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

Author

Listed:
  • Visit Limsombunchai

    (Department of Agricultural and Resource Economics,Faculty of Economics,Kasetsart University,Thailand)

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.

Suggested Citation

  • Visit Limsombunchai, 2007. "An Analysis of Credit Scoring Model for Rural Financial Market in Thailand," Working Papers 200701, Kasetsart University, Department of Agricultural and Resource Economics.
    • Handle: RePEc:kau:wpaper:200701
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    File URL: http://agri.eco.ku.ac.th/RePEc/kau/wpaper/are200701.pdf
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    More about this item

    Keywords

    Credit Scoring; Rural Financial Market;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • N25 - Economic History - - Financial Markets and Institutions - - - Asia including Middle East

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