Research Article
Analysis and research on financial risk prevention based on artificial intelligence algorithms
@INPROCEEDINGS{10.4108/eai.19-5-2023.2334410, author={Zhiming Xu}, title={Analysis and research on financial risk prevention based on artificial intelligence algorithms}, proceedings={Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19--21, 2023, Hangzhou, China}, publisher={EAI}, proceedings_a={ICBBEM}, year={2023}, month={7}, keywords={Artificial intelligence; Risk management; Online learning algorithms; Big data sample selection}, doi={10.4108/eai.19-5-2023.2334410} }- Zhiming Xu
Year: 2023
Analysis and research on financial risk prevention based on artificial intelligence algorithms
ICBBEM
EAI
DOI: 10.4108/eai.19-5-2023.2334410
Abstract
With the advent of the era of big data, the development of big data has brought opportunities as well as challenges to various industries. Effectively utilizing and analyzing the vast and complex big data has become a focal point across industries. Support Vector Machines (SVM), as a novel technology in data mining, possess unique advantages in addressing nonlinearity and high-dimensional problems. It demonstrates high accuracy in regression prediction and is capable of handling massive amounts of data. This article primarily elucidates the risk types faced by grassroots tax bureaus within the context of big data. By integrating ESG risk management, specific application scenarios, existing issues, and their underlying causes, the present state of risk management in grassroots tax bureaus in the era of big data is analyzed, providing insights into the dynamic field of risk management and offering potential avenues for future research.
