Research on early warning method of major financial risk based on abnormal detection
- DOI
- 10.2991/978-94-6463-098-5_75How to use a DOI?
- Keywords
- Outlier detection; Finance; Risk; Early warning
- 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.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xueke Song PY - 2022 DA - 2022/12/27 TI - Research on early warning method of major financial risk based on abnormal detection BT - Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022) PB - Atlantis Press SP - 660 EP - 664 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-098-5_75 DO - 10.2991/978-94-6463-098-5_75 ID - Song2022 ER -