The tool is helping the Nigeria Customs to begin analysing real-time data on imports coming through Tin Can Island Port, near Lagos, using the Machine Learning (ML) algorithms to detect fraud developed by the WCO as part of its BACUDA Project, according a WCO report on Thursday.
BACUDA is a collaborative research project between Customs and data scientists. Its objective is to develop data analytics methodologies as a response to WCO Members’ requests for assistance in this domain, which is also one of the priorities defined in the organisation’s current strategic plan..
“To develop the algorithms, BACUDA analysts used Customs data at the most disaggregated level, i.e. the transaction level. Such data was collected from Customs administrations wishing to support the project, including Nigeria Customs which provided a subset of five-year import data to enable the BACUDA Team experts to develop and test the algorithms for detecting fraud,” the organisation said.
It stated that the results obtained from analysing the data on imports coming through Tin Can Island Port using the BACUDA algorithms would be compared with those obtained from analysing the data on imports coming through Onne Port using traditional analytical methods.
The WCO Deputy Secretary General, Ricardo Treviño Chapa, attended the ceremony held to launch the pilot project on March 2, 2020.
Addressing the audience, he expressed his confidence that the methods developed by the WCO would enable the NCS to detect under-valuation with greater accuracy and, by so doing, to facilitate operations by compliant traders, create a fair business environment and increase revenue collection.
Chapa also thanked the NCS for the support provided to the BACUDA Project and congratulated the Administration for showing its strong commitment towards the adoption of modern targeting techniques.
Chapa also met with the NCS management team to discuss several projects, as well as with Hameed Ali, comptroller-general of Nigeria Customs Service, who reiterated his willingness to continue actively supporting the work done by the Organisation.