Predicting Audit Quality: Systemic Issues and Predictive Modeling of PCAOB Inspections on European audit firms between 2013-2023

Abstract

This study offers a comprehensive evaluation of Public Company Accounting Oversight Board (PCAOB) inspection reports concerning European audit firms over the period from 2013 to 2023. The research focuses on identifying systemic audit deficiencies and assessing the effectiveness of PCAOB-recommended interventions. By analyzing 120 inspection reports across several European countries, the study reveals pervasive issues in internal controls, particularly in areas such as revenue recognition, accounts receivable, and audit documentation. A mixedmethods approach is employed, combining multiple regression analysis and machine learning techniques to uncover significant predictors of these deficiencies, alongside qualitative insights that contextualize recurring problems. The findings highlight the complex, interrelated nature of audit processes and underscore the critical role of robust internal controls and adherence to PCAOB standards in enhancing audit quality. This research contributes to the literature by providing actionable recommendations for improving audit practices, thus offering valuable insights for regulators, policymakers, and audit professionals. The study’s implications extend to advancing regulatory effectiveness and ensuring higher standards of financial reporting in the European context.