# Customs Fraud Detection in the Presence of Concept Drift

arXiv: https://arxiv.org/abs/2109.14155 · HTML: https://mlsanity.com/paper/2109.14155/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 27 references that are in the map.
- First posted on arXiv 29 Sep 2021.

## Builds on (most cited first, 6 of 6)

- [XGBoost: A Scalable Tree Boosting System](https://mlsanity.com/paper/1603.02754/) (2016)
- [Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds](https://mlsanity.com/paper/1906.03671/) (2019)
- [Introduction to Multi-Armed Bandits](https://mlsanity.com/paper/1904.07272/) (2019)
- [Learning under Concept Drift: A Review](https://mlsanity.com/paper/2004.05785/) (2020)
- [Ready Policy One: World Building Through Active Learning](https://mlsanity.com/paper/2002.02693/) (2020)
- [Concept Drift Detection for Streaming Data](https://mlsanity.com/paper/1504.01044/) (2015)

## Built on by (most cited first, 4 of 4)

- [Self-Healing Machine Learning: A Framework for Autonomous Adaptation in Real-World Environments](https://mlsanity.com/paper/2411.00186/) (2024)
- [Knowledge Sharing via Domain Adaptation in Customs Fraud Detection](https://mlsanity.com/paper/2201.06759/) (2022)
- [Explainable Product Classification for Customs](https://mlsanity.com/paper/2311.10922/) (2023)
- [Customs Import Declaration Datasets](https://mlsanity.com/paper/2208.02484/) (2022)

## Abstract (arXiv)

Capturing the changing trade pattern is critical in customs fraud detection. As new goods are imported and novel frauds arise, a drift-aware fraud detection system is needed to detect both known frauds and unknown frauds within a limited budget. The current paper proposes ADAPT, an adaptive selection method that controls the balance between exploitation and exploration strategies used for customs fraud detection. ADAPT makes use of the model performance trends and the amount of concept drift to determine the best exploration ratio at every time. Experiments on data from four countries over several years show that each country requires a different amount of exploration for maintaining its fraud detection system. We find the system with ADAPT can gradually adapt to the dataset and find the appropriate amount of exploration ratio with high performance.