Lecture Prof. Dr. Peter Fettke
Utilizing Machine Learning Techniques to reveal VAT Compliance Violations in Accounting Data
The lecture video is available to members of HHU via the media library.
Abstract
In recent years, compliance management has gained more and more interest from a practice and research point of view. The financial service industry, in general, is strongly regulated and has to follow specific laws, standards and guidelines. However, research has shown that little attention is being paid to Value Added Tax (VAT) issues, although there is a high cost and risk exposure, especially in large international companies which use large IT-Infrastructures for tax handling. The lecture examines a commonly applied approach for the verification of VAT regulations within Enterprise Resource Planning systems (ERP) and points to weaknesses as well as error susceptibilities. Machine learning techniques can be utilized to minimize risks and increase VAT compliance. Thus, a supervised learning classifier is used to predict tax subjects and corresponding tax rates based on related voucher information of journal reports. By comparing the results of the model with the existing rule-based system of an ERP system, potential anomalies and compliance issues are revealed. The approach was evaluated on a given real-world data set of a leading chemical industry company that was exported from its ERP system. The results were validated by VAT experts of the company.
CV
Dr. Peter Fettke is a Professor of Business Informatics at Saarland University and Principal Researcher, Research Fellow and Research Group Leader at the German Research Center for Artificial Intelligence (DFKI) in Saarbrücken. In his research, Peter, together with his research group of about 30 people, is particularly concerned with the intersection between the topics of process management and artificial intelligence (AI), e.g. possible applications of AI technologies such as deep learning and process mining in operational processes. Peter is the author of more than 150 peer-reviewed publications. His work is among the most cited articles in leading international journals on business informatics and he is one of the top 10 most cited scientists at DFKI. He is also a sought-after reviewer for renowned conferences, journals, and research organisations. Since 2017 he has headed the Competence Center "Tax Technology" which he founded at DFKI.