A Case Study on the Application of Process Mining in Combination with Journal Entry Tests for Financial Auditing

Sebastian Stephan, Johannes Lahann, Peter Fettke

In: Data Analytics, Control, and Risk Management. Hawaii International Conference on System Sciences (HICSS-2021) January 4-8 Hawaii/Virtual HI United States Seiten 5718-5728 HICSS 1/2021.


The increasing complexity of data and processes within companies makes it increasingly difficult for auditors to ensure that annual audits are free of material misstatement. To cope with this complexity, a variety of analytical procedures have been developed in the last years. However, most of the existing procedures focus on conspicuous statements in the general ledger, and thus not consider behavioral aspects. In this paper, we show how journal entry tests can be effectively combined with process mining to capture a more comprehensive view within a company's audit. Therefore, the paper gives a comprehensive description of the purchase-to-pay-process and its realization in current SAP software as well as the required mechanism to extract event logs from raw SAP database tables. The conducted analysis is based on a dataset provided by a German medium-sized audit firm. The results suggest that we can discover anomalies that are not traceable through traditional analysis.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence