Pre-Warning Model Of Credit Risk Is Established For The Real Estate Of Commercial Bank

The financial crisis globalized in recent years has shown enormous impact of the loan crisis once of U.S.A. to us, see bank credit risk to whole financial influence of circle at the same time, especially the fast-developing real estate of our country at present, it brings just a bomb that may be ignited at any time of picture of recessive risk of the commercial bank. Though we already went out of period of the low ebb, the key period in our country's economy fast resuming, we should restrain the overheated momentum of invest, carry out the standard of the bank credit strictly, financial situation and unfinancial situation of the loan enterprises should be awared to prevent the credit risk from accumulating. Under this background, it is necessary to carry on further investigation on credit risk prewarning of the commercial bank, prevent the occurrence of risk from source, make correct credit policy, to reduce the credit losses of commercial bank to the lowest.This text is on the basis of studying the relevant theories of credit risk,construct the warning model of credit risk which meets the real estate of our country from financial factor index and non- financial factor index . First of all, it reviewed the course of the credit risk studying of domestic and international bank. Secondly, have introduced the knowledge of credit risk and the method of measuring. Moreover, analyzed the influence factor of credit risk, setting up the credit risk warning model for real estate. Finally, choosing the typical case of ICBC to examine the models, have proved feasibility and practicability of the models constructed to a certain extent.On the research approach, it uses the empirical research method to collect the dates of a large number of real estate enterprises. And then uses the main composition analytic approach and the structural equation to set up warning model, it is the first time to bring unmeasurable factor into warning models, overcome the shortcomings that there are too little quantitative index but too many indexes to determine the nature. Combine the datamation models with non-datamation models will obtain the early warning model of real estate enterprise's credit risk of judgement with simple and science.