How Does Big Data Mining Affect Financial Reporting Quality in Saudi Banks? A Mediated and Moderated Model

Abstract

High quality of financial reports is crucial to fostering transparency, boosting market reliability, and facilitating efficient decision-making in the banking industry, especially in growing markets like Saudi Arabia. Although reforms in regulation and the adoption of International Financial Reporting Standards (IFRS), financial reporting quality (FRQ) still an ongoing challenge due to data complexity, risk management techniques, and regulatory capability. The present research investigates the mediating role of Enterprise Risk Management (ERM) and the moderating role of IT readiness in the relationship between big data mining (BDM) and financial reporting quality in the Saudi banking sector. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings demonstrate that mining of big data has a significant effect on FRQ and significantly improves ERM practices. Furthermore, Enterprise Risk Management has been shown to strongly moderate the association between BDM and financial reporting quality, emphasizing its importance in turning data-driven insights into better reporting outcomes. Yet, IT readiness has insignificant impact in BDM–FRQ nexus, implying that technology alone is not a sufficient condition for improving financial reporting quality. This article suggests that banks should integrate big data analytics into complete enterprise risk management frameworks rather than relying exclusively on technological investments. By emphasizing the necessity of integrating big data analytics within enterprise risk management to boost financial reporting quality and further the goals of Saudi Vision 2030, these outcomes have significant implications for bank managers and policymakers.