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Control risk assessment in auditing: Artificial neural network approach

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Author Info
F.Münevver YILANCI (Osmangazi Üniversitesi)
Birol YILDIZ (Osmangazi Üniversitesi)
Abstract

The purpose of the study is to develop a decision support tool with Artificial Neural Network for the use of external auditors in assessing preliminary control risk level. A survey was conducted to collect internal control data of top 500 industrial corporations in Turkey. The number of surveys returned was 169 out of 500. An external auditor assessed control risk level for each corporation. While the research used 100 firms to develop an artificial neural network model, the remaining 69 firms were selected for testing the model. The findings indicated that the artificial neural network model could mimic the auditor’s decision. The category accuracy rate between the predictions of the artificial neural network model and the auditor opinion was 71.01%. In conclusion, the artificial neural network model provided a useful decision support tool for auditors to assess preliminary control risk level.

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Publisher Info
Article provided by Bilgesel Yayincilik in its journal İktisat İşletme ve Finans.

Volume (Year): 23 (2008)
Issue (Month): 273 ()
Pages: 119-132
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:iif:iifjrn:v:23:y:2008:i:273:p:119-132

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Web page: http://iif.com.tr

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Related research
Keywords: Auditing; Internal Control; Risk Assessment; Artificial Neural Networks;

Find related papers by JEL classification:
C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
M42 - Business Administration and Business Economics; Marketing; Accounting - - Accounting - - - Auditing

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This page was last updated on 2009-12-11.


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