There are some problems still exist in traditional individual credit assessment system. To solve the problems, a decision tree individual credit assessment model is proposed. Using SPSS Clementine data mining tool, the personal credit data is clustering analysis by decision tree C5.0 method. It is worse to class a customer as good when they are bad, than it is to class a customer as bad when they are good. It is discussed as the different proportion of loss.