Gated Mixture Variational Autoencoders for Value Added Tax audit case selection

In this work, we address the problem of targeted Value Added Tax (VAT) audit case selection by means of machine learning. This is a challenging problem that has remained rather elusive for EU-based Tax Departments, due to the inadequate quantity of tax audits that can be used for conventional superv...

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Veröffentlicht in:	Knowledge-based systems Jg. 188; S. 105048
Hauptverfasser:	Kleanthous, Christos, Chatzis, Sotirios
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 05.01.2020 Elsevier Science Ltd
Schlagworte:	Audit selection Audits Deep learning Finite mixture model Inference Machine learning Regularization Taxation Value added Value Added Tax Variational autoencoder VAT Cyprus Variational autoencoder Audit selection Value Added Tax Finite mixture model
ISSN:	0950-7051, 1872-7409
Online-Zugang:	Volltext
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