Tom Saltsberg , Product Manager
February 16, 2023

Transforming European Customs Clearance with Decision Intelligence 

Every year trillions of Euros worth of goods are imported into and exported out of European countries. The 27 EU member countries alone account for roughly 15%1 of the world’s trade in goods, a share which grows even larger if all European countries are considered.

However, as trade volumes continue to increase, European customs authorities find themselves spread thin. They face fundamental challenges in facilitating legal trade while also enforcing customs compliance and preventing fraud and criminal activities. To accelerate customs clearance, authorities must detect suspected cases of customs fraud, smuggling and criminal activities more accurately, thus allowing them to focus their workforce and resources on those shipments and containers, while fast-tracking the rest.

The Hijacking of Legitimate Trade by Criminal Groups

A cocaine shipment worth a record amount of EUR150 million was recently seized by Europol from a ship that was heading to a European port.

cocaine shipment. A large ship in the ocean with a small boat, linked to a recent EUR150 million cocaine seizure by Europol
Source: Europol, 2022 

This incident was not an isolated case, but an example of a larger trend. During 2021, Western European customs organizations reported 19,087 drug seizures, up 35% year over year2.  

Organized criminal groups are increasingly taking advantage of legitimate trade activity. These bad actors benefit from the sheer volume of global trade, which makes it easier for them to evade detection by authorities. 

Although illegal drugs also enter Europe by air transport, the majority are smuggled into via the maritime route from South America to western Europe. Belgium’s main container terminal in Antwerp has become the biggest route into Europe for illegal drugs, with 109.9 tons in total seized in 2022. 

Main trafficking connections between Latin American ports and EU ports
Source: EMCDDA, 2022 

In addition to drug trafficking, European customs organizations are facing growing challenges in combatting weapons smuggling, human trafficking, and trade in endangered species. 

Harnessing Customs Data

As explored in Cognyte’s recent report, customs officials in Europe and around the world are increasingly recognizing the value of data in optimizing their enforcement and operations. Significant efforts and investments have been made at national and regional levels in recent years to more effectively collect and aggregate data sources relevant for customs. OLAF, the European Anti-Fraud Office, maintains several massive databases, including CIS, IET, and CSM, which track goods and containers entering, leaving, and transiting EU member states.  

While customs declarations, invoices and bills of lading contain a wealth of information, there are many other data sources that can be tapped into to paint a wider picture. Government, commercial and open-source data sources can include everything from police records, AIS movement data, passenger data aggregated by SITA, and banking transactions to web and social media content. These sources can provide invaluable data to help customs officials combat illicit activities. For example, Interpol provides access to its stolen works of art database, which holds descriptions and pictures of more than 52,000 items. Using this database, customs officials are finding, identifying, and returning stolen cultural artifacts that might have otherwise slipped past.

Optimizing Customs Operations with Decision Intelligence 

However, access to siloed data sources alone is not enough. The challenge is fusing those data sources into a unified view, with holistic profiles for all relevant entities, and extracting analytical insights using machine learning and AI. But the diverse and siloed nature of the data poses a complex challenge. A Cognyte survey found that 78% of customs agencies identified fusing together structured and unstructured data from different sources as their biggest challenge in terms of extracting actionable insights from data. 

This is where decision intelligence comes into play. Decision intelligence combines analytics, machine learning, and AI to support and enhance critical decision-making.  

To uncover suspected instances of customs fraud and smuggling, many parameters must be analyzed, including:  

  • Individual taxpayers and corporations (including customs brokers, shippers, import/export companies, etc.) 
  • Places where goods are stored 
  • Movements of goods 
  • Means of transport 

Beyond simply analyzing the data, the true value lies in automatically detecting anomalies and suspicious patterns. 

For example, imagine a scenario where the European Union imposes anti-dumping duties for a particular product, rolled aluminum for example, coming from an Asian country. A shipment from a neighboring country, which shares a land border with the Asian country, is on its way to Spain. The volume and weight of the goods seems irregular for the type of product declared, but not enough to warrant further action. However, information from the ship’s AIS – a transponder that transmits a ship’s location – has some gaps. The ship is flying a Flag of Convenience and is registered with a corporation rather than an individual owner.  

When looked at individually, these data points may not raise a red flag. However, a decision intelligence platform providing a holistic view of all available data related to the shipment, could automatically generate an alert of suspicious activity, and flag the shipment for inspection. A best-in-class decision intelligence platform can generate a risk score for each shipment that passes through the border – and can do so at scale.  

Using risk management to prioritize which goods, shipments, and containers to inspect and which to fast-track is not a new concept. According to the WCO, risk profiling was the detection method responsible for 91% of weapons seizures, 80% of drug seizures, and 43% of tobacco and alcohol seizures3. Routine and random inspections and intelligence tipoffs were responsible for the rest. While these shares of seizure rates are high, they only hint at the effectiveness that true data-driven analysis might yield. Many customs organizations are using outmoded risk profiling systems which are based on outdated business rules and that analyze only a limited number of data sources. A top performing decision intelligence platform leveraging machine learning and analyzing multi-source data can improve the accuracy of inspections and the seizure rate far beyond the more rudimentary risk management tools currently used by many customs organizations.  

Going Beyond Customs Risk Management with NEXYTE

NEXYTE, the decision intelligence platform developed by Cognyte, was designed to enable faster, more accurate decision making through multi-source data fusion and advanced analytics.  

With NEXYTE, customs agencies can automatically assign risk scores for containers, shipments, and postal parcels, thus enabling optimized customs clearance and increased revenue collection. Using NEXYTE, customs organizations can conduct effective investigations and allow the authorities to conduct enforcement actions in a highly targeted manner. NEXYTE provides intuitive data visualization tools, making it easier for customer investigators to review and explore findings. Analysts and investigators can easily share information, collaborate effectively, and share data with law enforcement officials.  

Download our report, Transforming Customs Operations with Decision Intelligence, to see how you can increase revenue collection, stop smuggling, and prevent customs fraud. 

Book a live demo today to see how NEXYTE can improve your customs operations 


  2. WCO Illicit Trade report 2021 
  3. WCO Illicit Trade report 2021 

Tom Saltsberg , Product Manager

Tom is a Product Manager for NEXYTE, Cognyte’s decision intelligence platform. He has over 5 years of experience in Web and open source intelligence, as well as 6 years of experience in network intelligence. Tom holds a BSc in computer science from the Hebrew University and is currently pursuing a Master’s degree in computer science at Reichman University.
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