The original intention of commercial bank to configure real estate customer credit resources allocation is that they can bring metric values. This value should be exchanged with low-cost as far as possible, be durable, and low-risk even no risk. Customer credit rating is the concrete embodiment of such a value-centered administration concept. And its important role can not be ignored. In the whole commercial bank credit business and management process, customer credit risk assessment is equivalent to a sill. But because the bank in our country has not been commercialized for so long, the systematic study of commercial bank customer credit rating is still in its infancy.This article starts with the definition of the commercial bank’s real estate loan credit risk, first, it has analyzed the formation mechanism of commercial bank’s real estate loan credit risk from the aspects of the real estates’ capital source, commercial banks’ operating mode, information asymmetry between borrowers and lenders, irregularity of land business in our country and so on, Then, expanded the developing background and content of A bank’s real estate customer credit rating model, and analyzed the advantages and disadvantages of existing rating measures. In allusion to the disadvantages of real estate customer credit rating model, this article uses the Logistic regression model and makes this method reconstructed. The process of constructing a new rating model has been expanded mainly from the aspects of sample selection, rating model building, weight coefficient risk factor calculating, empirical results and comparison analysis and etc.This article also point out that the ultimate goal of real estate customer credit risk assessments is to establish an optimal real estate customer selection mechanism, achieve the optimal allocation of credit resources and make the credit assets safety, liquidity and efficiency to be harmonious and unified. Therefore, commercial banks must improve and perfect continuously their own real estate customer rating system, so as to effectively guard against the real estate industry customer credit risk in Hunan. |