The focus on the use of data and data analysis tools has increased significantly during the recent years, which in addition to an increase in the amount of available data, suggest that there is a possible potential waiting to be exploited by the audit business. The purpose of this thesis is to investigate how data analytics can be implemented in the audit process in practice and to what extent this will affect the efficiency of an audit. To answer this question, the legislation that auditors are subject to, is examined to identify in which way data analytics can be implemented in theory. An example company has been audited with the use of data analytics, to determine how this affects the efficiency of the audit process, compared to the actual audit without the use of data analytics. An interview with a key expert on the subject has been conducted, in addition to relevant external material to apply relevant perspectives to the thesis. Based on the examination of the regulation and standards, it can be concluded that the ISA, despite lacking suggestions on how to use data analytics in the audit process, are not to be seen as an obstacle towards its use. The standards do not support the use of data analytics, nor do they prohibit it. Furthermore, data analytics can be used broadly across the various stages of the audit process. However, auditor’s conclusions can never be based solely on data analytics. It must be conducted in addition to or supported by traditional auditing procedures. Moreover, it is deemed necessary that the use of data analytics is supported by the auditor’s own professional judgement. Due to the novelty factor of this methodology in the audit process, auditors are obliged to expand their skillset towards understanding data analytics and statistics, as well as being able to operate these technologies. According to the study, data analysis can be implemented in most of the audit process with a positive effect on the efficiency of the audit, where data can be used as a valid audit evidence. By having access to the financial data of a company, it is possible for the auditor, to automate and standardize many procedures, as well as providing the auditor with a deeper knowledge of the company which inevitably caused a more targeted, and therefore efficient and effective audit. It is concluded that data analytics is capable of replacing certain traditional audit procedures, as well as supplementing others. Auditors are ultimately likely to benefit from the overall use by affecting both the quality and the time consumption of the audit. This effect is caused by the combination of fewer manual procedures caused by automation, as well as the evidence obtained from the data analysis which can cause fewer overall samples.
|Educations||MSc in Auditing, (Graduate Programme) Final Thesis|
|Number of pages||100|
|Supervisors||Kim Klarskov Jeppesen|