Computer-assisted audit techniques based on an enhanced rough set model

  title={Computer-assisted audit techniques based on an enhanced rough set model},
  author={Ping-Feng Pai and Ming-Fu Hsu and Ming-Chieh Wang},
  journal={The 6th International Conference on Networked Computing and Advanced Information Management},
Due to the uncertainty of the business environment and critical competition, financial statement fraud (FSF) risk is higher than in past decades. Most FSF is caused by top managers who have the authority to override the internal controls and deploy de facto power against audit committees. An auditor is the last line of defense to detect FSF. Unfortunately, many auditors lack the expertise and experience to deal with related risks. In recent years, with the development of information technology… CONTINUE READING

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Showing 1-10 of 23 references

Causes, consequences, and deterence of financial statement fraud

  • Z. Rezaee
  • Critical Perspectives on Accounting, voL 16,
  • 2005

The relation between the new corporate governance rules and likelihood of financial statement fraud

  • O. S. Persons, S. Milind, T Zeng, V. Uma
  • Review of Accounting and Finance,
  • 2005

Swiniarski , and A Skowron , " Rough set methods in feature selection and recognition "

  • J. Aires-de-Sousa Caetano, M. Daszykowski
  • Pattern Recognition Letters
  • 2003

Fraud detection: Using data analysis techniques to detect fraud

  • G. D. Coderre
  • Global Audit Publications,
  • 1999

Cogger, "Neural network detection of management fraud using published financial data

  • K Fanning
  • International Journal of Intelligent Systems in…
  • 1998

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