摘要
金融风险全球溢出效应与国内金融业态创新发展中的伴生风险相叠加,使得我国所面临的国际金融及内生性金融风险形势非常严峻。针对传统风险预警技术因缺乏有效、及时的关键因子导致实践中对金融风险预警难度极大的技术难题,本文重点总结了如何利用感知认知技术从海量非结构化信息提取有效、及时的金融风险预警关键因子,并在回顾现有金融风险预警模型研究现状的基础上,对相关技术难点和未来研究趋势进行总结和展望。本文研究内容可为我国研发自主可控的金融风险预警技术提供必要参考。
The global spillover effect of financial risks is superimposed on the associated risks in the innovative develop-ment of China’s financial industry.The superposition has made the situation of international and China’s domestic fin-ancial risks severe.Under such circumstances,the lack of effective and timely key factors in the traditional risk early-warning technology makes it extremely difficult to predict and forewarn the financial risks.This paper focuses on how to use perceptual cognitive technology to extract effective and timely key factors for the financial risk early-warning from considerable unstructured data.In addition,based on the review of the current researches of existing models,the paper summarizes relevant technical difficulties and future research trends.The research content of this paper can provide necessary reference for China's research and development of independent and controllable financial risk early-warning technology.
作者
肖京
王磊
杨余久
李娜
赵盟盟
陈又新
谭韬
XIAO Jing;WANG Lei;YANG Yujiu;LI Na;ZHAO Mengmeng;CHEN Youxin;TAN Tao(Ping’An Technology(Shenzhen)Co.,Ltd.,Shenzhen 518029,China;Tsinghua Shenzhen International Graduate School,Shen-zhen 518055,China)
出处
《智能系统学报》
CSCD
北大核心
2021年第5期940-961,共22页
CAAI Transactions on Intelligent Systems
基金
国家科技部重大项目(2020AAA0104204)
广东省重大专项项目(2020B01038000).
关键词
金融风险预警
图像处理算法
自然语言处理算法
知识图谱
financial risk pre-warning
image processing algorithm
natural language processing algorithms
knowledge graph