Big Data Analytics and Auditing: A Review and Synthesis of Literature

The use of data analytics in auditing is increasingly growing. The application of common data analytics to audit engagements appears to be lagging behind other areas of practice, even though data analytics is thought to represent the future of audit, and there are still few publications that have examined this influence. This article reviews data analytics in audits and its potential for future audit engagements to describe the evolution of this research trend and picture its future growth directions. Future audit research potential and difficulties are also discussed. Data analytics application in auditing has enormous potential for refining audit quality, decreasing errors, increasing process transparency, and enhancing stakeholders’ confidence. We conducted a systematic literature review using the PRISMA approach. A total of 100 articles published in English from January 2011 to November 2021 were identified through a systematic search of reputed databases, including Web of Science and Scopus and many others. Our analysis reveals that data analytics is a promising domain for the auditing practice as it improves audit efficiency and promotes audit work digital transformation. While reviewing the most pertinent literature in the context of data analytics in auditing, this study offers insights on potential new directions and waning views on big data analytics in auditing.