Patent ID: 7277869
Filing Date: 2007-10-02
Classification: G06Q

Abstract:
1. A method for predicting loan collections for a group of non-stationary asset-based loans using a computer system configured with a collections model and a re-marketing model, the group of non-stationary asset-based loans included within a distressed loan portfolio, an account including at least one of the loans, said method comprising the steps of: categorizing each non-stationary asset-based loan included within the portfolio based on a prior month's payment of the corresponding loan, non-stationary asset-based loans include at least one of automobile loans, vehicle loans, and credit card loans; categorizing each loan included within the portfolio based on a contractual delinquency of the corresponding loan; utilizing the computer and the collections model to predict a payment behavior for a borrower of a non-stationary asset-based loan included within a distressed loan portfolio, the collections model is based on historical payment information of the borrower, loan delinquency assumptions, a plurality of collection strategies that may be utilized for collecting payment from the borrower, and the delinquency category assigned to the loan; initiating at least one of the plurality of collection strategies with respect to the borrower; analyzing the borrower's payment behavior after initiating the at least one collection strategy including whether the borrower made a payment and, if so, an amount of the payment; comparing the borrower's payment behavior after initiating the at least one collection strategy to the predicted payment behavior of the borrower and the delinquency category assigned to the corresponding loan; comparing the borrower's payment behavior after initiating the at least one collection strategy to the prior month's payment category of the corresponding loan; incorporating management feedback into expectations of future performance wherein management feedback includes recommending a change in collection strategies used for prompting payment from the borrower associated with the loan included within the portfolio and predicting future payment performance of the borrower based on the recommended change in collection strategies: updating the collections model based on the payment comparisons and the management feedback, the updated collections model predicts future cash inflows for each loan included within the portfolio, the updated collections model is configured to apply a greater weight to the payment performance of each loan for the current month as compared to the payment performance of each loan for prior months; utilizing the computer and the re-marketing model to calculate an amount generated and expenses incurred from repossessing the non-stationary asset used as collateral for the borrower's loan, the re-marketing model further calculates a probability that an event will occur impacting payment of the borrower's loan; generating delinquency moving matrices for each loan included within the group of loans including the borrower's loan based on an output from the updated collections model and the re-marketing model, the matrices displaying for each account a percentage indicating a probability that the account will roll forward into a next classification of delinquency, and a number of months that the account is delinquent; and predicting which accounts will roll forward into a next classification of delinquency based on information displayed in the matrices.