The Big Data in Financial Reporting: A Bibliometric Analysis of Global Research Trends

Abstract

This study aims to analyze the utilization of Big Data in financial reporting through bibliometric analysis and to identify global research trends in this field. In an increasingly complex and dynamic business environment, financial reports serve as a crucial tool for communication between companies and stakeholders, including investors, creditors, and regulators. The exponential growth of data presents challenges in effectively managing and analyzing this information, where Big Data offers opportunities to enhance accuracy, efficiency, and transparency in financial reporting. Using data from leading academic databases such as Scopus and Publish or Perish, the analysis reveals a significant increase in publications related to Big Data in financial reporting over the past decade, reflecting the growing interest in leveraging Big Data technologies to improve financial practices. This study identifies prominent authors and institutions contributing to this literature and highlights dominant research themes such as predictive analytics, data-driven decision-making, transparency and accountability, as well as the integration of new technologies such as artificial intelligence and machine learning. Despite the vast potential offered by Big Data, challenges such as data quality, security and privacy issues, and the need for adequate skills and resources are also identified. The study emphasizes the importance of cross-disciplinary collaboration in advancing this field and suggests that further exploration is needed regarding the challenges and opportunities in the application of Big Data in the financial sector to enhance existing reporting practices.