[1]肖京,王磊,杨余久,等.感知认知技术在金融风险预警中的应用研究[J].智能系统学报,2021,16(5):941-961.[doi:10.11992/tis.202107027]
　XIAO Jing,WANG Lei,YANG Yujiu,et al.A systematic review of perceptual cognitive technology and its application in the field of financial risk early warning[J].CAAI Transactions on Intelligent Systems,2021,16(5):941-961.[doi:10.11992/tis.202107027]
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感知认知技术在金融风险预警中的应用研究

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 16 期数: 2021年第5期 页码: 941-961 栏目: 吴文俊人工智能科技进步奖一等奖 出版日期: 2021-09-05
Title:
A systematic review of perceptual cognitive technology and its application in the field of financial risk early warning
作者:
肖京1, 王磊1, 杨余久2, 李娜1, 赵盟盟1, 陈又新1, 谭韬1
1. 平安科技（深圳）有限公司，广东 深圳 518029;
2. 清华大学深圳国际研究生院，广东 深圳 518055
Author(s):
XIAO Jing1, WANG Lei1, YANG Yujiu2, LI Na1, ZHAO Mengmeng1, CHEN Youxin1, TAN Tao1
1. Ping’An Technology (Shenzhen) Co., Ltd., Shenzhen 518029, China;
2. Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China
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; 金融风险预警; 图像处理算法; 自然语言处理算法; 知识图谱
Keywords:
financial risk pre-warning; image processing algorithm; natural language processing algorithms; knowledge graph; financial risk pre-warning; image processing algorithm; natural language processing algorithms; knowledge graph
分类号:
TP183
DOI:
10.11992/tis.202107027
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。
Abstract:
The global spillover effect of financial risks is superimposed on the associated risks in the innovative development of China’s financial industry. The superposition has made the situation of international and China’s domestic financial 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.
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备注/Memo

收稿日期:2021-07-15。
基金项目:国家科技部重大项目（2020AAA0104204）；广东省重大专项项目（2020B01038000）
作者简介:肖京， 教授级高级工程师，国家特聘专家，主要研究方向为人工智能、机器人及金融科技。获省部级科技进步奖2项、国家专利优秀奖2项，2019年吴文俊人工智能科学技术奖“杰出贡献奖”。获授权发明专利130余项，发表学术论文232篇。王磊， 高级统计师，主要研究方向为金融大数据建模理论及应用研究。获2020年吴文俊人工智能科技进步奖一等奖。主持及参与科技部重大项目、工信部示范项目、广东省重大专项等5项。发表学术论文20余篇。杨余久， 副教授，主要研究方向为大数据环境下信息处理与机器学习应用的研究。获2020年吴文俊人工智能科学技术奖科技进步一等奖（排名第二），2015年广东省科技进步奖一等奖。主持国家、省部级和深圳市科研项目30余项。发表学术论文80余篇。
通讯作者:王磊.E-mail:wangleis25@pingan.com.cn

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