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Classification of FinTech Patents by Machine Learning and Deep Learning Reveals Trends of FinTech Development in China

Hao Wang, Xizhuo Chen, Jiangze Du*, Kin Keung Lai

*Corresponding author for this work

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    526 Downloads (CityUHK Scholars)

    Abstract

    The development of the financial industry and its integration with information technology have promoted FinTech innovation. China is a major contributor to FinTech innovation, but few studies have systematically summarized FinTech innovation and development in China from the perspective of patents. This lacuna is attributable to the lack of a generally accepted classification of FinTech patents and the unavailability of classified Chinese FinTech patent text data. To fill this research gap, we developed a classification of Chinese FinTech patents and manually annotated a set of patent texts to train machine learning and deep learning models to classify massive Chinese patent application data and identify different types of FinTech innovations. Among the evaluated models, the character-level convolutional neural network (CNN) model and BERT model classified FinTech innovation most accurately. We used the character-level CNN to classify 20,529 Chinese FinTech patent applications from 2013 to 2020. The classified dataset was used to briefly analyze the history of FinTech innovation development in China and its future prospects.
    Original languageEnglish
    Article number1852447
    JournalMathematical Problems in Engineering
    Volume2022
    Online published8 Jul 2022
    DOIs
    Publication statusPublished - 2022

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 8 - Decent Work and Economic Growth
      SDG 8 Decent Work and Economic Growth
    2. SDG 9 - Industry, Innovation, and Infrastructure
      SDG 9 Industry, Innovation, and Infrastructure

    Publisher's Copyright Statement

    • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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