Introduction
Let’s explore the potential of Artificial Intelligence (AI) in progressing your global trade operations, with a specific focus on the process of Product Classification within international transactions. Over the past few years, AI has emerged as a pivotal technology, offering new opportunities to reshape our lives and business operations. Product Classification is complex and AI, particularly in the form of Prescriptive Machine Learning (ML), can enhance your trade team’s efficiency in this aspect of global trade.
Your global trade compliance efforts involve numerous business processes, and one that stands out prominently is Product Classification. Product Classification entails assigning a specific code from the Harmonized System (HS) to identify goods in international transactions. The resulting Classification Code holds significant global importance, impacting customs processing for both import management and export management. AI, and more specifically Machine Learning, can enhance the Product Classification process, offering business benefits in terms of time savings, accuracy and consistency.
Understanding Tariff Classification for Customs
The HS, developed by the World Customs Organization, serves as a standardized global tariff system. The first six digits, known as the “HS Code,” or a “subheading” aim to harmonize tariffs globally.
In addition, a country can add further numbers for more granular tracking of imports and exports. TARIC, the integrated Tariff of the European Union, and the US’s Harmonized Tariff Schedule (HTS) both use a 10-digit system.
The accurate assignment of the Classification Code is crucial for determining duties, eligibility for trade agreements, and adherence to government agency requirements. However, the process becomes intricate when additional attribute details are needed, often leading to delays, guesswork and inaccuracies in Classification.
Understanding Artificial Intelligence
To grasp the potential impact of AI on Product Classification, it is essential to understand the fundamentals of AI. Machine Learning, a subfield of AI, plays a pivotal role in processing vast amounts of data to achieve specific outcomes. At QAD, our approach involves Prescriptive Machine Learning, combining descriptive and supervised functionalities to provide users with recommended HTS Codes based on patterns identified in labeled data.
Let’s highlight a couple of definitions:
Artificial Intelligence: The field of artificial intelligence has a history longer than most people think. It encompasses computer systems that aim to emulate human cognition, as explained by Chirag Shah, a professor of information and computer science at the University of Washington.
Machine Learning: Machine learning is a subset of AI, serving as a means to achieve the goal of creating computer systems that replicate human behavior. Many of the successful AI systems developed in the last two decades, such as the autocorrect feature on iPhones or suggested searches on Google, rely on machine-learning techniques. While AI and ML are often used interchangeably, it is interesting to note that AI systems can exist without incorporating machine learning techniques.
QAD’s Approach to Product Classification Using AI
QAD’s AI capabilities for Product Classification leverages Machine Learning to analyze data from users’ Enterprise Resource Planning (ERP) systems, Import Entry declarations, and other relevant sources. The algorithm compares this data with previously Classified products in an importer’s database, returning a list of recommended HTS Codes based on the percentage of match. This innovative approach allows importers to boost efficiency and streamline the Classification process, starting from an established Classification and then significantly reducing manual efforts.
Misperceptions on AI’s Use for Product Classification
Addressing common misperceptions about AI in Product Classification is necessary for setting accurate expectations. Two prevalent misunderstandings include:
AI Performing Classification: Contrary to common belief, AI, particularly at the current stage of development, does not replace the human-driven Classification process entirely. QAD’s solution focuses on enhancing efficiency and accuracy through recommendations rather than autonomously performing the Classification.
AI Eliminating the Need for Classification Expertise: Despite advancements in AI, customs regulations emphasize the continued responsibility of Importers of Record to demonstrate ‘reasonable care’ in overseeing Classification accuracy. QAD recommends implementing periodic audits to ensure accuracy and augment the learning process of the AI application.
Summary
The complexities of Product Classification in global trade demand innovative solutions. QAD’s application of AI, specifically Prescriptive Machine Learning, offers an approach to accelerate the Classification process, improve accuracy and maintain compliance. As we embark on this exciting journey, QAD is committed to providing an understanding of both the challenges and solutions associated with AI in Product Classification. With QAD, our global trade customers gain efficiencies along with avoiding incorrect duty payments and noncompliance.
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