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Show Notes
Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques (Bart Baesens)
- Amazon USA Store: https://www.amazon.com/dp/B012WA66SK?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Fraud-Analytics-Using-Descriptive%2C-Predictive%2C-and-Social-Network-Techniques-Bart-Baesens.html
- eBay: https://www.ebay.com/sch/i.html?_nkw=Fraud+Analytics+Using+Descriptive+Predictive+and+Social+Network+Techniques+Bart+Baesens+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/B012WA66SK/
#Descriptivefraudanalytics #Predictivefraudscoring #Socialnetworkanalysis #Anomalydetection #Frauddetectionreturnoninvestment #FraudAnalyticsUsingDescriptivePredictiveandSocialNetworkTechniques
Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is a professional data science guide by Bart Baesens, Véronique Van Vlasselaer, and Wouter Verbeke. Positioned in the SAS Business Series, it examines how organizations can detect and prevent fraud through evidence drawn from operational data rather than through isolated rules or intuition. The book is not limited to a single industry or algorithm. Instead, it presents fraud analytics as a decision process combining descriptive analysis, predictive modeling, and social network methods. Descriptive techniques establish what normal and abnormal behavior looks like; predictive techniques estimate the likelihood that an event or entity is fraudulent; and network analysis investigates links among people, accounts, transactions, and shared resources. The authors also place technical work in a business setting, addressing investigation, model deployment, costs, benefits, and return on investment. Its purpose is to help practitioners frame fraud detection as an ongoing, measurable capability that balances loss prevention, customer treatment, operational capacity, and analytical rigor.
- Amazon USA Store: https://www.amazon.com/dp/B012WA66SK?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Fraud-Analytics-Using-Descriptive%2C-Predictive%2C-and-Social-Network-Techniques-Bart-Baesens.html
- eBay: https://www.ebay.com/sch/i.html?_nkw=Fraud+Analytics+Using+Descriptive+Predictive+and+Social+Network+Techniques+Bart+Baesens+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/B012WA66SK/
#Descriptivefraudanalytics #Predictivefraudscoring #Socialnetworkanalysis #Anomalydetection #Frauddetectionreturnoninvestment #FraudAnalyticsUsingDescriptivePredictiveandSocialNetworkTechniques
Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is a professional data science guide by Bart Baesens, Véronique Van Vlasselaer, and Wouter Verbeke. Positioned in the SAS Business Series, it examines how organizations can detect and prevent fraud through evidence drawn from operational data rather than through isolated rules or intuition. The book is not limited to a single industry or algorithm. Instead, it presents fraud analytics as a decision process combining descriptive analysis, predictive modeling, and social network methods. Descriptive techniques establish what normal and abnormal behavior looks like; predictive techniques estimate the likelihood that an event or entity is fraudulent; and network analysis investigates links among people, accounts, transactions, and shared resources. The authors also place technical work in a business setting, addressing investigation, model deployment, costs, benefits, and return on investment. Its purpose is to help practitioners frame fraud detection as an ongoing, measurable capability that balances loss prevention, customer treatment, operational capacity, and analytical rigor.
