Role of Big Data Analytics in Enhancing Audit Decision-Making and Detecting Material Misstatements

Abstract

In recent years, the integration of Big Data Analytics (BDA) into the auditing process has emerged as a transformative force, enhancing decision-making capabilities and improving the detection of material misstatements. This qualitative study employs a literature review methodology to explore the role of BDA in the auditing field. By analyzing existing research, the study identifies key themes related to the application of BDA in audit practices, including data collection, analysis techniques, and the impact on auditor judgment. The findings indicate that BDA facilitates a more comprehensive assessment of financial data, enabling auditors to identify anomalies and trends that may indicate misstatements. Furthermore, the study highlights the importance of auditor training in utilizing BDA tools effectively, ensuring that they can interpret complex data sets accurately. The research concludes that while the adoption of BDA presents challenges, such as data privacy concerns and the need for technological infrastructure, its potential to enhance audit quality and efficiency is significant. By leveraging BDA, auditors can improve their decision-making processes, ultimately leading to more reliable financial reporting. This study contributes to the growing body of knowledge on the intersection of technology and auditing, providing insights for practitioners and researchers alike.