There continues to be difficulties in applying dataanalytics in the current audit standards. The main challenges identified throughout this thesis are the following:
Classification of audit procedures: Data analytics is not easily divided into the classifications required by the standards (Risk assessment, test of controls, substantive procedures).
Documentation: Uncertainty remains regarding the documentation of actions performed by data analytics to comply with ISA 230 in its current state.
Relevance and reliability: The usage of data analytics requires the auditor increasingly to address risks of non-validated data especially from sources outside of the company.
Outliers: Uncertainty remains regarding work required to address outliers identified by data analytics.
Professional skepticism: The appliance of professional skepticism is essential throughout the audit data analytics may distance the auditor from the entity and restrict the usage of skepticism.
Nature of audit evidence: As data analytics is not easily classified as test of detail or analytical procedures the value of obtained audit evidence is difficult to value.
Affecting the decision making of the management: Issues arise from sharing information with the management and influencing the decision making. When the independent oversight bodies conduct a quality review of an audit, it is conducted with reference to the current standards. The quality review is carried out by The Danish Business Authority which, to some of the issues, have clear beliefs to how the challenges should be approached. The approach accepted by the Business Authority is yet to be shared with the industry and as such the uncertainty remains. As there is no guidance to be found relating to how auditors should fulfill requirements in the standards the above challenges acts as a barrier for further adoption of data analytics in financial statements audits. This thesis has explored the concept of dataanalytics. Challenges in applying data analytics in financial statement audits has been identified through an analysis of RFI issued by IAASB’s Data Analytics Working Group (DAWG). The thesis further includes multiple respondents, via interviews, from different backgrounds to get an all-round view of the audit industry’s current view on data analytics. The respondents further, provide proof that the challenges identified by DAWG also exist in practice. Concluding this examination, the independent oversight body of Denmark, the Danish Business Authority has been interviewed. This interview gives an understanding of the treatment of data analytics in audits from a quality review perspective. The technology applied throughout the different industries is in constant and rapid development. The technologies used in the audit business is no exemption to that fact and continues to evolve. Even with all the technological changes and the changes to the audit business, the audit standards which creates the foundation on which an audit is carried out has remained more or less the same for many years. This thesis sheds a light on the current issues cost by applying new technology to old standards.
|Educations||MSc in Auditing, (Graduate Programme) Final Thesis|
|Number of pages||106|