Credit Risk Analysis of Chinese Companies by Applying the CAFÉApproach

作     者：George X.Yuan Chengxing Yan Yunpeng Zhou Haiyang Liu Guoqi Qian Yukun Shi 

作者机构：Business SchoolChengdu UniversityChengdu 610106China Shanghai Hammer Digital Technology Co.Ltd.(Hammer)Shanghai 200093China Business SchoolSun Yat-Sen UniversityGuangzhou 510275China Business SchoolEast China University of Science and TechnologyShanghai 200093China School of Mathematics and StatisticsUniversity of MelbourneMelbourneVIC 3010Australia Adam Smith Business SchoolUniversity of GlasgowGlasgow G128QQUK 

出 版 物：《国际计算机前沿大会会议论文集》 (International Conference of Pioneering Computer Scientists, Engineers and Educators（ICPCSEE）)

年 卷 期：2022年第2期

页      面：475-502页

学科分类：0202[经济学-应用经济学] 02[经济学] 020205[经济学-产业经济学] 

主　　题：Credit risk analysis Digital economy Big data financial technology Hologram Unstructured features Credit rating CAFÉassessment system 

摘      要：It is known that the current Credit Rating in financial markets of China is facing at least three problems:1)the rating is falsely high;2)the differentiation of credit rating is insufficient;and 3)the poor performance of predicting early warning,thus we must consider how to create a reasonable new credit risk analysis approach to deal with issues for financial markets in China for those listed companies’*** report shows that by using a newmethod called the“Hologram approachas a tool,we are able to establish a so-called“CAFÉRisk Analysis System(in short,“CAFÉApproach,or“CAFÉ)to resolve three issues for credit rating in *** particular,the main goal in this paper is to give a comprehensive report for credit risk assessments for eight selected list companies by applying our“CAFÉfrom different industry sectors against actual market performance with the time period from the past one to three years through our one-by-one interpretation for event screening and true occurrence and related *** this way,we show how“CAFÉis able to resolve current three major problems of“rating is falsely high,the differentiation of credit rating grades is insufficient,and the poor performance of predicting early warningin the current credit market in China’s financial industry in practice.