Big Data Techniques in Auditing Research and Practice: Current Trends and Future Opportunities

Adrian Gepp, Martina K. Linnenluecke, Terry O'Neill, Tom Smith
2017 Social Science Research Network  
This paper analyzes the use of big data techniques in auditing, and finds that the practice is not as widespread as it is in other related fields. We first introduce contemporary big data techniques to promote understanding of their potential application. Next, we review existing research on big data in accounting and finance. In addition to auditing, our analysis shows that existing research extends across three other genealogies: financial distress modelling, financial fraud modelling, and
more » ... d modelling, and stock market prediction and quantitative modelling. Auditing is lagging behind the other research streams in the use of valuable big data techniques. A possible explanation is that auditors are reluctant to use techniques that are far ahead of those adopted by their clients, but we refute this argument. We call for more research and a greater alignment to practice. We also outline future opportunities for auditing in the context of real-time information and in collaborative platforms and peer-to-peer marketplaces. [Graphical Abstract provided in separate file] [Bullet-Point Highlights provided in separate file] Citation Note: A revised version has been accepted for publication in the Journal of Accounting Literature
doi:10.2139/ssrn.2930767 fatcat:tfo76egwmbgepd565wghu2oxmq