Tom Saltsberg , Product Manager
November 09, 2022

Preparing for Peak Retail Season – Boost Customs Risk Assessment With Decision Intelligence

November is a peak month for online shopping, with three major sale days – Singles’ Day, Black Friday and Cyber Monday – generating a frenzy of retail orders and shipments. In fact, Cyber Monday was the biggest online shopping day of 2021 in the US, with consumers spending $10.7 billion on US retail websites, according to the Adobe Digital Economy Index. While this shopping-heavy month can be heaven for retailers and shoppers alike, it can easily turn sour for the customs organizations responsible for gatekeeping a country’s entry-points, revenue collection and securing the flow of goods. 

Read on to find out how Cognyte’s decision intelligence platform assists customs organizations in assessing risks and deciding how to allocate their resources, especially during peak periods. 

Customs: A story of conflicting interests 

As the gatekeepers for a country’s imports and exports, customs organizations are faced with conflicting mandates. On the one hand, they are responsible for facilitating the flow of legitimate trade, a key component of economic growth and stability, and ensuring that customs duties are properly collected. On the other hand, customs organizations are tasked with preventing smuggling, tax evasion, and illicit activities, which often slows down the flow of goods.

Finding a balance between the need to monitor cargo, and the need to keep imports and exports flowing efficiently is perhaps the most significant challenge that customs organizations struggle with. This is especially true during peak shopping periods when volumes surge due to manufacturers shipping stock to retailers and ecommerce retailers sending packages to their customers. Less stringent monitoring means that customs clearance can proceed faster, thus avoiding port “traffic jams” and supply chain disruptions which can have a devastating impact on the economy. However, cutting back on monitoring can cause the government to lose out on customs revenue due to illicit trafficking of counterfeit goods, customs fraud, and tax evasion, and give free reign to dangerous and criminal activities. 

Maintaining the delicate balance 

Customs and port officials are tasked with making quick decisions regarding which goods should be inspected. All parties are interested in carrying out the customs inspection process and customs clearance in an efficient and effective manner. At the same time, customs officials must prevent smuggling and the loss of revenue from customs fraud and tax evasion. 

How can one balance the need to uphold the law and maintain security, while allowing a quick and efficient clearance process? Two main methods are commonly used by customs officials to determine which goods should be inspected: 

  • Risk profiling – Customs officials target specific cargo, packages, or containers for inspection, based on predefined criteria indicating that a certain shipment or package is suspect. 
  • Random inspection – Customs officials inspect certain types or categories of containers, packages, and transport vehicles arbitrarily, or based on loose criteria from past customs violations. This method is primarily used for deterrence. 

While each of these methods may lead to the discovery of some customs violations, a vast number of violations routinely slip through the hands of customs officials who rely on these methods alone. If customs organizations were to use all the resources and data available to them in an optimal way, they would catch many more violations and increase revenue collection significantly by optimizing the allocation of their staff and resources. 

Ideally, customs organizations should adopt a risk assessment approach and make data-driven decisions based on all relevant information in deciding which packages and shipments to inspect. However, this can be challenging given the large volumes of data which customs organizations have access to, as well as the diversity, inconsistency and siloed nature of the data. Underscoring the importance of leveraging data and adopting a data-driven decision making approach, the World Customs Organization has dedicated 2022 to urging the Customs community to scale up Customs digital transformation by embracing a data culture and building a data ecosystem.

Decision Intelligence 

This is where the concept of decision intelligence comes into play. 

Decision intelligence is the application of analytics, machine learning, and artificial intelligence to support and enhance human decision-making, and potentially automate the decision-making process. Interest in leveraging decision intelligence is growing rapidly amongst private enterprises as well as government agencies. Indeed, Gartner defined decision intelligence as one of the Top 10 Technology Trends for Government in 2022.

Decision intelligence platforms have been developed in recent years in order to put the concept of decision intelligence into practice on an enterprise scale. Best in class decision intelligence platforms leverage 3 main capabilities:  

  1. Data fusion – The synthesis of all relevant information into one unified view that provides a single source of truth and automatically generates holistic 360-degree profiles for all relevant entities (such as companies, shipments, vessels and containers). According to a recent survey conducted by Cognyte, data fusion is seen as a critical capability by investigators and analysts across all types of governmental agencies.
  1. Machine learning and analytics – Advanced capabilities that help assess risk, detect trends, uncover hidden connections, and spot suspicious patterns in shipments and financial transactions. 
  1. Collaboration tools – The ability to share information and collaborate in real-time in a single, unified workspace, allowing customs officials to work together and conduct investigations in. 

Making the “Random” Predictable 

Cognyte’s decision intelligence platform (NEXYTE) for customs organizations provides an answer to the risk assessment and investigations challenge.  

NEXYTE utilizes customs-specific data sources, including cargo manifests, airway bills, importer information, Harmonized System (HS) codes, container information, shipping routes and more. These data sources are combined to create a comprehensive profile for each shipment, merchandise, passenger or any other entity relevant for customs monitoring. 

Correlating many more data sources and analyzing small details that could easily go unnoticed can provide critical insights. For example, the route a shipment took before arrival by rail, sea or land and where it stopped, can be an important source of information. Was it a typical route, or an atypical, suspicious route? By detecting discrepancies between the information declared versus reality (e.g. weight discrepancies, route discrepancies, etc.), it is possible to home in on which cargo warrants extra inspection and examination. 

Leveraging advanced machine learning models tailored to the customs domain, NEXYTE analyzes each incoming and outgoing shipment or container to automatically calculate a risk score that helps customs officials decide whether it is legitimate, or whether there is reason to be suspicious and require an in-depth examination. 

In addition, NEXYTE provides a user-friendly platform that displays all information in a single-pane-of-glass view, making data accessible, and streamlining collaboration between customs personnel. This enables customs investigators and analysts to detect new trends and helps to uncover illicit activities and the bad actors involved. 

Leveraging over 25 years of experience in the field of investigative analytics, the NEXYTE decision intelligence platform enables customs organizations to boost clearance rates, more accurately detect suspicious shipments, increase revenue collection, and be better prepared for peak shopping season.  

Book a demo with our experts to find out more.  

Let's Empower Decision Intelligence

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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