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Case‐Based Reasoning and Risk Assessment in Audit Judgment

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  • Eric L. Denna
  • James V. Hansen
  • Rayman D. Meservy
  • Larry E. Wood

Abstract

The purpose of this paper is to describe the results of an effort to utilize case‐based reasoning (CBR) to model a specific audit judgment task. To date, most efforts to develop computational models of audit judgment have used strictly rule‐based representation methods. Some researchers have recently adopted more robust structures to model the auditor domain knowledge. Although these recent efforts to extend the representation methods appear to be more accurate descriptions of auditor reasoning and memory, they still lack a comprehensive theory to guide the development of the model. A commonly encountered phenomenon in audit judgment is for an auditor to compare the current case to similar previous experiences. Others have proposed a model for this type of judgment in other expert judgment domains. This model has become known as case‐based reasoning (CBR). This study describes our initial efforts to utilize CBR to model a specific audit judgment task.

Suggested Citation

  • Eric L. Denna & James V. Hansen & Rayman D. Meservy & Larry E. Wood, 1992. "Case‐Based Reasoning and Risk Assessment in Audit Judgment," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 1(3), pages 163-171, September.
    • Handle: RePEc:wly:isacfm:v:1:y:1992:i:3:p:163-171
    DOI: 10.1002/j.1099-1174.1992.tb00018.x
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    1. William F. Messier, Jr. & James V. Hansen, 1988. "Inducing Rules for Expert System Development: An Example Using Default and Bankruptcy Data," Management Science, INFORMS, vol. 34(12), pages 1403-1415, December.
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