A Meta-Model for Real-Time Fraud Detection in ERP Systems
Anna Fuchs, Kevin Fuchs, Fabian Gwinner, Axel Winkelmann · Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2021
Fraud is a worldwide issue affecting almost every organization once in a time. Recent studies have shown that fraudulent behavior impacts up to 5 % of a companies annual revenue. Information systems (IS) have become an integral part of every modern organization. They contain the data foundation of the entire company and thereby supporting business processes and day-to-day transactions. Although an IS usually contains control mechanisms to prevent different kinds of fraud, these mechanisms look insufficient, considering the role of IS in many fraud cases. Since many cases from different companies have shown the need for an appropriate countermeasure, we want to develop an application that efficiently detects fraud and fraudulent behavior. Therefore, we conducted a structured literature review and a qualitative survey to apply the design science research (DSR) methodology and derive requirements for a fraud detection system (FDS). As a result, we present a meta-model for a FDS for enterprise resource planning (ERP) systems. We also provide application requirements, principles, and features that define areas for further research.