Patent ID: 7003490

Claim:
A method of allowing inclusion of more than one variable in a classification and regression tree analysis for valuing a portfolio of non-performing loans and predicting future performance of the portfolio of non-performing loans using p explanatory variables, said method comprising the steps of: defining a first “parent” node representing the portfolio of non-performing loans; defining a split function to determine whether to create “child” nodes by generating a probability density function of the p explanatory variables at a corresponding parent node using a multivariate normal distribution; creating “child” nodes when a split function value for the corresponding parent node and child nodes indicates that the parent node is statistically non-homogeneous with respect to at least one of the p variables, wherein statistical non-homogeneity is determined by comparing the split function value for the corresponding parent and child nodes, and wherein statistical non-homogeneity indicates a greater predictive value included within at least one of the created child nodes as compared to the corresponding parent node; repeating said steps of defining a split function and creating “child” nodes until the parent node is statistically homogeneous; calculating y based on the p explanatory variables and the defined split functions, wherein y is a multivariate response vector representing a predicted recovery amount and a predicted timing value, the predicted recovery amount including at least one amount predicted to be recovered for each non-performing loan included within the portfolio of non-performing loans, the predicted timing value including at least one value predicting when each predicted recovery amount will be recovered, wherein the calculation is performed by a computer; and determining a value of the portfolio of non-performing loans based on the calculated y.