Research on early warning method of major financial risk based on abnormal detection

Xueke Song ()
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Xueke Song: Shenzhen Bao’an District Songgang Experimental School, Teaching Department

A chapter in Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022), 2023, pp 660-664 from Springer

Abstract: Abstract With the continuous advancement of the digitization of the supply chain in the financial field, the integration of manufacturing and retail has become one of the development trends of financial digitization, and data resources have gradually become a bridge between production and sales. The Customer-to-Manufactory (C2M) e-commerce model with user-driven industrial customized production has become one of the important ways for the manufacturing industry to achieve digital transformation. However, the C2M e-commerce model has obstacles and bottlenecks in practice, mainly in two aspects: First, digital capabilities need to be improved. Second, the development of big data resources related to consumers is insufficient. Therefore, this study explores the early warning ideas of major risk methods through the analysis of abnormal detection values.

Keywords: Outlier detection; Finance; Risk; Early warning (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-098-5_75

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DOI: 10.2991/978-94-6463-098-5_75

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