Towards a data-driven approach for fraud detection in the social insurance field: A case study in Upper Austria

J. Himmelbauer, J. Martínez Gil, M. Ksen, K. Linner, S. Plakolm. Towards a data-driven approach for fraud detection in the social insurance field: A case study in Upper Austria. volume 11709, pages 70-84, DOI 10.1007/978-3-030-27523-5_6,, 8, 2019.

Autoren
  • Johannes Himmelbauer
  • Jorge Martínez Gil
  • Michael Ksen
  • Katharina Linner
  • Sieglinde Plakolm
Editoren
  • A. Kö
  • E. Francesconi
  • G. Anderst-Kotsis
  • A Min Tjoa
  • I. Khalil
BuchElectronic Government and the Information Systems Perspective - Proc. EGOVIS 2019
TypIn Konferenzband
VerlagSpringer
SerieLecture Notes in Computer Science
Band11709
DOI10.1007/978-3-030-27523-5_6,
ISBN978-3-030-27522-8
Monat8
Jahr2019
Seiten70-84
Abstract

The Social Insurance industry can be considered as a basic pillar of the welfare state in many countries around the world. However, there is not much public research work on how to prevent social fraud. And the few published works are oriented towards detecting fraud on the side of the employees or providers. In this work, our aim is to describe our experience when designing and implementing a data-driven approach for fraud detection but in relation to employers not meeting their obligations. In fact, we present here a case study in Upper Austria but from which interesting lessons can be drawn to be applied in a wide range of diffrent situations.