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A Neural Network Approach for Analyzing Small Business Lending Decisions

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  • Wu, Chunchi
  • Wang, Xu-Ming

Abstract

In this paper, we apply the neural network method to small business lending decisions. We use the neural network to classify the loan applications into the groups of acceptance or rejection, and compare the model results with the actual decisions made by loan officers. Data were collected from a leading bank in Central New York. The sample contains important financial statement and business information of borrowers and the loan officers' decisions. We conduct the network training on the data sample and find that the neural network has a stronger discriminating power for classifying the acceptance and rejection groups than traditional parametric and nonparametric classifiers. The results show that the neural network model has a high predictive ability. Our findings suggest that neural networks can be a very useful tool for enhancing small-business lending decisions and reducing loan processing time and costs. Copyright 2000 by Kluwer Academic Publishers

Suggested Citation

  • Wu, Chunchi & Wang, Xu-Ming, 2000. "A Neural Network Approach for Analyzing Small Business Lending Decisions," Review of Quantitative Finance and Accounting, Springer, vol. 15(3), pages 259-276, November.
  • Handle: RePEc:kap:rqfnac:v:15:y:2000:i:3:p:259-76
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    Cited by:

    1. Christian A. Johnson, 2005. "Modelos de alerta temprana para pronosticar crisis bancarias: desde la extracción de señales a las redes neuronales," Revista de Analisis Economico – Economic Analysis Review, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines, vol. 20(1), pages 95-121, June.
    2. Christian A. Johnson & Rodrigo Vergara, 2005. "The implementation of monetary policy in an emerging economy: the case of Chile," Revista de Analisis Economico – Economic Analysis Review, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines, vol. 20(1), pages 45-62, June.
    3. repec:eee:riibaf:v:44:y:2018:i:c:p:16-25 is not listed on IDEAS
    4. Angelini, Eliana & di Tollo, Giacomo & Roli, Andrea, 2008. "A neural network approach for credit risk evaluation," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(4), pages 733-755, November.

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