Innovative Data Analytics, Data Sources, and Architecture for European Customs Risk Management: D8.8 Policy, Research and Standardization Recommendations

https://cordis.europa.eu/project/id/786748/results<br/>https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5f1716216&amp;appId=PPGMS<br/>

The use of machine learning to identify the correctness of HS Code for the customs import declarations

As an increasing volume of international trade activities around the world, the amount of cross-boarder import declarations grows rapidly, resulting in an unprecedented scale of potentially fraudulent transactions, in particular false commodity code (e.g., HS Code). The incorrect HS Code will cause duty risk and adversely impact the revenue...

Identifying the value of data analytics in the context of government supervision: Insights from the customs domain

eCommerce, Brexit, new safety and security concerns are only a few examples of the challenges that government organisations, in particular customs administrations, face today when controlling goods crossing borders. To deal with the enormous volumes of trade customs administrations rely more and more on information technology (IT) and risk...

Value of Big Data Analytics for Customs Supervision in e-Commerce

Big data and analytics have received a lot of attention in e-government research over the last decade and practitioners and researchers are looking into the transformative power of this technology to create for example competitive advantage, and increase transparency. Recent research points out that while parties are aware of the transformative...