Uncovering illicit trade practices: Leveraging trade data with a macro-meso-micro approach

Abstract

This paper explores the potential of legal trade data as a critical tool for analysing illicit trade. By analysing anomalies, trends, and patterns, it demonstrates techniques of uncovering illegal trade practices. The study advances a novel Macro-Meso-Micro Framework, analysing trade flows from broad trends to granular transaction details. Case studies on commodities like acetate tow, drug precursors, and anti-malaria drugs highlight red flags, including vague descriptions, abnormal routes, and opaque buyers. Case studies are offered that demonstrate how macro-meso-micro framework can uncover specific cases of illegal trade practices. The paper also demonstrates that cross-referencing trade data with other datasets enhances detection, offering actionable insights into combating illicit trade.