The Framework of CAFE Credit Risk Assessment for Financial Markets in China.

The main goal of this paper is to discuss how we establish the framework of CAFE system by applying the hologram approach in Fintech which is suitable for Chinese markets, and how our CAF system is able to resolve the current three major issues of "rating being falsely high, the differentiation of credit rating grades being insufficient, and the poor performance of predicting early warning". 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; and 3) the poor performance of predicting early warning and related issues. These issues and problems show that by so far there is no Credit Assessment System suitable for China with "BBB" credit rating grade as the basic investment level in accordance with international standard for capital markets in the practice, which have severely restricted the healthy development of Chinas capital market. From the perspective of financial technical processing, the main reason for this phenomenon is due to a simple fact that there is not enough default (bad) samples available from the markets in China, which led to the difficulty for domestic and foreign rating agencies to establish reliable credit rating assessment criteria for entities and bonds/debts for capital markets in China. Thus we must consider how to create a reasonable number of "bad samples by using new approach in dealing with non-structured data, which is called "hologram approach as a fundamental tool. In this way, it allows us to extract risk features based on the heterogeneous big data from different sources as breakthrough points to establish the so-called "CAFE Risk Assessment System" (CAFE System). [ABSTRACT FROM AUTHOR]