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Applying Data Mining Methodologies for Auditor Selection

Auditor selection can be regarded as a matter of audit quality. Research studies aiming to model the auditor choice employ statistical techniques. Here we employ three techniques derived from the Data Mining domain to build models capable of discriminating cases where companies choose a Big 4 or a Non-Big 4 auditor. Significant factors associated with the auditor choice are revealed. The three models are compared in terms of their performances. According to 10-fold cross validation bagging increases significantly the performance of one classifier.