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Credit risk evaluation and rating for SMES using statistical approaches: the case of European SMES manufacturing sector

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  • Kyriazopoulos Georgios

Abstract

The prevention of financial losses is crucial for enterprises, especially in periods of market instability and uncertainty. Credit risk refers to the likelihood that a company will not be able to cover its liabilities and become insolvent and defaulted. Credit risk is of utmost importance not only for the enterprises but also for financial institutions (banks), which try to eliminate any possible losses from insolvent clients. Most of the enterprises in Europe are SMEs (Small and Medium Enterprises). Manufacturing sector is one of the most important, especially in Western Europe. The aim of the current study is to evaluate credit risk of European SMES manufacturing companies for the period 2012-2014 under different schemes, with the use of a popular statistical approach, namely logistic regression. The results of the analysis imply that even with a mixed and unbalanced data set with a small number of defaults, the applied method perform well and provide meaningful results. The results of this paper could help the owners and the financial managers of SMEs in European Union in their financial decisions and strategic investments so as to be able to avoid credit risk and future bankruptcy. More viable SMEs in European Union may mean more development and less unemployment. Â JEL classification numbers: G30, G32, G33 Key Words: Credit risk, SMEs, Manufacture, Logistic Regression.

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  • Kyriazopoulos Georgios, 2019. "Credit risk evaluation and rating for SMES using statistical approaches: the case of European SMES manufacturing sector," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(5), pages 1-4.
    • Handle: RePEc:spt:apfiba:v:9:y:2019:i:5:f:9_5_4
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    References listed on IDEAS

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    Cited by:

    1. Pranith Kumar Roy & Krishnendu Shaw, 2022. "Developing a multi-criteria sustainable credit score system using fuzzy BWM and fuzzy TOPSIS," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5368-5399, April.
    2. Pranith Kumar Roy & Krishnendu Shaw, 2021. "A multicriteria credit scoring model for SMEs using hybrid BWM and TOPSIS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.

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    More about this item

    Keywords

    credit risk; smes; manufacture; logistic regression.;
    All these keywords.

    JEL classification:

    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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