Data Analytics in Practice: Overview of the Use and Plans in the Danish Audit Industry

Emilie L. K. Thomsen & Jacob Thøgersen

Student thesis: Master thesis


Historically, data analytics is in no way a new phenomenon and can be dated back several decades. However, the introduction and implementation of audit data analytics into the audit have gained ground in the last 3-5 years, and it seems there is no doubt among today’s auditors and audit companies that the introduction of audit data analytics cannot be neglected. The development of audit data analytics and the way of auditing itself are undergoing a fast-paced development, and audit data analytics has since its introduction decades ago been accompanied by phenomena as artificial intelligence, big data, and data mining, Following this fast-paced development, researchers have previously been highly focused on predicting the outcomes of introducing audit data analytics into the audits and thus, limited focus has been put on how the auditors and auditing companies in practice are experiencing and applying data analytics with regard to the audit. Thus, the thesis seeks to contribute to filling this void of research. By using theories from what is assessed to be the thesis’ two main pillars – data analytics and audit – the thesis seeks to examine how audit data analytics is applied in practice and which challenges are experienced in relation hereto as well as how audit companies are planning to implement and apply such analytics prospectively, Specifically, the examination applies theory and literature on Audit Documentation and Audit Evidence to obtain an understanding of how audit data analytics is and can be applied throughout the audit . Furthermore, the examination applies theory on how new technology and tools are implemented successfully into an organization in order to better understand which obstacles the Danish audit industry experiences and which necessary actions need to be taken in order to expanding the use of audit data analytics. Data is mainly gathered through interviews with representatives from the Danish audit industry. Based on the obtained data, it has been possible to conclude that there are currently large differences among the companies in the Danish audit industry. These differences are made up of differences in the understanding of what data analytics consists of, how the concept/definition is applied in practice, in which tools are applied, how far the different companies are in implementing such tools as well as what the primary objective of using such tools is. It has been concluded that there is plenty of room for further development and that there is still unexploited potential when it comes to applying data analytics in the audit industry. Currently, the companies within the Danish audit industry experience five main obstacles for a further expansion of the use of audit data analytics for the companies within the Danish industry experience: The auditor’s competencies; the auditor’s mind-set; company structures; and the lack of regulation/guidance. Overall, it is concluded that the auditor’s competencies and company structures are the two main obstacles, which the Danish audit industry should take into consideration and focus on overcoming. As the companies within the Danish audit industry prospective focus consists of developing and enhancing audit data analytics tools as well as the auditors’ competencies, there seems to be a gap between the actual plans for the future, which the Danish audit industry has, and what seems to be the necessary plans within the industry

EducationsMSc in Auditing, (Graduate Programme) Final Thesis
Publication date2019
Number of pages107
SupervisorsKim Klarskov Jeppesen