BIG DATA ANALYTICS IN DIGITAL ACCOUNTING: UNLOCKING FINANCIAL ACCURACY THROUGH PREDICTIVE ANALYTICS IN JORDANIAN CORPORATIONS

Abstract This study examines the mediating role of Data Quality and Integration Processes (DQIP) in the relationship between Big Data Analytics (BDA), Predictive Analytics Techniques (PAT), and Financial Accuracy (FACC) in Jordanian corporations. Targeting 850 financial professionals from 120 firms listed on the Amman Stock Exchange, a sample of 265 respondents was analyzed using PLS-SEM. The results confirm that BDA and PAT significantly improve FACC, with BDA showing a stronger direct effect. DQIP fully mediates these relationships, demonstrating its critical role in enhancing financial outcomes. The findings align with the Resource-Based View and Information Processing Theory, highlighting the interplay between technological resources and organizational processes. The study provides practical insights for managers to prioritize DQIP alongside analytics adoption, ensuring accurate financial reporting. Its originality lies in addressing the under-researched Jordanian context, offering empirical evidence on DQIP’s mediation in emerging markets, and bridging theoretical gaps in digital accounting literature. The implications extend to policymakers and firms seeking to optimize analytics investments in resource-constrained environments.