Data Science and External Audit

Abstract

AbstractIncorporating BDA in audit engagement provides the audit profession an opportunity to use more advanced predictive and prescriptive-oriented analytics.Considering the complexity and dynamism of the external audit process, the necessity of using BDA might be influenced by different, contingent, external, and internal factors.Large accounting firms and corporations are using advanced data analytical tools to leverage all the data available to them. With the right tool and access to enterprise data, auditors are able to examine the entire population of the data.Big Data Analytics, Data Analytics, Artificial Intelligence (AI), Robotic Process Automation (RPA), and Big Data are a new cluster of technologies that could use to further improve both the efficiency and effectiveness of audits.Big Data Analytics are altering the way the audit process is done at both the transaction and general ledger levels. Auditors have new tools to extract and visualize data, allowing them to dig into larger, nontraditional data sets and perform more intricate analysis.This chapter begins with an attempt to explain Big Data Analytics as a new opportunity to enhance productivity, efficiency, and innovativeness of External audits. I present and explain how to use Big Data Analytics in several aspects of audit process. Then, I explain how the external auditors can use ADAs to perform a variety of procedures to gather audit evidence, to help with the extraction of data, and facilitate the use of audit data analytics. Then, I explain the frameworks of ADA and defined its dimensions. I present the 5-Step Process to Performing Audit Data Analytics (ADAs). I present in this chapter BAD and ADA techniques. The last section of this chapter includes how to use the ADA in Risk Assessment Procedures, Substantive Analytical Procedures, and Tests of Detail.KeywordsAuditBig data analyticsExternal auditBDA’s tools and techniques