A method for predicting expected and unexpected loss outcomes for a portfolio of loans is provided. The loans are issued by a lender to a plurality of borrowers. The method includes recording key account and risk attributes for a historical portfolio of loans, recording actual default and loss information for each borrower included within the historical portfolio of loans, and comparing the key account and risk attributes with the actual default and loss information over a period of time. The method also includes selecting a sample of loans from the historical portfolio of loans to determine loss drivers based on the comparison of the key account and risk attributes with the actual default and loss information, building a regression tree based model representing relationships between the loss drivers, and expected and unexpected loss outcomes for the historical portfolio of loans, and predicting the expected and unexpected loss outcomes for a second portfolio of loans using the regression tree based model and the loss drivers for the second portfolio of loans.
A method for managing business information and account strategy by a business entity is provided. The method uses a computer system coupled to a database. The method includes receiving at the computer system information including historical financial data relating to at least one customer of the business entity, and entering into the computer at least one risk factor including at least one of a deal driver, a tracking source, a tracking frequency, a target metric, a trigger level, an impact of factor, and corresponding action plan wherein the risk factor indicating a risk associated with the business entity providing financing to the customer. The method further includes updating the database periodically with newly received information, and monitoring the at least one deal driver to determine whether to alter a current account strategy being applied by the business entity to the customer including updating a buy/hold/sell plan.