Audit‐firm group appointment: an artificial intelligence approach

Abstract

SUMMARYAuditor appointment can be regarded as a matter of pursued audit quality and is driven by several factors. The adoption of an effective auditor procurement process increases the likelihood that a company will engage the right auditor at a fair price. In this study, three techniques derived from artifi cial intelligence (AI) are used to propose models capable of discriminating between cases where companies appoint a Big 4 or a Non-Big 4 auditor. These three AI methods are then compared with the broadly used method of logistic regression. The results indicate that two of the AI techniques outperform logistic regression. In addition, one method further improves its performance by applying bagging. Finally, signifi cant factors associated with auditor appointment are revealed.

Classifying internal audit quality using textual analysis: the case of auditor selection

“…The results reported in Tables III and IV lead to several conclusions. First, the results of Kirkos et al (2010) are confirmed. Financial variables and ratios can be used to predict the type of the external auditor.…”

“…The average performance of the seven classifiers for the data set of financial figures and ratios is 83.3 per cent. Notably, this study and Kirkos et al (2010) use different data sets, as Kirkos et al (2010) used data from British and Irish companies. Second, the models which were developed using textual information predict the type of audit firm selected with similar accuracy.…”

“…More specifically, the Decision Tree model and the Support Vector Machine model showed that the greater a company’s debt, the more likely they will select a well-known auditor. In another study, Kirkos et al (2010) used financial ratios to predict the type of auditor, achieving satisfactory accuracy rates ranging from 69 to 82 per cent, depending on the used classifier.…”

“…For this reason more than one algorithm is frequently used. As an example, in accounting research, Kirkos et al (2010) developed several computational models to classify audit firm selection (Big 4 vs. non-Big 4) using financial data. The results indicated that two of the AI techniques performed better (i.e.…”

Perspective Chapter: Audit Digitalization – Key Impacts on the Audit Profession

“…In a world where every facet can be digitally enabled through emerging technologies, enterprises in all industries will need to adapt to keeping pace and prosper or will ultimately risk unplanned obsoletion [1]. Advances in emerging technologies have the potential to impact and disrupt the audit industry, most notably in big data analytics [2][3][4][5], artificial intelligence (AI) [6,7] and blockchain technology [3,8,9]. Audit firms cannot simply be familiar with emerging technologies any longer [10], as these principles and concepts have the potential to integrate with their existing processes and skills or replace them [11,12].…”