Artificial Intelligence-Driven Customs Risk Management: Enhancing Cross-Border Trade Resilience Under Tariff Fluctuations

Abstract

Customs authorities face mounting pressure to manage cross-border risks while tariff schedules fluctuate unpredictably. This study examines how artificial intelligence can strengthen customs risk management and enhance trade resilience under tariff volatility. A mixed-method design combines a conceptual framework with quantitative simulation using historical customs declaration records and tariff change events. The artificial intelligence pipeline includes data preprocessing, feature engineering, ensemble learning, and risk scoring. Three models are compared: logistic regression, random forest, and gradient boosting. Evaluation focuses on detection accuracy, precision, recall, area under the curve, clearance time, compliance cost, and risk interception rate. Results show that the gradient boosting model achieves the highest detection accuracy at 92.4%, with an area under the curve of 0.95. Under high tariff fluctuation, the artificial intelligence-assisted scenario reduces average clearance time by 24.0% and compliance costs by 19.0% compared with the baseline. The fully automated scenario achieves the strongest operational gains, reducing clearance time by 31.0% and compliance costs by 24.0% while raising the risk interception rate to 88.0%, but requires robust governance safeguards. Sensitivity analysis reveals that model performance remains stable when tariff volatility increases, although false positives rise modestly. The discussion highlights that artificial intelligence supports customs agencies through predictive targeting, resource allocation, and adaptive compliance monitoring. However, data quality, algorithmic transparency, and cross-border coordination remain critical constraints. The conclusion recommends phased implementation, human-in-the-loop oversight, and international data standards. These findings suggest that artificial intelligence-driven customs risk management can improve cross-border trade resilience under tariff fluctuations, but its benefits depend on institutional readiness and ethical safeguards. The study offers a practical roadmap for customs modernization and trade facilitation.