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PROFILE SIGNED

Data Analytics, Data Sources, and Architecture for Upgraded European Customs Risk Management

Total Cost €

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EC-Contrib. €

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Partnership

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Project "PROFILE" data sheet

The following table provides information about the project.

Coordinator
Cross-border Research Association 

Organization address
address: ROUTE DE LA CHOCOLATIERE 26
city: ECHANDENS
postcode: 1026
website: www.cross-border.org

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Total cost 4˙999˙991 €
 EC max contribution 4˙999˙991 € (100%)
 Programme 1. H2020-EU.3.7.3. (Strengthen security through border management)
 Code Call H2020-SEC-2016-2017-2
 Funding Scheme RIA
 Starting year 2018
 Duration (year-month-day) from 2018-08-01   to  2021-07-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    Cross-border Research Association CH (ECHANDENS) coordinator 944˙002.00
2    TECHNISCHE UNIVERSITEIT DELFT NL (DELFT) participant 559˙382.00
3    IBM IRELAND LIMITED IE (Ballsbridge) participant 556˙875.00
4    NEDERLANDSE ORGANISATIE VOOR TOEGEPAST NATUURWETENSCHAPPELIJK ONDERZOEK TNO NL (DEN HAAG) participant 482˙875.00
5    INLECOM SYSTEMS LTD UK (LONDON) participant 371˙249.00
6    JRC -JOINT RESEARCH CENTRE- EUROPEAN COMMISSION BE (BRUSSELS) participant 369˙700.00
7    MINISTERIE VAN FINANCIEN NL (S-GRAVENHAGE) participant 303˙331.00
8    TOTALFORSVARETS FORSKNINGSINSTITUT SE (STOCKHOLM) participant 298˙692.00
9    SERVICE PUBLIC FEDERAL FINANCES BE (BRUXELLES) participant 246˙812.00
10    Swedish Customs SE (Stockholm) participant 220˙640.00
11    DIRECTORATE OF NORWEGIAN CUSTOMS NO (OSLO) participant 207˙750.00
12    FORSVARETS FORSKNINGINSTITUTT NO (KJELLER) participant 207˙750.00
13    UNIVERSITE DE LAUSANNE CH (LAUSANNE) participant 173˙125.00
14    MAKSU- JA TOLLIAMETI EE (TALLIN) participant 55˙000.00
15    BMT GROUP LTD UK (TEDDINGTON) participant 2˙805.00

Map

 Project objective

Security and fraud in cross-border trade and supply chains are key priorities for the EU customs administrations due to the increasing risk of transnational crime and terrorism and the e-commerce-driven growth of customs declarations. Hence, EU customs administrations have to rapidly increase their capability to search for more accurate data sources to better assess these risks and increase their inspection hit rate. To address this challenge, PROFILE seeks to accelerate the uptake of state-of-the-art data analytics and incorporation of new data sources for more effective and efficient European customs risk management. The project provides tailored solutions, that build on modern methods in machine learning, graph-based analytics, and natural language processing, to help targeting officers and strategic analysts to collect and organise unstructured data, data-mine large datasets, apply semi-supervised machine learning that utilises feedback of control results, and to visualize complex data sets. PROFILE enables customs-to-customs systematic sharing of Entry Summary Declarations and other risk-relevant information through the EU-wide PROFILE Risk Data Sharing Architecture (RDSA). The project also connects national customs risk management systems to logistics Big Data of INTTRA and the Universal Postal Union (UPU) and provides customs an improved access to online data, especially valuation-relevant data of e-commerce sites. PROFILE also strengthens cooperation and data exchange among customs and other competent authorities. Better access to data, customised state-of-the-art data analytics, and stronger cooperation will provide the customs an enhanced 360º view on cross-border cargo flows. With PROFILE solutions, customs administration can increase substantially the hit rate of inspections and their capacity to cope with transnational crime, terrorism, and the dramatic e-commerce-driven growth of customs declarations.

 Publications

year authors and title journal last update
List of publications.
2019 Boriana Rukanova, Yao-hua Tan
Digital Trade Infrastructures and Big Data Analytics: The concept of Value as a Linking Pin
published pages: , ISSN: , DOI:
2020-03-05
2019 Boriana Rukanova, Yao-Hua Tan, Micha Slegt, Marcel Molenhuis, Ben van Rijnsoever, Krunoslav Plecko, Bora Caglayan, Gavin Shorten
Value of Big Data Analytics for Customs Supervision in e-Commerce
published pages: , ISSN: , DOI:
2020-03-05

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The information about "PROFILE" are provided by the European Opendata Portal: CORDIS opendata.

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