An Analysis of Credit Scoring Model for Rural Financial Market in Thailand

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Visit Limsombunchai: Department of Agricultural and Resource Economics,Faculty of Economics,Kasetsart University,Thailand

No 200701, Working Papers from Kasetsart University, Department of Agricultural and Resource Economics

Abstract: Loan contracts performance determines the profitability and stability of the financial institutions. The screening process of the loan applications is a key process in minimizing credit risk. Thus, the purpose of this research is to develop credit scoring model for rural financial market in Thailand. The results verify the important of asset value, capital turnover ratio, and the duration of bank-borrower relationship as important factors in determining the probability of a good loan in agricultural lending, whereas return on asset and capital turnover ratio are key factors in determining the probability of a good loan in non-agricultural lending. The study supports the use of Probabilistic Neural Network (PNN) in classifying good and bad loans. It is found that the PNN can detect a bad loan more accurately than Logit and Artificial Neural Network (ANN) models, and it gives the lowest misclassification costs.

Keywords: Credit Scoring; Rural Financial Market (search for similar items in EconPapers)
JEL-codes: G21 N25 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2007-06
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Published in ARE Working Paper No. 2550/1 (June 2007)

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