In recent years, the digital transformation has taken the world by storm and the world of the auditors is no different. In regard to this matter, the necessity for auditors to understand, focus and remain experts has become a must when it comes to maintaining the role as the representative of the public. This thesis examines how a data analytics approach to auditing is used for medium-sized companies in Denmark in order to increase the quality and the efficiency of the audit process, and thereby creating more value for the clients. Furthermore, it examines the effect that data analytics has on selected areas within the audit process. Data analytics is already being used by the Big Four accounting firms and they are all determined to have it implemented in several other audit areas as well. Through multiple interviews with auditors from the Big Four, this thesis provides an insight on how data analytics can contribute to the auditor’s risk assessments, test of controls, test of details, substantive analytical procedures and extended review. Data analytics is a great tool for the auditors in obtaining a better understanding of the client’s business and environment. It gives the auditor a better overall picture of the individual accounting items, whereto the auditor is able to test the entire population in a relatively short period of time and obtain a more accurate risk assessment. Even though this is a great tool, the data analytics alone does not provide the audit enough evidence, which is why the professional judgement of an auditor is still relevant and still plays a key role when auditing. Nevertheless, this is considered to be a great tool the auditor can use in the risk assessment and aforementioned procedures. Additionally, it was discovered that the data analytics can contribute to the test of the controls and the test of details. Whereas the auditor selects samples based on a sample table or other tools that only provide a test of the details, data analytics makes it possible to test the entire population as well as making the selection of the samples more accurate and specified around transactions, where there is a risk of misstatement. This method clearly differs from the normal approach, which is typically based on one’s judgement or randomness. In regard to substantive analytic procedures, data analytics can provide the auditor with proposed hypotheses about the correlation between the different data variables, in which regression or visualization software is great at highlighting this. Lastly, it was brought to light that data analytics can also implicitly contribute to the auditor’s inquiry as an extension of an analytical action. The expectation is that the analysis will identify “abnormal” transactions within the Company to which the auditor can ask for more specific and determined data. Essentially, the use of data analytics is an exceptional option to improve the overall audit quality, the efficiency of the audit process and equip the Company with new insight that might optimize their business processes and create new value for them as a whole.
|Educations||MSc in Auditing, (Graduate Programme) Final Thesis|
|Number of pages||134|