Beschreibung:
This paper aims to explore the impact of Big Data Analytic (BDA) tools on financial audit procedures by modelling and comparing the applications of traditional and BDA tools in financial audit procedures. By using the lens of Dffusion of Innovation Theory and relevant literature review, the paper explains interactions among the BDA tools, their applicability in financial audit procedures. The multiple cases studies from agriculture, retail, and manufacturing have been carried out. The comparison of traditional and BDA tools is evaluated on 5 criterion of effectiveness.Results showed that the explored BDA tools enable to improve productivity and completeness of the financial audit procedures. Comparing to traditional tools, 60% of the BDA tools provide more clarity in the audit results and can be smoothly tracked by repeating the testing process. However, only 20% of BDA tools allow for a comparison of current and past audit data in the applied procedures.This paper contributes to the financial audit literature by explaining how innovative BDA tools might facilitate audit professional judgement when facing uncertainties due to the large amounts of audit client’s structured and unstructured data. More specifically, the study shows, which audit procedures can be performed more effectively by BDA tools: achieving higher productivity, obtaining more detailed results, replicating procedures, and using the available data for subsequent years of audit testing