Developing Credit Scoring Models When Small Sample Sizes Are Available

Journal of Business Review, Cambridge, 20(1), 138-143, 2012

Posted: 30 Nov 2013

See all articles by Vesarach Aumeboonsuke

Vesarach Aumeboonsuke

International College of National Institute of Development Administration (ICO NIDA)

Arthur Dryver

National Institute of Development Administration (NIDA)

Date Written: 2012

Abstract

Making lending decision is an important process for financial institutions because it has a direct impact on the profits and losses of financial institutions. Therefore, financial Institutions try to develop good credit scoring models to make lending decisions. The purpose of this research is to compare the performance of the credit scoring models between multiple linear regression and logistic regression. The comparison of the credit scoring models is done through using three sets of population data generated through simulation. The odds ratio is adopted in this research as an evaluation tool. The findings of this research are useful for financial institutions especially commercial banks because they present the evidence of how well each credit scoring model can predict the credit score of the loan applicants.

Keywords: Credit scoring

JEL Classification: G21

Suggested Citation

Aumeboonsuke, Vesarach and Dryver, Arthur, Developing Credit Scoring Models When Small Sample Sizes Are Available (2012). Journal of Business Review, Cambridge, 20(1), 138-143, 2012, Available at SSRN: https://ssrn.com/abstract=2361280

Vesarach Aumeboonsuke (Contact Author)

International College of National Institute of Development Administration (ICO NIDA) ( email )

118 Seri Thai Road
Bangkok, 10240
Thailand

Arthur Dryver

National Institute of Development Administration (NIDA) ( email )

118 Seri Thai Road
Bangkok, 10240
Thailand

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