13. The system of claim 9 , wherein the profile dependent variable is bankrupt/default wherein characteristics of consumers who file for bankruptcy versus those who go to default are used to classify a consumer as more likely to file bankruptcy or default.
9. A system for optimal partitioning of segments in a consumer credit segmentation tree comprising: a memory configured for storing credit related data comprising the input image; a processor, coupled to the memory, wherein the processor is configured to perform the steps of: generating by a computer a first attribute-based independent variable on a segmentation tree using a primary dependent variable having two classes, wherein a value of the independent variable is selected that creates two groups that minimize misclassification of the two classes of the primary dependent variable; generating by the computer a second attribute-based independent variable on the tree using the primary dependent variable; generating by the computer risk tiers for the first attribute-based independent variable on the tree using a first risk score and the primary dependent variable, wherein values of the independent variable are selected that create two groups that minimize misclassification of the two classes of the primary dependent variable; generating by the computer risk tiers for a first segment of the second attribute-based independent variable on the tree using the first risk score and the primary dependent variable, wherein values of the independent variable are selected that create two groups that minimize misclassification of the two classes of the primary dependent variable; generating by the computer risk tiers for a second segment of the second attribute-based independent variable on the tree using a second risk score and the primary dependent variable; and generating by the computer profiles in the risk tiers for the second segment of the second attribute-based independent variable with a profile dependent variable having two classes to complete the tree, wherein values of a profile model are selected that create two groups that minimize misclassification of the two classes of the profile dependent variable.