Customs valuation assessment using cluster-based approach

Customs duties are vital for national revenue, and deviations in declared values can lead to economic instability. This paper introduces a novel cluster-based approach for detecting customs commodity value manipulation. By representing shipment data in a 3-dimensional space, the method employs distance- and density-based techniques to identify abnormal behaviour. Achieving an 86% accuracy, this technique enhances capabilities to safeguard revenue and secure the trade supply chain from illegitimate activities, offering a valuable contribution to customs enforcement.