Examining the Need of Big Data Analytics in Auditing: A Bibliometric Approach

Abstract

Big data has become a growing trend in business operations. It is being employed in a variety of industries from manufacturing to accounting and supply chain management. Businesses that can take advantage of big data may be able to make better judgments, save money, and keep up with changing client needs.In the accounting scope, especially in auditing, big data allows auditors to increase their project’s samples and make comparisons across larger sets of data sets through its real-time data analysis characteristics. Big data assists auditors in detecting fraud and updating the reporting process to enable them identifying the immediate business risks and conducting appropriate audits according to the risks. Big data uses automation and artificial intelligence to analyse larger volumes and in a faster rate of data, increase auditor’s understanding on non-compliance history, current policy changes, and potential risk and fraud.Despite the potential benefits of big data analytics for the auditing profession, the auditing business has lagged behind in terms of its adoption or its utilisation (Aboud and Robinson, 2020). Internal and external auditors have not fully tapped into real-time data insights to monitor compliance and guarantee that businesses are reaching their maximum potential, despite the fact that big data offers a wide range of auditing applications. For example, using data from prior events, predictive and prescriptive analytics can be used to assess the possibility of future outcomes. In addition, auditors and other stakeholders will be more confident in assessing the efficiency of specific firm operations. The objectives of this paper are to: (1) highlight the current trend of big data analytics adoption in the auditing field and (2) discuss the need of big data analytics in auditing. Keywords: Accounting Information Systems, Big Data, Big Data Analytics, Audit, Bibliometric.