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Credit Risk Assessment Model for Small and Micro-Enterprises: The Case of Lithuania

Author

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  • Rasa Kanapickiene

    (Department of Finance, Faculty of Economics and Business Administration, Vilnius University, 10222 Vilnius, Lithuania)

  • Renatas Spicas

    (Kaunas Region Credit Union, 44249 Kaunas, Lithuania)

Abstract

In this research, trade credit is analysed form a seller (supplier) perspective. Trade credit allows the supplier to increase sales and profits but creates the risk that the customer will not pay, and at the same time increases the risk of the supplier’s insolvency. If the supplier is a small or micro-enterprise (SMiE), it is usually an issue of human and technical resources. Therefore, when dealing with these issues, the supplier needs a high accuracy but simple and highly interpretable trade credit risk assessment model that allows for assessing the risk of insolvency of buyers (who are usually SMiE). The aim of the research is to create a statistical enterprise trade credit risk assessment (ETCRA) model for Lithuanian small and micro-enterprises (SMiE). In the empirical analysis, the financial and non-financial data of 734 small and micro-sized enterprises in the period of 2010–2012 were chosen as the samples. Based on the logistic regression, the ETCRA model was developed using financial and non-financial variables. In the ETCRA model, the enterprise’s financial performance is assessed from different perspectives: profitability, liquidity, solvency, and activity. Varied model variants have been created using (i) only financial ratios and (ii) financial ratios and non-financial variables. Moreover, the inclusion of non-financial variables in the model does not substantially improve the characteristics of the model. This means that the models that use only financial ratios can be used in practice, and the models that include non-financial variables can also be used. The designed models can be used by suppliers when making decisions of granting a trade credit for small or micro-enterprises.

Suggested Citation

  • Rasa Kanapickiene & Renatas Spicas, 2019. "Credit Risk Assessment Model for Small and Micro-Enterprises: The Case of Lithuania," Risks, MDPI, vol. 7(2), pages 1-23, June.
    • Handle: RePEc:gam:jrisks:v:7:y:2019:i:2:p:67-:d:239504
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    References listed on IDEAS

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    Cited by:

    1. Peng Liu & Daxin Dong, 2020. "Impact of Economic Policy Uncertainty on Trade Credit Provision: The Role of Social Trust," Sustainability, MDPI, vol. 12(4), pages 1-24, February.
    2. Carmen Gallucci & Rosalia Santullli & Michele Modina & Vincenzo Formisano, 2023. "Financial ratios, corporate governance and bank-firm information: a Bayesian approach to predict SMEs’ default," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 27(3), pages 873-892, September.
    3. Maribel Paredes-Torres & Ana del Rocío Cando-Zumba & José Varela-Aldás, 2022. "Income Tax for Microenterprises in the COVID-19 Pandemic: A Case Study on Ecuador," Sustainability, MDPI, vol. 14(5), pages 1-20, February.
    4. Teoh, Wenji, 2019. "The Market Risk on Domino's Pizza Incorporation's Peformance," MPRA Paper 97244, University Library of Munich, Germany, revised 15 Nov 2019.
    5. Rasa Kanapickiene & Greta Keliuotyte-Staniuleniene & Deimante Teresiene, 2021. "Disclosure of Non-Current Tangible Assets Information in Private Sector Entities Financial Statements: The Case of Lithuania," Economies, MDPI, vol. 9(2), pages 1-64, May.
    6. Wenji, Teoh, 2019. "Market Risk on Domino's Pizza Incorporation's Performance," MPRA Paper 97319, University Library of Munich, Germany, revised 15 Nov 2019.

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