Financial Statements Fraud

56771 Words Jul 3rd, 2013 228 Pages
University of South Florida

Scholar Commons
Graduate School Theses and Dissertations Graduate School

6-1-2008

Detecting financial statement fraud: Three essays on fraud predictors, multi-classifier combination and fraud detection using data mining
Johan L. Perols
University of South Florida

Follow this and additional works at: http://scholarcommons.usf.edu/etd Part of the American Studies Commons Scholar Commons Citation
Perols, Johan L., "Detecting financial statement fraud: Three essays on fraud predictors, multi-classifier combination and fraud detection using data mining" (2008). Graduate School Theses and Dissertations. http://scholarcommons.usf.edu/etd/449

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Dissertation Overview............................................................................................... 1 1.1. 1.2. 2.1. 2.2. 2.3. 2.3.1 2.3.2 2.3.2.1 2.3.2.2 2.3.2.3 2.4. 2.4.1 2.4.2 2.4.2.1 2.4.2.2 2.4.2.3 2.4.2.4 2.4.3 2.4.3.1 2.4.3.2 2.4.3.3 2.5. 2.5.1 2.5.1.1 Research Framework.......................................................................................... 1 Overview of the Three Essays ............................................................................ 3 Introduction ........................................................................................................ 5 Related Research ................................................................................................ 7 Information Market Based Fusion...................................................................... 8 Information Markets .................................................................................... 8 Information Market Based Fusion ............................................................... 9 Determining Final Odds.......................................................................... 10 Classifying Objects................................................................................. 14 Distributing Payout ................................................................................. 14 Base-Classifiers and Data
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