Customs processes are of critical interest to governments due to their trade and national security significance. However, current manual processes overseeing customs operations can miss risky trade and declaration profiles potentially putting nations and their trade apparatus at huge risk. Continuously learning Intelligent Customs Solutions powered by AI/ML can help customs experts zero in on high-risk profiles while continuously managing all trade movements without fail and getting better with their predictions over time.
As goods are exchanged as part of the trade between nations, the growing cargo traffic almost always involves several issues and challenges related to customs duties, norms, and processes. The processes have become more intricate as different countries have different customs thresholds and structures while many have specific agreements with their top trading partners. Monitoring cargo movement and the associated documents manually is no longer feasible if the departments want to reduce leakage and stem illegal movement.
Traders sometimes adopt questionable practices with regard to their documents, tariff classification or goods valuation in order to reduce the duty and tax assessments or escape inspections by the government of restricted items that require licenses and additional supporting information.
With growing global trade, it’s not practical for customs authorities to constantly monitor the accuracy of commodity declarations to predict risky profiles for further examination.
As per the existing manual systems, risk profiling is static where customs experts spend most of their time on adding/updating business rules, identifying classifications by reviewing, and verifying user requests, and charge calculations and collections, instead of focusing on challenging classifications that carry the maximum risk.
Machine Learning helps create intelligent machines that work and react like humans at higher accuracy and efficiency than humans themselves. Intelligent customs solutions powered by AI-Machine Learning offer consistency, efficiency, and accuracy and are being embraced by customs organizations around the world. These intelligent solutions play a significant role in evaluating risks, monitoring commodity declarations, shrinking the customs cycle, and identifying fraudulent cases intelligently. They continue to learn and their predictions get better with time.
IC solutions are dynamic risk profiling solutions powered by Artificial Intelligence/ Machine learning capabilities and pinpoint risky declarations by using intelligent algorithms and predictive modeling based on target data elements, feeds, patterns, and historical data with declared HS codes. IC solutions also help organizations in supplementing existing business rules with newer rules to validate the declarations better. Implementing intelligent solutions for customs authorities can minimize their routine tasks and help them prioritize the most critical work instead. They assist authorities in improving process efficiency based on dynamic risk profiling, generating higher revenue, and assisting the customs experts to focus on red indicator profiles that require their attention.
Assumptions
Typically, government systems exhibit the most inertia in the face of even the strongest winds of change. However, ironically, any transformation of their processes and systems can have the maximum return. Customs processes and tariffs assume critical significance as global trade grows whose norms are not always straightforward. It is especially so in light of exceptions due to several multi-lateral agreements that exist to minimize the costs of trade through favorable tariffs. In such an environment, manual monitoring of trade borders to flawlessly identify and address risky or illegal trade is just not going to be enough. Intelligent Customs Solutions powered by AI/ML can systematically collate, analyze and identify riskier profiles more efficiently than any human agent can. This leaves the agents more time to focus on issues that require their maximum attention while enhancing government revenue, enhancing efficiency, and reducing errors.