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Assess the Rating of SMEs by using Classification And Regression Trees (CART) with Qualitative Variables

Author

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  • Francesco Campanella

    (Department of Economics, Second University of Naples Corso Gran Priorato di Malta, 1, Capua, Caserta, 81043, ITALY)

Abstract

Italian banks have never used the credit rating system to grant funds to SMEs until the introduction of Basel II accord. Credit Rating Systems use financial ratios that are often not adapted to SMEs' assessment. In fact, small and medium-size enterprises are characterized by a high level of intangible assets. Some researchers focus their attention on the evaluation of qualitative variables of SMEs (management; corporate governance; SMEs-territory relationship), but no research is able to integrate these SMEs¡¯ qualitative variables into a single scoring model, or to sufficiently consider the characteristics of SMEs-financial markets relationship. This paper proposes a specific credit scoring model to SMEs' assessment which includes all these variables combining two methods: Altman¡¯s ¡®EM-Score¡¯ and CART (Classification and Regression Tree). This model is performed on a sample of 6,534 Italian manufacturing firms getting a high level of reliability.

Suggested Citation

  • Francesco Campanella, 2014. "Assess the Rating of SMEs by using Classification And Regression Trees (CART) with Qualitative Variables," Review of Economics & Finance, Better Advances Press, Canada, vol. 4, pages 16-32, August.
  • Handle: RePEc:bap:journl:140302
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    References listed on IDEAS

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    1. Kwan, Simon H., 1996. "Firm-specific information and the correlation between individual stocks and bonds," Journal of Financial Economics, Elsevier, vol. 40(1), pages 63-80, January.
    2. da Silva Rosa, Ray & Velayuthen, Gerard & Walter, Terry, 2003. "The sharemarket performance of Australian venture capital-backed and non-venture capital-backed IPOs," Pacific-Basin Finance Journal, Elsevier, vol. 11(2), pages 197-218, April.
    3. Rajeswararao S. Chaganti & Vijay Mahajan & Subhash Sharma, 1985. "Corporate Board Size, Composition And Corporate Failures In Retailing Industry[1]," Journal of Management Studies, Wiley Blackwell, vol. 22(4), pages 400-417, July.
    4. Lee, Tian-Shyug & Chiu, Chih-Chou & Chou, Yu-Chao & Lu, Chi-Jie, 2006. "Mining the customer credit using classification and regression tree and multivariate adaptive regression splines," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 1113-1130, February.
    5. David Durand, 1941. "Risk Elements in Consumer Instalment Financing," NBER Books, National Bureau of Economic Research, Inc, number dura41-1.
    6. Eric M. Schwartz & Eric T. Bradlow & Peter S. Fader, 2014. "Model Selection Using Database Characteristics: Developing a Classification Tree for Longitudinal Incidence Data," Marketing Science, INFORMS, vol. 33(2), pages 188-205, March.
    7. Kavoussi, Rostam M., 1984. "Export expansion and economic growth : Further empirical evidence," Journal of Development Economics, Elsevier, vol. 14(1), pages 241-250.
    8. Lopez, Jose A. & Saidenberg, Marc R., 2000. "Evaluating credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 151-165, January.
    9. Giampaolo Gabbi & Massimo Matthias & Marco De Lerma, 2006. "CART analysis of qualitative variables to improve credit rating processes," Computing in Economics and Finance 2006 179, Society for Computational Economics.
    10. Cumming, Douglas & Schmidt, Daniel & Walz, Uwe, 2010. "Legality and venture capital governance around the world," Journal of Business Venturing, Elsevier, vol. 25(1), pages 54-72, January.
    11. Crouhy, Michel & Galai, Dan & Mark, Robert, 2000. "A comparative analysis of current credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 59-117, January.
    12. David Durand, 1941. "Risk Elements in Consumer Instalment Financing, Technical Edition," NBER Books, National Bureau of Economic Research, Inc, number dura41-2.
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    Cited by:

    1. Francesco Campanella & Maria Rosaria Della Peruta & Stefano Bresciani & Luca Dezi, 2017. "Quadruple Helix and firms’ performance: an empirical verification in Europe," The Journal of Technology Transfer, Springer, vol. 42(2), pages 267-284, April.
    2. Muhammad Akbar Ilma & Murtanto Murtanto, 2022. "Bank role in preventing money laundering and cyber security," Technium Social Sciences Journal, Technium Science, vol. 37(1), pages 287-299, November.
    3. Mauro Mussini, 2016. "On Measuring Income Polarization: An Approach Based On Regression Trees," Statistics in Transition New Series, Polish Statistical Association, vol. 17(2), pages 221-236, June.
    4. Corazza, Marco & Funari, Stefania & Gusso, Riccardo, 2016. "Creditworthiness evaluation of Italian SMEs at the beginning of the 2007–2008 crisis: An MCDA approach," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 1-26.
    5. Mussini Mauro, 2016. "On Measuring Income Polarization: An Approach Based on Regression Trees," Statistics in Transition New Series, Polish Statistical Association, vol. 17(2), pages 221-236, June.
    6. Mauro Mussini, 2016. "On Measuring Income Polarization: An Approach Based On Regression Trees," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 17(2), pages 221-236, June.
    7. Marco Corazza & Giovanni Fasano & Stefania Funari & Riccardo Gusso, 2017. "PSO-based tuning of MURAME parameters for creditworthiness evaluation of Italian SMEs," Working Papers 04, Department of Management, Università Ca' Foscari Venezia.

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    More about this item

    Keywords

    Credit scoring model; Hierarchies of qualitative variables; Classification and Regression Trees; Rating; Relationship between SMEs and financial markets;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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