APPLICATION OF LOGISTIC REGRESSIONIN ASSESSING THE CREDIT RISK OF SMES

Hristina Vasileva ()
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Hristina Vasileva: University of Economics – Varna, Bulgaria

Economic Science, education and the real economy: Development and interactions in the digital age, 2020, issue 1, 334-345

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.

Keywords: Logit regression; credit risk; SMEs (search for similar items in EconPapers)
JEL-codes: C53 G17 G33 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:vrn:cfdide:y:2020:i:1:p:334-345

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