Identifying Qualified Auditors' Opinions: A Data Mining Approach

Data Mining tools and methods can be used to facilitate auditors to issue their opinions. Numerous of these methods have not yet been tested for the purpose of discriminating cases of qualified opinions. In this study we employ three Data Mining classification techniques to develop models capable to predict qualified auditors' reports. The input vector is composed of quantitative and qualitative variables. The three developed models are compared in terms of their performances. Additionally, variables which are associated with qualified reports and can be used as indicators are revealed. The results of this study can be useful to internal and external auditors and company decision makers.