Document Type

Thesis - Open Access

Award Date


Degree Name

Master of Science (MS)

Department / School



All lending institutions are faced with the fact that a portion of their outstanding loans will not be repaid. A loan officer, or other designated individual, is normally charged 'it h the responsibility of evaluating loan applicants in terms of their comparative risks in order to reduce this inherent cost of doing business. The loan officer has traditionally evaluated consumer installment loan applicants using the three C's rule: character, collateral and capacity to repay, as his guideline for evaluating risk. The information required for this type of evaluation came from the data on the loan application, a credit check and character references. This study attempts to give a more objective alternative means of evaluating risk in consumer installment loans. It is believed that there are shared characteristics of individuals who repay loans and a different set of shared characteristics for those who do not. If these sets of characteristics are significantly different, future applicants could then be evaluated to see if their characteristics are more like those of the group which repaid their loans or to the group who didn’t. In order to accomplish this study, one particular lending institution was chosen whose principal business is that of consualer installment loans. Discriminant analysis was employed as the statistical tool used to determine if a sample of loans that were repaid and those which were not could be separated into two groups solely on their shared characteristics. The discriminant analysis allows the researcher the means of accomplishing this separation and ascertaining the degree of certainty that. the two groups are dissimilar, as well as evaluating which factors are most important in the discrimination process.

Library of Congress Subject Headings

Banks and banking, Cooperative

Installment plan

Ellsworth Air Force Base Federal Credit Union



Number of Pages



South Dakota State University