Décloisonner l’analyse des données pour appuyer la modernisation des douanes : une illustration à partir du Gabon

Over the last few years, customs authorities in many developing countries have introduced modern risk management techniques relying on data mining and statistical scoring techniques. By demonstrating that risk analysis in customs may be a valuable tool to facilitate legal trade and combat fraud more effectively, these techniques have helped improving the performance of customs authorities. However, these risk management techniques may prove to be inefficient in a context of moral hazard and low-performance customs administration. One way to address this weakness is to rely on information gained from discrepancies in bilateral trade statistics. The analysis of discrepancies in bilateral trade statistics (or mirror analysis) is increasingly used to identify high-risk import operations and to estimate revenue losses. By comparing data on fraud recorded by the Gabon customs administration with discrepancies in Gabon's bilateral trade data, this paper highlights the benefits for a customs administration of a joint analysis of fraud records and mirror trade statistics data, the latter being indicative of the fraud remaining to be detected. Such an analysis helps customs to target ex post audits on risky import declarations unadjusted by the frontline customs officer. Finally, we point that analyzing jointly data on fraud records and mirror trade statistics data may be useful to (i) identify imported products for which the fraud remaining to be detected is large and (ii) monitor the performance of customs inspections.