Forecasting the Type of Audit Opinions: A Data Mining Approach

Subject Areas : Management Accounting

محمدحسین  ستایش ¹ (ندارد)
فهیمه  ابراهیمی ² (ندارد)
سیدمجتبی  سیف ³ (ندارد)
مهدی  ساریخانی ⁴ (ندارد)

Received: 2012-04-08 Accepted : 2012-08-05 Published : 2013-03-09

Keywords: Audit Opinion, Artificial Neural Networks, Support Vector Machines, nearest neighbors, Decision tree,

Abstract :

Data mining methods can be used to assist auditors with providing audit opinions.The purpose of this research is to forecast the type of audit opinions using data miningmethods and compare the performance of these methods. Artificial neural networks,support vector machines, nearest neighbors and decision tree methods were used toconduct the research. The sample consists of 842 observations between 2001 and 2010.The observations were divided in two groups: one group for training and the other forassessment of the method. A comparison of the performance of methods indicates thatsupport vector machines approach outperforms the other approaches with a predictiveability of 76%. Also measuring type I and type II error rates of each method shows thatthe performance of support vector machines is higher than the other methods.