This paper develops a credit-analysis model encompassing the accuracy of analytical methods, quality of applicants, cost of acquisition and analysis, profit from good loans, and losses from bad loans. Information generally available to the lending institution and subjective estimates can then be used to select from among alternative credit-granting systems the system with the greatest expected net present value. Each institution is thus able to find the credit granting system most appropriate for its particular market and analytical abilities.

The model's profit maximizing objective and broad scope make it useful for setting credit department standards of performance. Costs can be compared with theoretical values of performance computed from loss rates, acceptance rates, and market information. The conditional probabilities, the chances of making the correct decision, can also be estimated for use in comparing methods of analysis or individual analysts. Unlike the loss rate, the conditional probability is an independent, unbiased measure of a method's accuracy.

The example presented dealt with consumer installment loans, but the formulation is applicable to direct lending of any type. It provides the means for comparing loans with differing initial costs as well as widely varying risk classes and maturities. Financial institutions making direct loans add substantial values to capital supplied by the money and capital markets. The model is a theoretical formulation of the relationship between the cost and output of credit analysis.