Similarity versus Supervision: Best Approaches for HS Code Prediction
Sédrick Stassin, Otmane Amel, Sidi Ahmed Mahmoudi, Xavier Siebert · 2023
With growing e-commerce flows and new legislative rules, customs representatives confront serious liabilities when completing customs declarations for their clients.In the latter, the Harmonized System (HS) code is a crucial component using 10 digits (HS10) to classify products and define national tax rates.In this paper, we first compare the performance of sentence embedding models using semantic similarity, and second, we assess the effectiveness of supervised models, both aimed at predicting up to the HS10 code.To the best of our knowledge, there is currently little research being conducted on this topic.We demonstrate the differences and respective strengths of each approach.Our results show the outstanding performance of the semantic similarity approach with a top-3 and top-5 accuracy of 89% and 94.8% respectively for HS10 prediction.* These authors contributed equally to this work.† The authors thank the support of the Infortech institute and the E-origin