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Qualitative Modelling of Credit Scoring: A Case Study in Banking

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  • Bana e Costa C.
  • Barroso L.
  • Soares J.

Abstract

Several modelling procedures have been suggested in the literature that aim to help credit granting decisions. Most of these utilize statistical, operational research and artificial intelligence techniques to identify patterns among past applications, in order to enable a more well-informed assessment of risk as well as the automation of credit scoring. For some types of loans, we find that the modelling procedure must permit the consideration of qualitative expert judgements concerning the performance attractiveness of the applications. In this paper, we describe in detail the various steps taken to build such a model in the context of the banking sector, using the macbeth interactive approach. The model addresses the scoring of medium and long term loans to firms, to enable the multicriteria assignment of each application to a category which may range from rejection to acceptance with different spreads.

Suggested Citation

  • Bana e Costa C. & Barroso L. & Soares J., 2002. "Qualitative Modelling of Credit Scoring: A Case Study in Banking," European Research Studies Journal, European Research Studies Journal, vol. 0(1-2), pages 37-52, January -.
    • Handle: RePEc:ers:journl:v:v:y:2002:i:1-2:p:37-52
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    References listed on IDEAS

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    1. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
    2. Zopounidis, C., 1999. "Multicriteria decision aid in financial management," European Journal of Operational Research, Elsevier, vol. 119(2), pages 404-415, December.
    3. Doumpos, Michael & Zopounidis, Constantin, 2001. "Assessing financial risks using a multicriteria sorting procedure: the case of country risk assessment," Omega, Elsevier, vol. 29(1), pages 97-109, February.
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    Cited by:

    1. Constantin Zopounidis & Michael Doumpos, 2013. "Multicriteria decision systems for financial problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 241-261, July.
    2. Maria A. S. Xavier & Fernando A. F. Ferreira & José P. Esperança, 2021. "An intuition-based evaluation framework for social credit applications," Annals of Operations Research, Springer, vol. 296(1), pages 571-590, January.
    3. Angilella, Silvia & Mazzù, Sebastiano, 2015. "The financing of innovative SMEs: A multicriteria credit rating model," European Journal of Operational Research, Elsevier, vol. 244(2), pages 540-554.

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