Title: Fraud detection using data mining
Creator: Pienaar, Abel Jacobus
Subject: Computer crimes, Forensic accounting, Data mining
Date: 2014-02-10
Type: Thesis
Identifier: uj:3733
Identifier: http://hdl.handle.net/10210/9112
Description: M.Com. (Computer Auditing), Fraud is a major problem in South Africa and the world and organisations lose millions each year to fraud not being detected. Organisations can deal with the fraud that is known to them, but undetected fraud is a problem. There is a need for management, external- and internal auditors to detect fraud within an organisation. There is a further need for an integrated fraud detection model to assist managers and auditors to detect fraud. A literature study was done of authoritative textbooks and other literature on fraud detection and data mining, including the Knowledge Discovery Process in databases and a model was developed that will assist the manager and auditor to detect fraud in an organisation by using a technology called data mining which makes the process of fraud detection more efficient and effective.
Contributor: Du Toit, A., Prof.
Rights: University of Johannesburg
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Fraud detection using data mining