An analysis of fuzzy clustering and a hybrid model for the auditor's going concern assessment

An analysis of fuzzy clustering and a hybrid model for the auditor's going concern assessment

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Article ID: iaor20031707
Country: United States
Volume: 31
Issue: 4
Start Page Number: 861
End Page Number: 884
Publication Date: Oct 2000
Journal: Decision Sciences
Authors: , ,
Keywords: artificial intelligence: decision support
Abstract:

This study provides a description and testing of fuzzy clustering and a hybrid model that can support the decision an auditor makes when completing the going concern evaluation. Fuzzy clustering is based on fuzzy logic, and the hybrid system is designed to address the going concern decision through the combined use of a statistical model and an expert system. These models have the capability of identifying categories of firms with particular characteristics that may indicate whether or not the audit report of the firms requires a going concern modification. A prediction of whether or not a firm may go bankrupt is included as one of the components of the going concern decision. As a result, if a firm is placed in a particular bankrupt category by a decision model, it may help in the determination of the auditor's opinion regarding the continuity of the business.

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