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On Credit Cooperatives’ Credit Risk Management System Based On Data Exploring’s Design And Application

Posted on:2015-06-16Degree:MasterType:Thesis
Country:ChinaCandidate:M L HuangFull Text:PDF
GTID:2308330467989299Subject:Software engineering
Abstract/Summary:PDF Full Text Request
As china s financial system is getting more open towards the outside, the RuralCredit Cooperatives, just like the commercial banks, are confronted withunprecedented opportunities and challenges. To survive and strive the toughenvironment, it is urgent for the (RCCs) to building up an advanced applicationanalyzing system on data collecting, PC connecting, and data analyzing for the creditrisk management,. This system here known as CRMS (Credit Risk ManagementSystem) not only helps its users to make accurate decision, but also improves theRCC s core competition ability. At present, the RCCs businesses mainly focused onaccepting deposits and making loans, therefore, controlling the credit risk is the toppriority among all the issues. By building a model of database analyzing applicationsystem and applying credit risk management theory, this paper eventually expored theCRMS suitable to improve RCCs competition ability.My analyzing tasks including the followings:(1) By reviewing the data exploring,credit risk management theories and its process of model building, this paper stressedthe importance of data analyzing technology in real credit risk management;(2)Completing the design for CRMS. First of all, it briefly stated the system overalldesign from the three layers of C/S structure and overall system structure. Then, itintroduced the overall system design structure from the customer management,business management model, interest management model, personnel managementmodel, system management model and query statistics model. Finally it had carried onthe credit cooperatives credit data base design from the concept of structure designand physical structure design.(3) Finally, The CRMS was completes from fouraspects: the project plans, the data line, the technology line and the application line.Moreover, the system test was also done by analyzing the system in the way of datapreprocessing, and data extracting.
Keywords/Search Tags:Data explorin, Clustering algorithm, Model building, Credit Managementsystem
PDF Full Text Request
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