This research objective focuses on data mining, which is quickly becoming a popular artificial intelligence technique used by tax administrations for better fraud detection. However, many challenges still exist. One of the main challenges is explaining the predicition made by complex algorithms. Within this research objective, we explore the opportunities of tackling this challenge of explainable AI by making use of counterfactual explanations. 

Research projects

Fraud detection with behavioural data

  • researcher Dieter Brughmans 
  • supervisor prof. David Martens 
  • research is funded by the University of Antwerp
  • read more on this topic on the website of Antwerp Tax Academy​​

Explainable Artificial Intelligence  







Previous Research

The research output of DigiTax builds on previous research of its supervisors. Hereunder a selection of relevant publications related to the research opbjective described in this section.



  •  Van Hoeyveld, Jellis, Martens, David, Peeters, Bruno, "Datamining voor fraudedetectie",  in Cahiers politiestudies / Centrum voor Politiestudies,  Gent, 2016, 39:2(2016), p. 167-211
  •  Martens, David, De Cnudde, Sofie, Moeyersoms, Julie, Praet, Stiene, Stankova, Marija, Tobback, Ellen, Vanhoeyveld, Jellis, "Big data in banking", in Bank- en financiewezen / Belgisch Financieel Forum. Studiecentrum voor het Financiewezen; Forum financier belge. Centre d'études financières, Brussel, 2016, p. 117-122
  •  Vanhoeyveld, Jellis, Martens, David, Peeters, Bruno, "Datamining voor fraudedetectie", in Criminele organisaties en organisatiecriminaliteit, Serie Cahiers politiestudies / Centrum voor Politiestudies, Antwerpen, Maklu, 2016, p. 167-211