Research on the early warning of financial system risks of debt of local and regional government based on artificial intelligence from the perspective of text analysis

Yinglan Zhao; Can Li; Xiang Sun

doi:10.1117/12.3026139

8 April 2024 Research on the early warning of financial system risks of debt of local and regional government based on artificial intelligence from the perspective of text analysis

Yinglan Zhao, Can Li, Xiang Sun

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Proceedings Volume 13090, International Conference on Computer Application and Information Security (ICCAIS 2023); 130904R (2024) https://doi.org/10.1117/12.3026139
Event: International Conference on Computer Application and Information Security (ICCAIS 2023), 2023, Wuhan, China

Abstract

Municipal debt levels have been on the rise in recent years, increasing the potential for financial system risks to emerge. Given that the traditional research methods are difficult to deal with the problems of irregular data and limited accuracy of early warning models, this paper introduces artificial intelligence methods such as neural networks to build a risk early warning model by learning and analyzing a large number of actual data. In addition, most of the existing studies only measure debt of local and regional government risk by index data, but do not fully consider the response strength of text information to the risk of debt of local and regional government and its important implications for financial system risks. In this respect, this paper introduces the text analysis method by constructing the word frequency matrix and calculating the weight contribution ratio, and adds and confirms the important role of new variables and factors in the early detection of financial system risks. The research result of this paper is expected to promote the deeper application of text analysis on early detection of financial system risks, and provide more accurate warning of financial system risks.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Yinglan Zhao, Can Li, and Xiang Sun "Research on the early warning of financial system risks of debt of local and regional government based on artificial intelligence from the perspective of text analysis", Proc. SPIE 13090, International Conference on Computer Application and Information Security (ICCAIS 2023), 130904R (8 April 2024); https://doi.org/10.1117/12.3026139

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KEYWORDS

Neural networks

Data mining

Data modeling

Analytical research

Education and training

Computing systems

Databases

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