An increasing number of businesses are choosing to automate their manual processes. This allows them to streamline their workflows, become more productive, cut costs and reduce human error.
Manual data entries fall victim to human error. Moreover, they consume much time which could be used for other more complex tasks. This is the reason why a food and beverage company decided to invest in automating the HS assignment process to each of their products.
The HS code is an international standardized system of numbers to classify traded products. In an international shipment, every item must have an HS code and should be placed in the Commercial Invoice. The code must be correctly introduced as it determines the number of import duties or other taxes the company must pay.
In the following graph, we can observe how the HS codes are organized:
As we can see, each pair of numbers refers to some specific information about the product.
The aim of this project is to create a machine learning model to automatically assign the HS code to each product based on its description. By using this algorithm, it is possible to eliminate manual data entry. This simplifies the work of warehouse employees and reduces errors in the HS codes assignation to products while also reducing costs and saving time.
The algorithm consists of a machine learning model that takes the description of a product and assigns the proper HS code by using specific rules. We can observe this process in the following diagram:
First, the algorithm is trained with millions of products’ descriptions with their matching HS codes and using machine learning it is possible to build a mathematical model which consists of specific rules for the HS code assignment. These rules are a single word or a combination of words contained in the product’s description and must be unique for each product.
Before applying artificial intelligence to their HS code assignation process, the company spent much time on this and the codes were wrong more frequently.
However, by using Artelnics' machine learning technology, this company managed to eliminate manual data entry, reduce human errors and improve their efficiency.
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