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Contrôler moins pour contrôler mieux : l’utilisation du data mining pour la gestion du risque en douane

Author

Listed:
  • Ousmane COUNDOUL

    (FERDI)

  • Massene GADIAGA

    (FERDI)

  • Anne-Marie GEOURJON

    (Ferdi)

  • Bertrand LAPORTE

    (Université Clermont Auvergne – CERDI)

Abstract

Pour limiter les contrôles intrusifs, les administrations douanières les plus modernes s’appuient sur l’analyse du risque, seul moyen efficace, compte tenu de l’accroissement du volume des opérations commerciales, pour faciliter les échanges et sécuriser leurs opérations. Les douanes des pays en développement (PED) ont jusque-là tardé à s’engager dans cette voie. Cet article montre, à partir de l’expérience du Sénégal, que le data mining et les techniques de scoring peuvent être utilisées de manière efficace dans les douanes des PED pour évaluer le risque et orienter les déclarations dans les différents circuits de contrôle. Il met également en évidence que le développement à l’interne de tels systèmes dans les douanes de ces pays renforce de manière significative le processus de modernisation.

Suggested Citation

  • Ousmane COUNDOUL & Massene GADIAGA & Anne-Marie GEOURJON & Bertrand LAPORTE, 2012. "Contrôler moins pour contrôler mieux : l’utilisation du data mining pour la gestion du risque en douane," Working Papers P46, FERDI.
    • Handle: RePEc:fdi:wpaper:570
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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