 Control risk assessment in auditing: Artificial neural network approachF.Münevver Yilanci and
Birol Yildiz
Iktisat Isletme ve Finans, 2008, vol. 23, issue 273, 119-132 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. Keywords: Auditing; Internal Control; Risk Assessment; Artificial Neural Networks (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:iif:iifjrn:v:23:y:2008:i:273:p:119-132 Ordering information: This journal article can be ordered from Access Statistics for this article Iktisat Isletme ve Finans is currently edited by Ali Bilge More articles in Iktisat Isletme ve Finans from Bilgesel Yayincilik |
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