Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques by Bart Baesens
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.-
Predictive Business Analytics
-
Demand-Driven Forecasting
-
Predictive Analytics for Human Resources
-
Credit Risk Scorecards
-
Business Analytics for Managers
-
Trade-Based Money Laundering
-
Artificial Intelligence for Marketing
-
Statistical Thinking
-
Executive's Guide to Solvency II
-
Harness Oil and Gas Big Data with Analytics
-
The Analytics Lifecycle Toolkit
-
Bank Fraud
-
Visual Six Sigma
-
Analytics
-
Style and Statistics
-
Anti-Money Laundering Transaction Monitoring Systems Implementation
-
Business Intelligence Competency Centers
-
Big Data Analytics
-
The Visual Organization
-
The Data Asset
-
Practitioner's Guide to Operationalizing Data Governance
-
Economic Modeling in the Post Great Recession Era
-
Case Studies in Performance Management
-
Mastering Organizational Knowledge Flow
-
Marketing Automation
-
Business Transformation
-
Heuristics in Analytics
-
Economic and Business Forecasting
-
Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners (Wiley and SAS Business Series)
-
Credit Risk Analytics
-
Profit Driven Business Analytics
-
Agile by Design
-
Killer Analytics
-
The Analytic Hospitality Executive
-
Demand-Driven Inventory Optimization and Replenishment
-
Win with Advanced Business Analytics
-
A Practical Guide to Analytics for Governments
-
Intelligent Credit Scoring
-
Strategies in Biomedical Data Science
-
Next Generation Demand Management
-
Hotel Pricing in a Social World
BART BAESENS is a full professor at KU Leuven, and a lecturer at the University of Southampton. He has done extensive research on analytics, customer relationship management, web analytics, fraud detection, and credit risk management. He regularly advises and provides consulting support to international firms with respect to their analytics and credit risk management strategy.
VÉRONIQUE VAN VLASSELAER is a PhD researcher in the Department of Decision Sciences and Information Management at KU Leuven. Her research focuses on the development of new techniques for fraud detection by combining predictive and network analytics.
WOUTER VERBEKE is an assistant professor at Vrije Universiteit Brussel (Brussels, Belgium). His research is situated in the field of predictive analytics and complex network analysis with applications in fraud, marketing, credit risk, human resources management, and mobility.
| SKU | Unavailable |
| ISBN 13 | 9781119133124 |
| ISBN 10 | 1119133122 |
| Title | Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques |
| Author | Bart Baesens |
| Series | Wiley And Sas Business Series |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | John Wiley & Sons Inc |
| Year published | 2015-10-09 |
| Number of pages | 400 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |