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 |
|---|---|
| Title of host publication | Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 37-49 |
| Number of pages | 13 |
| Volume | 56 |
| ISBN (Print) | 9783319396293 |
| DOIs | |
| Publication status | Published - 2016 |
| 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) | 21903018 |
| ISSN (Electronic) | 21903026 |
Other
| Other | 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016 |
|---|---|
| Country | Spain |
| City | Puerto de la Cruz, Tenerife |
| Period | 6/15/16 → 6/17/16 |
Fingerprint
Keywords
- Anomaly detection
- Cluster analysis
- Self-organizing maps
- Tax evasion detection
ASJC Scopus subject areas
- Computer Science(all)
- Decision Sciences(all)
Cite this
Detecting value-added tax evasion by business entities of Kazakhstan. / Assylbekov, Zhenisbek; Melnykov, Igor; Bekishev, Rustam; Baltabayeva, Assel; Bissengaliyeva, Dariya; Mamlin, Eldar.
Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016. Vol. 56 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
}
TY - GEN
T1 - Detecting value-added tax evasion by business entities of Kazakhstan
AU - Assylbekov, Zhenisbek
AU - Melnykov, Igor
AU - Bekishev, Rustam
AU - Baltabayeva, Assel
AU - Bissengaliyeva, Dariya
AU - Mamlin, Eldar
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Anomaly detection
KW - Cluster analysis
KW - Self-organizing maps
KW - Tax evasion detection
UR - http://www.scopus.com/inward/record.url?scp=84977098268&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84977098268&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-39630-9_4
DO - 10.1007/978-3-319-39630-9_4
M3 - Conference contribution
AN - SCOPUS:84977098268
SN - 9783319396293
VL - 56
T3 - Smart Innovation, Systems and Technologies
SP - 37
EP - 49
BT - Intelligent Decision Technologies 2016 - Proceedings of the 8th KES International Conference on Intelligent Decision Technologies, KES-IDT 2016
PB - Springer Science and Business Media Deutschland GmbH
ER -