Articlegold2019

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

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Financial Distress and Bankruptcy Prediction Banking stability, regulation, efficiency Working Capital and Financial Performance

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.

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 2015Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research 1997Statistical Classification Methods in Consumer Credit Scoring: A Review 2006Trade Credit: Suppliers as Debt Collectors and Insurance Providers 2017Measuring firm size in empirical corporate finance 2007Modelling Credit Risk for SMEs: Evidence from the U.S. Market 1985ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS 2016Bargaining power and trade credit

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2022Financial ratios, corporate governance and bank-firm information: a Bayesian approach to predict SMEs’ default

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