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The Credit Risk Assessment for Chinese Companies Based on CAFÉ System by Using Bigdata Method

EasyChair Preprint no. 8128

9 pagesDate: May 31, 2022


The Credit rating is one of the most important parts in finance and capital market, but, after nearly 30 years of rapid development in China's financial industry, the current domestic credit rating market is facing at least these three problems: 1) The rating is falsely high; 2) The differentiation of ​credit rating grades is insufficient; 3) The poor performance of predicting early warning and related issues. These issues and problems have not been a Credit Assessment System suitable for China with "BBB" as the basic investment level. From the perspective of financial technical processing, the main reason for this phenomenon is due to a simple fact that there is not enough bad samples available from the markets in China, so it is difficult for domestic and foreign rating agencies to follow the current well established practice to conduct the corresponding credit rating for listed companies. Thus we must consider how to create a reasonable number of bad samples by using new approach in dealing with non-structure data, which is called “Hologram approach” as a fundamental tool. In this way, we are able to extract risk feature factors based on the un-structured data as a breakthrough point to establish the so-called “CAFÉ Risk Assessment System”. The main goal of this paper is to conduct the assessment for a number of selected list companies as the application of “CAFÉ Credit Risk Assessment System” for eight cases from different industries, especially by combining the actual market performance of these eight cases with the time period from the past one to three years with our one-to-one interpretation of event screening and assessments, to show that how “CAFÉ approach” is able to resolve the 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.

Keyphrases: big data financial technology, CAFÉ Assessment System, credit rating, digital economy, Hologram, unstructured features

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {George X. Yuan and Chengxing Yan and Yunpeng Zhou and Haiyang Liu},
  title = {The Credit Risk Assessment for Chinese Companies Based on CAFÉ System by Using Bigdata Method},
  howpublished = {EasyChair Preprint no. 8128},

  year = {EasyChair, 2022}}
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