Abstract

In the past few years, the development of natural language processing has been able to deal with many issues such as emotional analysis, semantic analysis, and so on. This review first introduces the development of natural language processing, and then summarizes their applications in financial technology, which mainly focuses on public opinion analysis, financial prediction and analysis, risk assessment, intelligent question answering, and automatic document generation. The analysis shows that natural language processing can give full play to its advantages in the financial field. Moreover, this paper also discusses the problems and challenges for financial technology that are developed based on natural language processing. Finally, this paper presents two developing trends of natural language processing in financial technology: deep learning and knowledge graph.

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