Detecting value-added tax evasion by business entities of Kazakhstan

Zhenisbek Assylbekov; Igor Melnykov; Rustam Bekishev; Assel Baltabayeva; Dariya Bissengaliyeva; Eldar Mamlin

doi:10.1007/978-3-319-39630-9_4

Detecting value-added tax evasion by business entities of Kazakhstan

Zhenisbek Assylbekov
, Igor Melnykov
, Rustam Bekishev
, Assel Baltabayeva
, Dariya Bissengaliyeva
, Eldar Mamlin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

25 Scopus citations

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.

Original language	English (US)
Title of host publication	Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016
Editors	Lakhmi C. Jain, Robert J. Howlett, Ireneusz Czarnowski, Alfonso Mateos Caballero, Lakhmi C. Jain, Lakhmi C. Jain
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	37-49
Number of pages	13
ISBN (Print)	9783319396293
DOIs	https://doi.org/10.1007/978-3-319-39630-9_4
State	Published - 2016
Externally published	Yes
Event	8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 - Puerto de la Cruz, Tenerife, Spain Duration: Jun 15 2016 → Jun 17 2016

Publication series

Name	Smart Innovation, Systems and Technologies
Volume	56
ISSN (Print)	2190-3018
ISSN (Electronic)	2190-3026

Conference

Conference	8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016
Country/Territory	Spain
City	Puerto de la Cruz, Tenerife
Period	6/15/16 → 6/17/16

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2016.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 17 Partnerships for the Goals

Keywords

Anomaly detection
Cluster analysis
Self-organizing maps
Tax evasion detection

Publisher link

10.1007/978-3-319-39630-9_4

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Cite this

Assylbekov, Z., Melnykov, I., Bekishev, R., Baltabayeva, A., Bissengaliyeva, D., & Mamlin, E. (2016). Detecting value-added tax evasion by business entities of Kazakhstan. In L. C. Jain, R. J. Howlett, I. Czarnowski, A. M. Caballero, L. C. Jain, & L. C. Jain (Eds.), Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 (pp. 37-49). (Smart Innovation, Systems and Technologies; Vol. 56). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-39630-9_4

Detecting value-added tax evasion by business entities of Kazakhstan. / Assylbekov, Zhenisbek; Melnykov, Igor; Bekishev, Rustam et al.
Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016. ed. / Lakhmi C. Jain; Robert J. Howlett; Ireneusz Czarnowski; Alfonso Mateos Caballero; Lakhmi C. Jain; Lakhmi C. Jain. Springer Science and Business Media Deutschland GmbH, 2016. p. 37-49 (Smart Innovation, Systems and Technologies; Vol. 56).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Assylbekov, Z, Melnykov, I, Bekishev, R, Baltabayeva, A, Bissengaliyeva, D & Mamlin, E 2016, Detecting value-added tax evasion by business entities of Kazakhstan. in LC Jain, RJ Howlett, I Czarnowski, AM Caballero, LC Jain & LC Jain (eds), Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016. Smart Innovation, Systems and Technologies, vol. 56, Springer Science and Business Media Deutschland GmbH, pp. 37-49, 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016, Puerto de la Cruz, Tenerife, Spain, 6/15/16. https://doi.org/10.1007/978-3-319-39630-9_4

Assylbekov Z, Melnykov I, Bekishev R, Baltabayeva A, Bissengaliyeva D, Mamlin E. Detecting value-added tax evasion by business entities of Kazakhstan. In Jain LC, Howlett RJ, Czarnowski I, Caballero AM, Jain LC, Jain LC, editors, Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016. Springer Science and Business Media Deutschland GmbH. 2016. p. 37-49. (Smart Innovation, Systems and Technologies). doi: 10.1007/978-3-319-39630-9_4

Assylbekov, Zhenisbek ; Melnykov, Igor ; Bekishev, Rustam et al. / Detecting value-added tax evasion by business entities of Kazakhstan. Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016. editor / Lakhmi C. Jain ; Robert J. Howlett ; Ireneusz Czarnowski ; Alfonso Mateos Caballero ; Lakhmi C. Jain ; Lakhmi C. Jain. Springer Science and Business Media Deutschland GmbH, 2016. pp. 37-49 (Smart Innovation, Systems and Technologies).

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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.",

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Detecting value-added tax evasion by business entities of Kazakhstan

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

Publisher link

Find It

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