The purpose of this thesis is to examine how audit is performed in the SME-segment and to what extent data analytics are used. Furthermore, the thesis will examine the challenges when implementing data analytics and the effects of data analytics. The study is based on interviews with regular auditors from a variety of firms to examine the knowledge, opinions and assumptions of the average auditor.
Audits performed in the SME segment is still based on the traditional methodology because the advantages outweigh the advantages of data analytics at this point according to the auditors. The traditional methodology is efficient, the quality of the audit evidence is well known and optimized to the current employee structure. Data analytics is therefore not used systematically and in most of the audit firms of the respondents the data analytics is in a test phase or implemented on larger clients. Most of the firms invest in data analytics and some see it as a necessity to survive and be competitive on the market.
The auditors have a general knowledge of data analytics. There are some differences regarding the possibilities and opportunities with data analytics which indicates a need for education in the use and understanding of data analytics. The need for education and guidance is one of the challenges the auditors themselves mention in connection to the implementation of data analytics. Furthermore, according to the auditors, the challenges are as follows: the software for data analytics is primarily designed for larger clients, not very user friendly and require a high level of computer skills. Clients in the SME-segment do not have the resources or skills to provide the auditor with relevant data in a usable format and the auditors feel a pressure to meet demands on quality, efficiency and earnings which limits the implementation of data analytics.
Because most of the auditors don’t have experience with data analytics the effect of data analytics is based on their opinions and assumptions. All of the auditors believe the quality of the audit evidence will increase with data analytics. An analysis on the transactions will provide the auditor with further insight about the client, their processes and thereby enabling a better risk-based selection on deviations. When it comes to the effect of data analytics on insights, value creation and efficiency the auditors are split. Some of the auditors believe that data analytics can heighten the efficiency of an audit if the tools have a high level of automation and standardization while others believe the time consumption is allocated from one task to another. According to some of the auditors Data analytics focusing on insights and value creation is a separate analysis and therefore will not be part of the audit process.
|Educations||MSc in Auditing, (Graduate Programme) Final Thesis|
|Number of pages||200|
|Supervisors||Kim Klarskov Jeppesen|