The paper investigates a mathematical and statistical methodology for designing risk profileindicators (RPIs) — the central element of customs risk management. Using two datasets — 16,035consignments with detected discrepancies and 616,925 declarations — seven base indicators are combinedinto 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.
| Mualliflar | Niyazov, Sherzod |
|---|---|
| Jurnal | Innovation science and technologiy |
| Nashr sanasi | 2026-05-01 |
| Jild | 2 |
| Son | 5 |
| DOI | 10.5281/zenodo.20390828 |
DOI: 10.5281/zenodo.20390828 · Maqolaning asl sahifasi
risk management, customs control, risk profile, conditional probability, Laplace smoothing, lift coefficient, naive Bayes classifier, association rules
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