@inproceedings{41ac8731b7f34cd98d691451c53ec6ce,
title = "Detecting value-added tax evasion by business entities of Kazakhstan",
abstract = "This paper presents a statistics-based method for detecting value-added tax evasion by Kazakhstani legal entities. Starting from features selection we perform an initial exploratory data analysis using Kohonen self-organizing maps; this allows us to make basic assumptions on the nature of tax compliant companies. Then we select a statistical model and propose an algorithm to estimate its parameters in unsupervisedmanner. Statistical approach appears to benefit the task of detecting tax evasion: our model outperforms the scoring model used by the State Revenue Committee of the Republic of Kazakhstan demonstrating significantly closer association between scores and audit results.",
keywords = "Anomaly detection, Cluster analysis, Self-organizing maps, Tax evasion detection",
author = "Zhenisbek Assylbekov and Igor Melnykov and Rustam Bekishev and Assel Baltabayeva and Dariya Bissengaliyeva and Eldar Mamlin",
year = "2016",
doi = "10.1007/978-3-319-39630-9_4",
language = "English (US)",
isbn = "9783319396293",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "37--49",
editor = "Jain, {Lakhmi C.} and Howlett, {Robert J.} and Ireneusz Czarnowski and Caballero, {Alfonso Mateos} and Jain, {Lakhmi C.} and Jain, {Lakhmi C.}",
booktitle = "Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016",
address = "Germany",
note = "8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 ; Conference date: 15-06-2016 Through 17-06-2016",
}
