The Use of Detailed Statistical Data in Customs Reform : The Case of Madagascar
To carry out their various missions (collecting revenue, facilitating trade, and ensuring security), many customs administrations have established a risk management unit. In developing countries, however, because of the lack of dedicated human and...
| Main Authors: | , , |
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| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2016
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/2016/04/26185078/use-detailed-statistical-data-customs-reform-case-madagascar http://hdl.handle.net/10986/24167 |
| Summary: | To carry out their various missions
(collecting revenue, facilitating trade, and ensuring
security), many customs administrations have established a
risk management unit. In developing countries, however,
because of the lack of dedicated human and material
resources, intelligence and risk analysis remain
insufficiently developed. In view of the lack of resources,
this paper proposes a simple methodology aiming at detecting
risky import operations. The mirror analysis first helps to
identify and target products or sectors with the greatest
risk. Based on the examination of customs declarations
patterns (data mining), it is possible to identify and
target higher risk economic operators (importers and customs
brokers). When implemented in Madagascar, this method has
helped to reveal probable fraud cases in the present context
of customs reform. Estimates suggest that, in 2014, customs
fraud reduced non-oil customs revenues (duties and import
value-added tax) by at least 30 percent. |
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