| With the personal credit business volume increased year by year,the risk of personal credit has gradually become an unstable factor which affecting the sustainable development of the banking industry.How to avoid personal credit risk,optimize the risk assessment program and reduce the potential loss of personal credit have become the urgent problems which need to be solved.In this paper,firstly,the relation between equivalence relation and partition is defined and attribute set independence determination is completed.An attribute reduction algorithm based on relative identification relationship is designed on the basis of relative identification relationship.Secondly,the theory of rough set is applied to the index system of personal credit risk assessment.The personal credit data processing was translated into finding attribute reduction in decision information system through data preprocessing method,such as data discretization and comprehensive evaluation,and the corresponding evaluation rules are obtained,and the design of the individual credit risk assessment model is completed.Then,the above personal credit risk assessment model and attribute reduction algorithm are applied to personal credit risk assessment system,which achieves the functions of sample acquisition,attribute reduction and rule extraction of personal credit data.Through processing and analyzing 67 sets of personal credit data and 31 sets of cases in Zhumadian commercial bank,the obvious improvement in efficiency and accuracy of system has been showed.The subjectivity of using theorem analysis to weaken the individual credit classification standards has been overcome by this system effectively.The classification of credit customers is more easily.The assessment of personal credit risk is more comprehensive,scientific and reasonable.The data support and decision reference for bank credit personnel and regulators will be provided to assess individual credit risk comprehensively and objectively. |
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