Proactive fraud detection in enterprise systems
Paper
Paper/Presentation Title | Proactive fraud detection in enterprise systems |
---|---|
Presentation Type | Paper |
Authors | Singh, Kishore (Author), Best, Peter (Author) and Mula, Joseph M. (Author) |
Journal or Proceedings Title | Proceedings of the 2nd International Conference on Business and Information: Steering Excellence of Business Knowledge (ICBI 2011) |
ERA Conference ID | 60409 |
Number of Pages | 15 |
Year | 2011 |
Place of Publication | Kelnaiya, Sri Lanka |
ISBN | 9789559044963 |
Web Address (URL) of Paper | http://www.kln.ac.lk/fcms/ICBI2011/ |
Conference/Event | 2nd International Conference on Business and Information: Steering Excellence of Business Knowledge (ICBI 2011) |
International Conference on Business and Information (BAI) | |
Event Details | 2nd International Conference on Business and Information: Steering Excellence of Business Knowledge (ICBI 2011) Event Date 20 Oct 2011 Event Location Kelaniya, Sri Lanka |
Event Details | International Conference on Business and Information (BAI) BAI |
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 |
Keywords | fraud detection, enterprise system, continuous monitoring, audit trail |
ANZSRC Field of Research 2020 | 350199. Accounting, auditing and accountability not elsewhere classified |
Public Notes | No evidence of copyright restrictions, or refereed status. |
Byline Affiliations | School of Accounting, Economics and Finance |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q16vy/proactive-fraud-detection-in-enterprise-systems
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