Risk management systems: using data mining in developing countries' customs administration

Limiting intrusive customs inspections is recommended under the revised Kyoto Convention, and is also a proposal discussed as part of World Trade Organization (WTO) trade facilitation negotiations. To limit such inspection, the more modern administrations intervene at all stages of the customs chain using electronic data exchange and risk analysis and focusing their resources on a posteriori controls. Customs administrations of developing countries are slow to move in that direction. Risk analysis would therefore seem to be a priority for modernising the customs systems in developing countries. The most effective risk management system uses statistical scoring techniques. Several simple statistical techniques are tested in this article. They all show a good capability to predict and detect declarations that contain infractions. They can easily be implemented in developing countries' customs administrations and replace the rather inefficient methods of selectivity that result in high rates of control and very low rates of recorded infractions.