Identifying qualified auditors' opinions : a data mining approach

Spathis, Charalambos/ Nanopoulos, Alexandros/ Manolopoulos, Yannis/ Kirkos, Efstathios/ Κύρκος, Ευστάθιος/ Μανωλόπουλος, Γιάννης/ Σπαθής, Χαράλαμπος/ Νανόπουλος, Αλέξανδρος

Institution and School/Department of submitter: ΤΕΙ Θεσσαλονίκης
Keywords: Qualified auditors opinions;Ελεγκτές ορκωτοί λογιστές;Chartered accountant;Audits;Απόψεις ειδικευμένων ελεγκτών;Έλεγχοι;Ελεγκτική διαδικασία;Audit procedure;Qualified opinions (Auditing);Ειδικευμένες απόψεις (Ελεγκτική)
Issue Date: Dec-2007
Publisher: American Accounting Association
Citation: Kirkos, E., Spathis, C., Nanopoulos, A., Manolopoulos, Y. (1 Δεκεμβρίου 2007). Identifying Qualified Auditors' Opinions: A Data Mining Approach. Journal of Emerging Technologies in Accounting 4, (1). Διαθέσιμο σε: (Ανακτήθηκε 30 Ιουνίου 2015).
Journal: Journal of Emerging Technologies in Accounting, vol. 4, no. 1, 2007
Abstract: Data Mining methods can be used in order to facilitate auditors to issue their opinions. Numerous of these methods have not yet been tested on the purpose of discriminating cases of qualified opinions. In this study, we employ three Data Mining classification techniques to develop models capable of identifying qualified auditors' reports. The techniques used are C4.5 Decision Tree, Multilayer Perceptron Neural Network, and Bayesian Belief Network. The sample contains 450 publicly listed, nonfinancial U.K. and Irish firms. The input vector is composed of one qualitative and several quantitative variables. The three developed models are compared in terms of their performance. Additionally, variables that are associated with qualified reports and can be used as indicators are also revealed. The results of this study can be useful to internal and external auditors and company decision‐makers.
Description: Δημοσιεύσεις μελών--ΣΔΟ--Τμήμα Λογιστικής, 2007
ISSN: 1558-7940
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Appears in Collections:Δημοσιεύσεις σε Περιοδικά

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