METHODOLOGICAL FOUNDATIONS FOR FORMING CUSTOMS RISK PROFILE INDICATORS BASED ON MATHEMATICAL AND STATISTICAL METHODS
DOI:
https://doi.org/10.5281/zenodo.20390828Keywords:
risk management, customs control, risk profile, conditional probability, Laplace smoothing, lift coefficient, naive Bayes classifier, association rulesAbstract
The paper investigates a mathematical and statistical methodology for designing risk profile
indicators (RPIs) — the central element of customs risk management. Using two datasets — 16,035
consignments with detected discrepancies and 616,925 declarations — seven base indicators are combined
into 120 combinations and 386,516 risk indicator sets. Conditional probabilities are computed with Bayes–
Laplace smoothing, and the lift coefficient ranks combinations by their fraud-detection power.
References
World Customs Organization. Customs Risk Management Compendium. – Brussels: WCO, 2012. – Vol. 1–2. URL:
https://www.wcoomd.org/en/Topics/Facilitation/Instrument%20and%20Tools/Tools/Risk%20Management%20
Compendium
World Customs Organization. SAFE Framework of Standards to Secure and Facilitate Global Trade. 2021 Edition. –
Brussels: WCO, 2021.
ISO 31000:2018. Risk management — Guidelines. – Geneva: International Organization for Standardization, 2018.
– 16 p.
Knight F. H. Risk, Uncertainty and Profit. – Boston: Houghton Mifflin Company, 1921. – 381 p.
Jeffreys H. Theory of Probability. – 3rd ed. – Oxford: Oxford University Press, 1961. – 459 p.
Agrawal R., Srikant R. Fast Algorithms for Mining Association Rules // Proc. of the 20th VLDB Conference. – Santiago
de Chile, 1994. – P. 487–499.
Manning C. D., Schütze H. Foundations of Statistical Natural Language Processing. – Cambridge, MA: MIT Press,
– 680 p.
Shapley L. S. A Value for n-Person Games // Contributions to the Theory of Games / Eds. H. W. Kuhn, A. W. Tucker. –
Princeton: Princeton University Press, 1953. – Vol. II. – P. 307–317.
Triepels R., Daniels H., Feelders A. Data-driven fraud detection in international shipping // Expert Systems with
Applications. – 2018. – Vol. 99. – P. 193–202. DOI: 10.1016/j.eswa.2018.01.007.
Geourjon A.-M., Laporte B. Risk management for targeting customs controls in developing countries: a risky venture
for revenue performance? // Public Administration and Development. – 2005. – Vol. 25, No. 2. – P. 105–113.
Vanhoeyveld J., Martens D., Peeters B. Customs fraud detection: assessing the value of behavioural and highcardinality
data under the imbalanced learning issue // Pattern Analysis and Applications. – 2020. – Vol. 23. – P.
–1477.
Chawla N. V., Bowyer K. W., Hall L. O., Kegelmeyer W. P. SMOTE: Synthetic Minority Over-sampling Technique //
Journal of Artificial Intelligence Research. – 2002. – Vol. 16. – P. 321–357.
Chen T., Guestrin C. XGBoost: A Scalable Tree Boosting System // Proc. of the 22nd ACM SIGKDD International
Conference on Knowledge Discovery and Data Mining (KDD’16). – San Francisco, CA, 2016. – P. 785–794.
Lundberg S. M., Lee S.-I. A Unified Approach to Interpreting Model Predictions // Advances in Neural Information
Processing Systems (NeurIPS 2017). – Long Beach, CA, 2017. – P. 4765–4774.
Customs code of the Republic of Uzbekistan. URL: https://lex.uz/ru/docs/5535133
Customs Committee under the Ministry of Economy and Finance of the Republic of Uzbekistan. Official documents on
the “Green Channel” mechanism and the electronic declaration system. – Tashkent: 2020–2024.
