Veronique Van Vlasselaer,Wouter Verbeke Livre eBook France
Télécharger Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection de Bart Baesens,Veronique Van Vlasselaer,Wouter Verbeke Livres En Ligne
Télécharger "Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection" de Bart Baesens,Veronique Van Vlasselaer,Wouter Verbeke livre En ligne
Auteur : Bart Baesens,Veronique Van Vlasselaer,Wouter Verbeke
Catégorie : Livres anglais et étrangers,Business & Investing,Industries & Professions
Broché : * pages
Éditeur : *
Langue : Français, Anglais
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.
Télécharger Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection de Bart Baesens,Veronique Van Vlasselaer,Wouter Verbeke Francais PDF
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A Fraud Detection Approach with Data Mining in Health ~ Data mining tools and techniques can be used to detect fraud in large sets of insurance claim data. One of the most common data mining techniques used for finding fraudulent records is anomaly detection. This technique aims to detect outliers or anomalies which deviate from the usual patterns. For example, an anomaly in data traffic pattern in a computer network could be an indication of .
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Seven ways predictive analytics can improve healthcare ~ The patient's genome includes a gene marker for early onset Alzheimer's disease, determined by researchers using predictive analytics. This gene is rare and runs in the patient's family on one side. Several years ago, when it was first discovered, the patient agreed to have his blood taken to see if he had the gene. He did. There was no gene treatment available, but evidence based research .
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Predictive Analytics / IBM ~ Predictive analytics is the use of advanced analytic techniques that leverage historical data to uncover real-time insights and to predict future events. The use of predictive analytics is a key milestone on your analytics journey — a point of confluence where classical statistical analysis meets the new world of artificial intelligence (AI). Predictive analytics can help you transform the .
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