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Developing Credit Scoring Models When Small Sample Sizes Are Available

by Vesarach Aumeboonsuke

Title:

Developing Credit Scoring Models When Small Sample Sizes Are Available

Author(s):

Vesarach Aumeboonsuke

Issued date:

2013

Citation:

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

Keyword(s):

Credit scoring

Resource type:

Article

Extent:

6 pages

Type:

Text

File type:

application/pdf

Language:

eng

Rights holder(s):

Vesarach Aumeboonsuke

URI:

http://repository.au.edu/handle/6623004553/20958
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Copyright © Assumption University.
All Rights Reserved.

Contact Us

The St. Gabriel's Library   
Hua Mak Campus  
Ramkhamhaeng 24, Hua Mak  
Bangkok Thailand 10240  
Tel.: (662) 3004543-62 Ext. 3402  
Fax.: (662) 7191544  
E-Mail Library : library@au.edu  


The Cathedral of Learning Library
Suvarnabhumi Campus
Bang Na-Trad Km. 26 Bangsaothong
Samuthprakarn Thailand 10540
Tel.: (662) 7232024, 7232025
Fax.: (662) 7191544
E-Mail Library : library@au.edu
 

 

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