The Impact of Audit Data Analytics in The Relationship Between Internal and External Auditors in The Kingdom of Saudi Arabia

Abstract

The rapid advancement of technology is significantly reshaping auditing practices globally. Among these innovations, Audit Data Analytics (ADA) has emerged as a transformative tool, enhancing the capacity of auditors to analyse large datasets, detect risks, and improve decision-making. This thesis investigates the impact of ADA on the relationship between internal auditor (IA) and external auditor (EA) in the Kingdom of Saudi Arabia (KSA), a region undergoing rapid digital and economic transformation aligned with the kingdom’s “Vision 2030.” Despite the importance of the IA–EA cooperation for audit quality and efficiency, limited research has explored how emerging technologies such as ADA influence these dynamics, particularly in developing economies. Drawing upon Relational Coordination Theory (RCT), this study develops a conceptual model centred on organisational design, inter-organisational networks, and performance outcomes. The research examines how ADA affects IA attributes (competence, objectivity, quality of work), EA attributes (work style, risk assessment), and IA–EA cooperation, ultimately impacting audit effectiveness and audit fees. This study adopts a multiple methods approach employing an explanatory sequential multiple-methods design. The researcher first conducted 22 semi-structured interviews with internal and external auditors, followed by a survey receiving 107 valid responses. Findings from both interviews and survey data reveal that ADA has a strong positive influence on IA competencies. IAs have enhanced their data analytical capabilities, critical thinking, and technological skills, with many organisations recruiting specialists in business intelligence, data science, and artificial intelligence. ADA also strengthens IA objectivity by minimising human bias and allowing auditors to rely on data-driven assessments. Furthermore, audit quality has improved, as auditors are now able to perform full-population testing, leading to higher accuracy and reliability. The influence of ADA on EA attributes is more nuanced. Interviews suggest some improvements in EA work styles, such as greater precision and standardisation. However, survey results indicate that these changes are still evolving, with no statistically significant relationship yet established. Nevertheless, ADA has significantly enhanced EA risk assessment capabilities, allowing EAs to detect anomalies, reassess risks, and make more informed audit decisions. In terms of IA–EA cooperation, ADA has begun to foster stronger collaboration, although complete integration remains a work in progress. Improvements in IA outputs and increased reliability of IA work are gradually encouraging greater EA reliance. Both qualitative and quantitative findings support the view that ADA acts as a relational enabler, facilitating better communication and reducing audit redundancies. Regarding audit outcomes, the study finds that ADA adoption enhances audit effectiveness by improving audit quality, transparency, and timeliness. However, its impact on audit fees is mixed; while ADA reduces duplication and improves efficiency in some cases, the costs of technology adoption can offset potential fee reductions. In conclusion, this thesis indicates that ADA is not merely a technological tool but a catalyst for reshaping auditor relationships, enhancing audit processes, and fostering cooperation in KSA. It offers valuable insights for practitioners, policymakers, and researchers seeking to understand and leverage emerging technologies to improve audit quality in rapidly evolving economic landscapes.