Customs Valuation Assessment Using Cluster-based Approach

Abstract Customs duty obligations are primary revenue sources for nations. Any under or over value can result in economic instability. The role of customs is safeguarding society and local businesses from criminally guided value manipulations. In this paper, a cluster-based approach to detect the customs commodity value manipulation is proposed. This approach represents the shipment related information into 3-dimensional space to determine any wrongdoing through two stages comprising distance- and density-based techniques. This representation simplifies the process by identifying relationships among the various shipment features. These two stages work together in order to analyse the shipments information and determine any abnormal behaviour for these shipments. The results of the proposed approach achieved an accuracy of 86%. This technique will provide much needed capabilities to protect the revenue and securing the trade supply chain from illegitimate activities.