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Application Of Logistic Regressionin Assessing The Credit Risk Of Smes

Author

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  • Hristina Vasileva

    (University of Economics – Varna, Bulgaria)

Abstract

Bank lending is the main financing source for small and medium-sized enterprises. At the same time, banks consider SME lending riskier than large enterprise. As result the rejection rate of SME loans and interestrates are higher than large enterprises. Thus, access to finance for SMEs is more difficult than large companies.. The purpose of the author is to present the nature of logistic regression and its application in the creation of credit risk assessment models, expressed through the ptobability of default; highlighting the advantages, disadvantages and difficulties of building a model through logistic regression and testing it; study of existing logistic regression models with a view to the future construction and adaptation of such a model, taking into account the peculiarities of SME financing in Bulgaria.

Suggested Citation

  • Hristina Vasileva, 2020. "Application Of Logistic Regressionin Assessing The Credit Risk Of Smes," Economic Science, education and the real economy: Development and interactions in the digital age, Publishing house Science and Economics Varna, issue 1, pages 334-345.
    • Handle: RePEc:vrn:cfdide:y:2020:i:1:p:334-345
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    More about this item

    Keywords

    Logit regression; credit risk; SMEs;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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