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

被引:13
|
作者
Kanapickiene, Rasa [1 ]
Spicas, Renatas [2 ]
机构
[1] Vilnius Univ, Fac Econ & Business Adm, Dept Finance, LT-10222 Vilnius, Lithuania
[2] Kaunas Reg Credit Union, LT-44249 Kaunas, Lithuania
来源
RISKS | 2019年 / 7卷 / 02期
关键词
trade credit; small and micro-enterprises; financial non-financial variables; risk assessment; logistic regression; TRADE CREDIT; EMPIRICAL-ANALYSIS; CORPORATE FAILURE; FINANCIAL RATIOS; CEO POWER; PREDICTION; SMES; DETERMINANTS; SYSTEM; SIZE;
D O I
10.3390/risks7020067
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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.
引用
收藏
页数:23
相关论文
共 50 条
  • [21] Research On Credit Guarantee Problems In Small And Micro Enterprises' Credit Financing
    Guo, Xiaoyan
    Wang, Jing
    Wang, Fang
    PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON EDUCATION TECHNOLOGY AND INFORMATION SYSTEM (ICETIS 2014), 2014, 115 : 105 - 109
  • [22] Credit strategy of micro, small, and medium enterprises with known reputation risk: Evidence from a comprehensive evaluation model
    Chen, Wanting
    Wu, Xuanyi
    Chen, Z. Y.
    Meng, Yahui
    Wang, Ruei-yuan
    Chen, Timothy
    JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, 2023, 44 (04): : 637 - 652
  • [23] Credit Rationing in Small and Micro Enterprises: A Theoretical Analysis
    Jin, Yuhuan
    Zhang, Sheng
    SUSTAINABILITY, 2019, 11 (05):
  • [24] Credit Decision System of Small and Medium Sized Micro Enterprises Based on Big Data Technology and Risk Assessment Thinking
    Xu, Chenheng
    Tao, Jindian
    Xu, Pengyuan
    2021 6TH INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA 2021), 2021, : 477 - 480
  • [25] Research on the Safeguard Mechanism of Cooperation between Vocational Colleges and Small Micro-enterprises
    Li, Kun
    INTERNATIONAL SYMPOSIUM ON ENGINEERING TECHNOLOGY, EDUCATION AND MANAGEMENT (ISETEM 2014), 2014, : 604 - 609
  • [26] The Financing Method of China's Small and Micro-Enterprises: Based on Mathematical Modelling
    Yang Juan
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS, 2014, 52 (03): : 100 - 109
  • [27] Credit Risk Assessment Model of Real Estate Enterprises Based on SVM
    Wu Chong
    Zhang Xinying
    Navia Vazquez, Angel
    PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON CONSTRUCTION & REAL ESTATE MANAGEMENT, VOLS 1 AND 2, 2009, : 308 - +
  • [28] What Barriers prevent Small and Micro-enterprises from Implementing a Risk Assessment of Mental Stress? A qualitative Interview Study from multiple Sources
    Pavlista, V
    Angerer, P.
    Kuske, J.
    Schwens, C.
    Diebig, M.
    GESUNDHEITSWESEN, 2021, 83 (08/09) : 684 - 684
  • [29] Housing credit access model: The case for Lithuania
    Zavadskas, EK
    Kaklauskas, A
    Banaitis, A
    Kvederyte, N
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2004, 155 (02) : 335 - 352
  • [30] Investigation of the Application of Machine Learning Algorithms in Credit Risk Assessment of Medium and Micro Enterprises
    Zhao, Yujie
    IEEE ACCESS, 2024, 12 : 152945 - 152958