Rule based fuzzy reasoning system for assessing the risk of management fraud

Ashutosh Deshmukh, T. L.N. Talluru

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

Statement on Auditing Standards (SAS) No. 53 requires that the audit be designed to provide a reasonable assurance of detecting management fraud. Traditionally auditors have utilized personal, business, and economic red flags in risk analysis and audit planning. Touche Ross, Coopers and Lybrand, and Price Waterhouse released a list of red flags based on business and economic factors that can be used as a set of warning indicators. SAS No. 53 cites several examples of red flags, such as management operations and financial decisions dominated by a single person, management's unduly aggressive attitude toward financial reporting, and management's poor reputation in the business community. The purpose of this paper is to demonstrate the use of a rule based fuzzy reasoning system to assess the risk of management fraud. Based on the Bell et al. study we identified statistically significant red flags for each assessing the risk of management fraud. Using the statistical significance of each red flag and the theoretical model we developed membership functions and fuzzy rules. The rule based system was implemented in XpertRule. Then the fuzzy reasoning system tested using the same fraud data as in Bell et al. and the results obtained were similar to statistical models. The fuzzy reasoning system can be used as an intuitive decision aid in assessing the risk of management fraud and in structured decision making.

Original languageEnglish (US)
Pages (from-to)669-673
Number of pages5
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume1
StatePublished - Dec 1 1997
EventProceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics. Part 1 (of 5) - Orlando, FL, USA
Duration: Oct 12 1997Oct 15 1997

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Hardware and Architecture

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