Eight Issues on Audit Data Analytics We Would Like Researched

TLDR

Data analytics is highlighted as an effective tool in audit engagements, yet our understanding and use of it remain limited. The paper aims to draw academic researchers’ attention to the data‑analytics issues identified by an experienced practitioner. The issues span standards, frameworks, application across audit phases, use of external data, sample versus population, and reliance on internal auditors. Addressing these issues can help researchers provide solutions and enrich the academic literature.

Abstract

ABSTRACT Data analytics has been emphasized as an effective tool in audit engagements. However, both our understanding and the use of data analytics in audit engagements are limited. The objective of this paper is to draw academic researchers' attentions to the issues of data analytics identified by an experienced practitioner in the field. These issues range from standards and the framework of data analytics to the use of data analytics in different phases of audit engagements and the corresponding consequences. The use of external data, sample versus population, and reliance on the work of internal auditors are also discussed. By addressing these issues, academic researchers can not only provide solutions to the field but also contribute to the knowledge body of academic literature.