Value-added tax fraud detection with scalable anomaly detection techniques

The tax fraud detection domain is characterized by very few labelled data (known fraud/legal cases) that are not representative for the population due to sample selection bias. We use unsupervised anomaly detection (AD) techniques, which are uncommon in tax fraud detection research, to deal with the...

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Veröffentlicht in:	Applied soft computing Jg. 86; S. 105895
Hauptverfasser:	Vanhoeyveld, Jellis, Martens, David, Peeters, Bruno
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.01.2020
Schlagworte:	Scalable algorithms Tax fraud detection Unsupervised anomaly detection Tax fraud detection Scalable algorithms Unsupervised anomaly detection
ISSN:	1568-4946, 1872-9681
Online-Zugang:	Volltext
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