Wolf GardianDie digitale Betriebsprüfung in der Gastronomie

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The gastronomy sector, characterized by cash intensity and flexible business processes, has long been considered particularly susceptible to VAT fraud. Manipulations of revenue data for the purpose of tax evasion cause billions of euros in losses to society annually. But how can such interventions be detected efficiently and reliably? In the digital auditing processes conducted by tax authorities, mathematical and statistical methods are increasingly being employed. Among these is Benford’s Law, a mathematical principle describing the distribution of digits in datasets. Based on this, tax authorities derive certain expectations regarding unmanipulated revenue data.

This study examines the suitability of this principle as a foundation for digital auditing. It investigates whether unmanipulated revenue data in the gastronomy sector genuinely adhere to the Benford distribution and whether manipulations create significant deviations that can be identified. These research questions are addressed through a combination of theoretical, practical, and experimental approaches. Using real and simulated revenue data, the hypothesis that unmanipulated data conform to specific distribution patterns is tested. Additionally, innovative experiments explore how individuals manipulate data and whether such interventions are detectable.

The findings provide practical insights into auditing methods, highlighting both the potential and the limitations of statistical approaches. This work offers valuable perspectives for researchers, tax authorities, and practitioners. It establishes a foundation for fairer tax audits and provides impetus for the further development of digital control mechanisms. Discover how mathematics and psychology collaborate to combat tax fraud.