Data Science Chair

    Occupational Fraud Detection

    Occupational fraud, where employers abuse their occupation through the deliberate misuse of the organization’s assets, is estimated to cause losses of 5% of revenue for companies. Our research in this area focuses on detecting fraud within the large amount of data tracked by companies through Enterprise Resource Planning (ERP) systems.

    In previous work we provided publicly accessible ERP data including fraud cases, employed machine learning methods from anomaly detection to automatically detect fraud, and employed explainable AI to provide both well performing and interpretable detection systems.


    If you are interested in this topic, feel free to contact Julian!