The Role of Big Data in Financial Reporting Quality: A Bibliometric Analysis

This research focuses on the possibilities of Big Data Analytics (BDA) to increase greatly financial reporting quality (FRQ) and develop the knowledge base and conceptual framework inside this field of activity. The researcher investigated publications, including authors, journals, keywords, co-citations, thematic development, and topic trends, using a bibliometric method and the Biblioshiny tool. According to the analytical results, five primary clusters of profit management detection, financial statement manipulation theory, corporate governance, machine learning, and data mining techniques define the use of Big Data Analytics in the Financial Reporting Quality study. The key findings reveal that data mining and machine learning are the most often utilized and successful approaches for identifying deceptive behavior in financial reporting. Moreover, narrative report analysis helps BDA to enhance detecting skills. Artificial intelligence, deep learning, and machine learning are rising technologies projected to be the key subjects of future financial reporting quality studies.