Dataanalyse og besvigelser: Anvendelse af it-værktøjer til identifikation af besvigelser i den finansielle revision

Benjamin Holse Andersen

Studenteropgave: Kandidatafhandlinger


This thesis combines to problems discusses in regards to the financial audit:
The first problem is that almost every company in the world relies extensively on computer technology, now more than ever. With this increase in computer usage within the companies, it should be evident, that the financial auditor in the search for material misstatements should use computers to the same extent as the companies, but is highly regarded not to be the case.
The second problem is that the financial auditors are burdened with the publics expectations, that they are set in the world to find fraud in the financial statements, but the auditors themselves proclaim, that their job is to find material misstatements, which is not the same; This is the so-called “expectation gap”. It is believed that around the world, companies loses 5% of their yearly revenues, which is believed to be excess $ 3.7 trillion globally; this makes occupational fraud a huge social problem.
This thesis combines these to problems and seeks to find out how Computer Assisted Audit Tools (CAAT) are utilized in the financial audit, specific in the search for fraudulent behavior from employees in the organizations. The focus is on occupational fraud, which is the fraudulent behavior conducted within the organizations.
The conclusion to these problem is, that even though there is a fairly large utilization of Computer Assisted Audit Tools in the financial audit, the focus towards fraudulent behavior is somewhat diminished by the way the traditional audit is thought to be executed, due to interpretation of the audit standards.
The thesis finds that there is need to further testing in this area. Prior research is primarily based on questionnaires and interviews; with test of these techniques, the benefit of Computer Assisted Audit Tools presumably would be more evident. Furthermore, there is a need to research the way Machine Learning could potentially revolutionize the financial audit.

UddannelserCand.merc.aud Regnskab og Revision, (Kandidatuddannelse) Afsluttende afhandling
Antal sider94