Article ID: | iaor1995166 |
Country: | United States |
Volume: | 42 |
Issue: | 4 |
Start Page Number: | 589 |
End Page Number: | 613 |
Publication Date: | Jul 1994 |
Journal: | Operations Research |
Authors: | Rosenberg Eric, Gleit Alan |
Keywords: | statistics: data envelopment analysis |
Many static and dynamic models have been used to assist decision making in the area of consumer and commercial credit. The decisions of interest include whether to extend credit, how much credit to extend, when collections on delinquent accounts should be initiated, and what action should be taken. The authors survey the use of discriminant analysis, decision trees, and expert systems for static decisions, the dynamic programming, linear programming, and Markov chains for dynamic decision models. Since these models do not operate in a vacuum, they discuss some important aspects of credit management in practice, e.g., legal considerations, sources of data, and statistical validation of the methodology. The authors provide the present perspective on the state-of-the-art in theory and in practice.