Research On The Modeling Of Risk Custermer Identifying And Implementation

The current domestic and foreign Banks to group clients as well as ordinary customers conducted a risk assessment and early warning information system construction. Due to the traditional banking business in China, financial innovation is relatively conservative, although there is no foreign business so big risk, but with the development of domestic enterprises, also appeared a lot of bad debt risk. So the bank risk of early warning to the customer, become important content in bank risk customer identification work.This thesis mainly from the type of bank customer, customer risk recognition technology had two aspects, from the technical architecture of risk early warning global bank customer risk early warning model research. Especially for the customer demand, function demand of data in risk early warning, based on the algorithm, classification algorithm, Logistic algorithm, and algorithm for identification of risk and so on to analyze the characteristics of data modeling, according to the specific types and characteristics of our country banking customers of modeling tools selection, development tools, such as SAS system compare of the system, which will be based on customer recognition of risk early warning model, data analysis, information collection and pretreatment method, risk group of customer recognition algorithm, risk early warning model based on Logistic algorithm, modeling process, the comparative evaluation of the model, model improvement and merged together as a whole. In comparison, the research on the basis of the above problems, the practical application of the model and the possible effect of concrete experiment and analysis, from the inspection of the instance, test and application effect of data base and application, and analyzes some problems.Based on the principle, technology, and made some exploratory work on the design and implementation, has certain actual application value, and can adapt to different business, the great convenience of bank credit risk early warning of the decision making process.