Name origin classification with Natural Language Processing models

The exploration of name origins holds immense value in understanding the rich cultural and historical tapestry of human societies. Moreover, name origin classification plays a crucial role in the "Know Your Customer" (KYC) process, which is an essential component of customer due diligence in various industries, including banking, finance, and e-commerce. This work investigates the application of Natural Language Processing (NLP) techniques to classify and analyze the origins of personal names, aiming to unravel the linguistic patterns embedded within them. This goal is achieved by leveraging cutting-edge NLP algorithms, such as word embeddings, sequence labeling, and Deep Learning models on a wide dataset of names coming from various origins. Indeed, this work presents a comprehensive dataset, built from diverse sources and by collecting an extensive range of data, in order to address the limitations of existing datasets and enable more nuanced analyses