How Analytics Help Reduce Risks and Streamline Customs Operations

Governments and agencies around the world are facing great pressures to be more efficient and effective, in addition to doing more with fewer resources. Customs authorities, in particular, are facing new challenges resulting from the pandemic, as well as shrinking budgets and increasing risks.

As supply chains and the flow of products across borders and ports normalize, customs must be more agile and resilient, while monitoring strict compliance with rules and regulations, as well as keeping an eye out for any attempts at fraud or crime.

Traditional methods have generally worked well but current global and local conditions demand the use of more advanced methods to address these challenges. For this purpose, customs authorities implement technological tools, such as analytics, artificial intelligence, and machine learning, to improve their processes, and thus ensure compliance and improve service to citizens and organizations.

They must also do so by always observing freedom of movement, reducing risks, preserving national and social security, ensuring the correct collection of tariffs, deploying human talent in the right places, at the right time, and ensuring that revisions do not delay the transit of goods and people. 

Ensuring Efficiency

Agencies must, therefore, take advantage of their data, which is often dispersed in different sources and siloes. Collecting this data can help detect suspicious events, identify areas of risk, and issue notifications to agents to respond immediately to intercept illegal or high-risk activities.

Each country is responsible for monitoring its borders and keeping an eye on aspects such as national security, migration, combating the movement of people and migrants, preventing the smuggling and passage of drugs, making efficient use of public resources and funds, and complying with local and international legislations.

Physical security, in combination with new processes, is important and can help in this task. But in a world where data is fundamental, it is important to use processes and technologies that ensure efficiency in identifying and investigating suspicious activities.

It is not enough to simply collect data. Organizations must make good use of their data assets to ensure that high-risk passengers and cargo shipments are intercepted without a negative impact on the processing of legitimate passengers and freight at borders.

Many governments have raised their requirements for collecting data. In addition, customs authorities now have access to a wide range of sources, including manifestos, requests for permits and visas, watch lists or blacklists, police files, intelligence reports, and non-intrusive systems.

A Holistic View

Regarding human capital, agents, analysts, and researchers may have certain limitations in manually identifying unusual activity patterns, suspicious people, and other anomalies among this vast amount of data. 

Agencies, therefore, choose to use analytics to identify high-risk cargoes or passengers, and make all that data available to other colleagues and stakeholders so that they can act immediately. Here, collaboration between institutions to guarantee social and national security is critical.

Complemented by artificial intelligence, machine learning, data mining, and automation, analytics gives these stakeholders a holistic view of all available data, helping them identify hidden relationships, and bring to light social networks around people, organizations, shipments, and other elements.

In the same way, it allows the design of surveillance scenarios and rules that identify areas of concern around goods, travelers and high-risk or suspicious events, and automatically alerts analysts, and agents. These, in turn, gain the ability to search multiple internal and external data sources from a single interface. 

Based on their discoveries and the results of investigations, analysts make concrete decisions to speed up processes and traffic, or to prevent the passage of objects or people that represent a latent risk.

Customs Efficiency

In an environment where international trade is accelerating and where border surveillance is crucial, customs agents and analysts must no longer work with information silos that are difficult to access.

Working with silos of information that are difficult for border agents and analysts to access is not suitable for the modern era of border management and international trade. It is imperative that national border agencies empower their analysts using data, risk-based analysis, proactive surveillance and alerting, data exploration, and case and investigation management.

It is also important that the responsible authorities in each country provide their collaborators with the tools and collaborative systems that allow them to take advantage of the data, carry out accurate risk analysis, carry out proactive surveillance, and manage cases and investigations efficiently.  

This will have a positive impact on the exchange of merchandise and talent, in the context of current trade agreements between countries, such as the treaty between the US, Mexico and Canada (USMCA), as well as on global supply chains that are being reactivated after a delay caused by the pandemic. This will not only contribute to raising economic competitiveness but allow much more to be done with less and more effectively.