Year: 2011
Type: article
Abstract: Fraud is a multi-billion dollar industry that continues to grow annually. Many organisations are poorly prepared to prevent and detect fraud. Fraud detection strategies are intended to quickly and efficiently identify fraudulent activities that have circumvented preventative measures so that an organisation can take appropriate corrective action. This paper investigates the use of enterprise system audit trails to support fraud detection. A framework for analysing these audit trails for potential fraud is developed. Key components of the framework include; defining the data requirements for fraud detection; and creating a catalogue of fraud symptoms. SAP, a market leading enterprise system is examined. We propose a MCL-based approach for proactive fraud detection that entails periodic extraction and analysis of SAP accounting audit trails for potential fraud. The paper \nemphasises the importance of visual presentation of information as it is this characteristic that enables an auditor to effectively and efficiently find trends, correlations, and identify patterns of activity that may lead to important conclusions regarding potentially fraudulent activities.
Authors: Kishore Singh, Peter Best, Joseph M. Mula
Institutions: Queensland University of Technology, University of Kelaniya
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1494475373