Fraud Detection Gap between Auditor and Fraud Detection Models: Evidence from Gulf Cooperation Council

Abstract

This study investigates an auditor’s fraud detection gap (FDG) in Gulf Cooperation Council (GCC) companies by comparing the result of the fraud detection models (namely the Beneish M-score, Dechow F-score, and Altman Z-score) with an actual of audit opinion given by the auditors. Prior scholars documented that financial models are accurate and important measurements in fraud detection. However, the majority of fraud cases in the region are revealed accidentally which indicates the unclear role of the internal and external auditor. The data consists of 365 companies operated in the GCC for the period from 2015 to 2017 with a total of 1,095 observations. The study found that the success rate of detecting financial statement frauds for Dechow F model is much higher than Beneish M or Altman Z models. The result also indicated that the highest FDG-score results were obtained by the Dechow F model. However, the Beneish M model can detect financial statements’ fraud better for companies associated to local audit firms as compared to international audit firms. Additionally, Big 4 audit firms are associated with a lower FDG in Beneish M model but increase FDG in Altman Z model. Hence, the study supported the inclusion of statistical models, to a certain extent, as an alternative or supplementary method that assisted in making better decision-making for companies within the Gulf States. The regulators, policy maker, and practitioners, mainly the audit firms must concern that the ability to detect financial statement’s fraud can be enhanced by utilizing the appropriate fraud detection model.