Internal fraud risk reduction: Results of a data mining case study

International Journal of Accounting Information Systems

Volumn 11, Issue 1, 2010, Pages 17-41

  Jans, Mieke ^a   Lybaert, Nadine ^a   Vanhoof, Koen ^a  

^a HASSELT UNIVERSITY   (Belgium)

Author keywords

Data mining; Internal fraud; Latent class clustering; Risk reduction

Indexed keywords

EID: 77049099784     PISSN: 14670895     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.accinf.2009.12.004     Document Type: Article

References (23)

1. ACFE. 2008 ACFE report to the nation on occupational fraud and abuse (2008), Technical report, Association of Certified Fraud Examiners
2. Alles M., Brennan G., Kogan A., and Vasarhelyi M.A. Continuous monitoring of business process controls: a pilot implementation of a continuous auditing systems at Siemens. Int J Account Inf Syst 7 (2006) 137-161
3. Alles M.G., Kogan A., and Vasarhelyi M. Restoring auditor credibility: tertiary monitoring and logging of continuous assurance systems. Int. J. Account. Inf. Syst. 5 (2004) 183-202
4. Brockett P.L., Derrig R.A., Golden L.L., Levine A., and Alpert M. Fraud classification using principal component analysis of RIDITs. J Risk Insur 69 3 (2002) 341-371
5. Cortes C., Pregibon D., and Volinsky C. Communities of interest. Intell Data Anal 6 (2002) 211-219
6. Dowling C., and Leech S. Audit support systems and decision aids: current practice and opportunities for future research. Int J Account Inf Syst 8 (2007) 92-116
7. Elsas Ph.I. X-raying segregation of duties: support to illuminate an enterprise's immunity to solo-fraud. Int J Account Inf Syst 9 (2008) 82-93
8. Estévez P., Held C., and Perez C. Subscription fraud prevention in telecommunications using fuzzy rules and neural networks. Expert Syst Appl 31 (2006) 337-344
9. Fanning K., and Cogger K. Neural network detection of management fraud using published financial data. Int J Intell Syst Account, Finance Manag 7 (1998) 21-41
10. Grabski S.V., and Leech S.A. Complementary controls and ERP implementation success. Int J Account Inf Syst 8 (2007) 17-39
11. Hagenaars J.A., and McCutcheon A.L. Applied latent class analysis (2002), Cambridge University Press
12. 2 framework. Int J Digit Account Res 9 (2009) 1-29
13. Kaplan D. The sage handbook of quantitative methodology for the social sciences (2004), Sage Publications, Thousand Oaks
14. Kim H., and Kwon W.J. A multi-line insurance fraud recognition system: a government-led approach in Korea. Risk Manag Insur Rev 9 2 (2006) 131-147
15. Kirkos E., Spathis C., and Manolopoulos Y. Data mining techniques for the detection of fraudulent financial statements. Expert Syst Appl 32 (2007) 995-1003
16. Kogan A., Sudit E., and Vasarhelyi M. Continuous online auditing: a program of research. J Inf Syst 13 2 (1999) 87-103
17. Li S.-H., Huang S.-M., and Lin Y.-C.G. Developing a continuous auditing assistance system based on information process models (2007), J Comp Inf Syst, Fall 2-13
18. Li C., Lim J.-H., and Wang Q. Internal and external influences on IT control governance. Int J Account Inf Syst 8 (2007) 225-239
19. Lynch A., and Gomaa M. Understanding the potential impact of information technology on the susceptibility of organizations to fraudulent employee behaviour. Int J Account Inf Syst 4 (2003) 295-308
20. Magidson J., and Vermunt J.K. Latent class models for clustering: a comparison with k-means. Can J Mark Res (2002)
21. Mock T.J., Sun L., Srivastava R., and Vasarhelyi M. An evidential reasoning approach to Sarbanes-Oxley mandated internal control risk assessment. Int J Account Inf Syst 10 (2009) 65-78
22. PwC. Economic crime: people, culture and controls. The 4th biennial global economic crime survey. Technical report (2007), PriceWaterhouse & Coopers
23. Wells J.T. Principles of fraud examination (2005), John Wiley & Sons