Abstract
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’ performance.
This report shows that by using a new method called the “Hologram approach” as a tool, we are able to establish a so-called “CAFÉ Risk Analysis System” (in short, “CAFÉ Approach”, or “CAFÉ”) to resolve three issues for credit rating in China. 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 “CAFÉ” from 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 events. In this way, we show how “CAFÉ” is 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 warning” in the current credit market in China’s financial industry in practice.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Five ministries and commissions including the people’s Bank of China: Notice on promoting the high-quality and healthy development of the credit rating industry in the bond market (Exposure Draft), 28 March 2021. http://www.pbc.gov.cn/tiaofasi/144941/144979/3941920/4215457/index.html
Altman, E.I.: Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J. Finance 23(4), 589–609 (1968)
Altman, EI., Sabato, G.: Modeling credit risk for SMEs: evidence from the US market. Abacus 43(3), 332–357 (2007)
Dun and Bradstreet: Dun and Bradstreet on credit rating [EB/OL] (2014). http://www.dandb.com/glossary/d-b-rating/
FICO. What is a credit score. https://www.myfico.com/credit-education/credit-scores/
Hull, J.: Options, Futures and Other Derivatives, 10th edn. Pearson, New York (2017)
Hull, J.: Risk Management and Financial Institutes, 5th edn. Pearson, New York (2018)
Jing, X.C., Li, D., Wang, J.: Current situation and development prospect of China’s credit rating agencies. China Financ. Bimonthly 21, 47–48 (2003)
Du, L.H.: Plan ahead: the internationalization challenge of Chinese rating agencies. Financ. Mark. Res. 62(7), 119–127 (2017)
Zhang, H.: Review and prospect of the development of China’s credit rating market. Financ. Dev. Res. 29(10), 29–35 (2018)
Feng, GH., et al.: Principles and Pragmatism of Credit Rating. China Finance Press (2019)
Baidu Encyclopedia: The Introduction to the world’s three major rating agencies (2020). https://baike.baidu.com/item/%E4%B8%96%E7%95%8C%E4%B8%89%E5%A4%A7%E8%AF%84%E7%BA%A7%E6%9C%BA%E6%9E%84/8368411?fr=aladdin
Anderson, R.: The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation, 1st edn. Oxford University Press, Oxford (2007)
Chi, G.T., Yu, S.L., Yuan, G.X.: Facility rating model and empirical for small industrial enterprises based on LM test. J. Ind. Eng. Manag. 33, 170–181 (2019)
Thomas, L., Crook, J., Edelman, D.: Credit Scoring and Its Applications, 2nd edn. SIAM, Philadelphia (2017)
Witzling, D.: Financial complexity: accounting for fraud. Science 352(6283), 301–301 (2016)
Yuan, G., Wang, H.Q.: The general dynamic risk assessment for the enterprise by the hologram approach in financial technology. Int. J. Financ. Eng. 6(1), 1–48 (2019)
Ministry of Finance of the People’s Republic of China: Accounting Standards for Business Enterprises No. 36 - disclosure by related parties, promulgated on 18 June (2008)
Yuan, G.X.: Using big data approach to improve the quality of credit rating in China: the CAFÉ risk assessment system. Tsinghua Financ. Rev. 98, 70–74 (2022)
Yuan, G.X.: Overview for the credit rating system for the financial industry in line with international standards and suitable for Financial Markets in China. Reported by Xinhua Finance and economics. https://bm.cnfic.com.cn/sharing/share/articleDetail/2603844/1. Accessed 25 Dec 2021
Jarrow, R.A., Lando, D., Turnbull, S.M.: A Markov model for the term structure of credit risk spreads. Rev. Financ. Stud. 10(2), 481–523 (2004)
Yuan, G.X., Zhou, Y.P., Yan, C.X., et al.: New method for corporate financial fraud early warning and risk feature screening: based on artificial intelligence algorithm. In: Proceedings of the 15th China Annual Management Conference, pp. 709–724 (2020)
Yuan, G.X., Liu, H.Y., Zhou, Y.P., et al.: The extraction of risk features by applying stochastic search algorithm FOF under the framework of bigdata. Manag. Sci. 33(6), 41–53 (2020)
Yuan, G.X., Zhou, Y.P., Li, D., et al.: The framework for risk characteristic factor base on AI algorithms in Fintech. J. Anhui Univ. Eng. 35(04), 1–13 (2020)
Geman, S., Geman, D.: Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Math. Intell. 6, 721–741 (1984)
Fawcett, T.: An introduction to ROC analysis. Pattern Recogn. Lett. 27(8), 861–874 (2006)
Hanley, J.A., McNeil, B.J.: A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 148(3), 839–843 (1983)
Altman, E.I.: Corporate Financial Distress. A Complete Guide to Predicting, Avoiding, and Dealing with Bankruptcy. Wiley Interscience, Wiley, New York (1983)
Yuan, G.X., Zhou, Y.P., Liu, H.Y., Yan, C.X.: The framework of CAFE credit risk assessment for financial markets in China. Procedia Comput. Sci. 202, 33–46 (2022)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Yuan, G.X., Yan, C., Zhou, Y., Liu, H., Qian, G., Shi, Y. (2022). Credit Risk Analysis of Chinese Companies by Applying the CAFÉ Approach. In: Wang, Y., Zhu, G., Han, Q., Zhang, L., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2022. Communications in Computer and Information Science, vol 1629. Springer, Singapore. https://doi.org/10.1007/978-981-19-5209-8_33
Download citation
DOI: https://doi.org/10.1007/978-981-19-5209-8_33
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-5208-1
Online ISBN: 978-981-19-5209-8
eBook Packages: Computer ScienceComputer Science (R0)