When auditing the adequacy of the financial report, a detailed examination of the accounting entries is required. Depending on the size and the industry of the audited companies, there may be up to several million lines of journal entries. Processing these files with manual tools is no longer possible, so there is a need for an IT-supported application.
In case of files with million items, Excel does not provide a secure solution, used to process smaller files, so there is a need for an application which can handle large files, which is capable to automate functions, and which application is suitable for accounting by filtering the data for financial audit team's fraud detection tests.
I have created an application to automate the analysis of journal entries and visualize results of the queries. Automation greatly accelerates the audit fraud detection process and easier to use a visualization results than using a spreadsheet. By this new application we can see all of our results in a summary in a visualization tool. In my thesis, I consider the pitfalls of receiving data and those points that can pose difficulties to an auditor.
As a result of my thesis, I have created an application that will speed up the process of filtering the journal entries for the IT team and provide the results for the financial audit team in a visualized format that is easy to interpret, visualize, and which facilitates further analysis. In the application, I developed 15 scripts and I tested these for the unusual accounting transactions that I have experienced so far to detect fraud. The processes related to the application were visualized in 5 flowcharts.
The application can be developed further based on the need of the audit team, because the application is modular. The process can be further automated with a server that automatically loads the data into the visualization software and accelerates the process.