The world of technological capability is changing at a riveting pace. Whether the audit profession chooses to acknowledge this, at some point the implementation of technologies such as block chain will have a deep impact on the basic need for assurance on financial transactions, on which the auditor has built his business model.
However, before we get to that point, the auditor is in a unique position to utilize some of these technologies and the massive availability of client data to increase audit quality. In this thesis we aim to explore some these options, while keeping a close connection to the theoretical guidelines that lies in the foundation of auditing.
For the purpose of this thesis we start out by defining audit quality as measured both the auditor but also by the audit client. We come to the conclusion that a wide array of qualities must be taken into consideration when assessing audit quality, but the utmost relevant can be summarized to; the auditor’s judgment and skepticism, the probative value of the evidence, the cost efficiency of the audit, the perception of the audit’s performed work, and qualitative insights
obtained from the audit.
We define our analysis on the evaluation of the data analytics techniques; Automation, Statisical Analysis, Benchmarking and Transaction analysis. By looking at the impact on the above factors, represented by the application of these techniques, we derive the conclusion that the use of data analytics will have a significant positive impact across the board.
|Educations||MSc in Auditing, (Graduate Programme) Final Thesis|
|Number of pages||119|