Applying Mass Data Analysis for Continuous Auditing to evaluate its Return on Investment

Abstract

Auditing in most companies often involves manual procedures, although data for automatic audit checks would be available in ERP systems. This Master Thesis is written in collaboration with the Group Internal Audit (IA) department of ABB which is quite advanced with regard to automation in its auditing automation approach and continuously expands its automated auditing service offerings for its stakeholders. Automation of auditing steps incurs very few additional costs if a running automatic data analysis (DA) is performed more frequently. For all companies not having implemented a DA for CA approach for at least some critical key controls the Master Thesis answers whether DA for CA for several continuously and automatically tested controls results in a higher Return on Investment (ROI) than testing the same controls with alternative audit procedures. This example is a first approach to compare two audit approaches. Companies not having yet implemented DA for CA should have an idea on whether they could benefit from implementing DA for CA for at least some of their controls. Therefore several DA control tests are analyzed in detail. Some control tests are directly implemented by the author of this Master Thesis....