Predicting China’s SME Credit Risk in Supply Chain Finance Based on Machine Learning Methods

You, Zhu; Xie, Chi; Wang, Gang‐Jin; Yan, Xin-Guo

doi:10.3390/e18050195

Cited by 36 publications

(17 citation statements)

References 22 publications

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“…Chang et al [ 33 ] using arithmetic, geometric and harmonic means, assessed how individual countries could prepare for COVID-19 and how, in relation to the above, effective business, economic and financial decisions can be planned. In turn, G. Wang et al [ 34 ], when considering risk management, focused on economic and social development provided by universities which, in crisis situations, gather relevant human resources necessary for emergency medical services. This is illustrated by one of the behavior models in the crisis situation related to the pandemic, which is different in the case of enterprises where human resources are reduced.…”

Section: Literature Reviewmentioning

confidence: 99%

Risk Assessment of the SME Sector Operations during the COVID-19 Pandemic

Grondys

Ślusarczyk

Hussain

et al. 2021

IJERPH

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The subject matter of the article relates to the assessment of the perception of selected types of risk in economic activities of the SME sector, which change their intensity as a result of the outbreak of the COVID-19 pandemic. The current economic downturn is unprecedented and involves many companies and industries that have faced new, previously unknown challenges and threats. The objective of the article is to identify the most important risks and their resources based on the empirical research carried out in small and medium-sized enterprises in Poland. The formulated objective was accomplished using the data collection method, i.e., the survey and reports on the condition of the SME sector in Poland as well as statistical data analysis methods, i.e., structure index and the analysis of variance, using the SPSS system. The process of primary data collection was carried out by means of an electronic survey among selected enterprises of the SME sector, conducting business activities in Poland. In the study, the employment factor was taken into account as a determinant of the perception and assessment of the intensity of selected risks arising from the economic activity in the Polish market in the conditions of the current economic downturn. On the basis of the obtained results, the impact of market, economic, financial and operational risks, depending on their intensity, on the functioning of micro-, small and medium-sized enterprises was identified. Based on the analysis of variance, the effect of the size of the company on the level of individual risks was also examined. As a result of the observations made, it was established that, during the pandemic, the level and type of risk is similar in all the surveyed enterprises. They are most often threatened by strong competition in the industry, an increase in energy prices and insufficient profit. The overall results of the empirical research indicate the importance and the need to manage the key threats to the Polish SME sector.

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Section: Literature Reviewmentioning

confidence: 99%

Risk Assessment of the SME Sector Operations during the COVID-19 Pandemic

Grondys

Ślusarczyk

Hussain

et al. 2021

IJERPH

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“…Some literatures [26,32] identified credit risk by considering whether the enterprise is special treatment (ST).…”

Section: Multiview Graph-based Learning For Classificationmentioning

confidence: 99%

“…Zhang et al [25] considered the leading enterprise's credit status and the relationships developed in the supply chain by assembling SVM and BP. Zhu et al [26] proposed a two-stage hybrid model by integrating the results of LR and ANN to boost the accuracy of the single model. Nevertheless, all methods mentioned above are heavily dependent on the annotated SME data tightly.…”

Section: Introductionmentioning

confidence: 99%

Multiview Graph Learning for Small‐ and Medium‐Sized Enterprises’ Credit Risk Assessment in Supply Chain Finance

Zhang

2021

Complexity

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In recent years, supply chain finance (SCF) is exploited to solve the financing difficulties of small- and medium-sized enterprises (SMEs). SME credit risk assessment is a critical part in the SCF system. The diffusion of SME credit risk may cause serious consequences, leading the whole supply chain finance system unstable and insecure. Compared with traditional credit risk assessment models, the supply chain relationship, credit condition of SME, and core enterprises should all be considered to rate SME credit risk in SCF. Traditional methods mix all indicators from different index systems. They cannot give a quantitative result on how these index systems work. Furthermore, traditional credit risk assessment models are heavily dependent on the number of annotated SME data. However, it is implausible to accumulate enough credit risky SMEs in advance. In this paper, we propose an adaptive heterogenous multiview graph learning method to tackle the small sample size problem for SMEs’ credit risk forecasting. Three graphs are constructed by using indicators from supply chain operation, SME financial indicator, and nonfinancial indicator individually. All the graphs are integrated in an adaptive manner, providing a quantitative explanation on how the three parts cooperate. The experimental analysis shows that the proposed method has good performance for determining whether SME is risky or nonrisky in SCF. From the perspective of SCF, SME financing ability is still the main factor to determine the credit risk of SME.

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“…Hui and Yun-Lin further refined the definition of supply chain finance and expressed it as the process of capital reallocation and cost optimization in the industry chain dominated by core enterprises [9]. Zhao et al believed that supply chain finance is a special means of payment [10]. In terms of the research on the development of supply chain financing mode, Huff and Rogers put forward the design idea of supply chain financing based on their own understanding and carried out the design of prepayment financing mode [11].…”

Section: Literature Reviewmentioning

confidence: 99%

Construction of Supply Chain Financial Risk Management Mode Based on Internet of Things

Wang

2019

IEEE Access

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The objective of this paper is to analyze the problems of information asymmetry, mode lag, and high operational risk between banks and enterprises in the practice of supply chain finance business. In this paper, first, the concept and function of supply chain finance were elaborated, and the theoretical basis of supply chain financial risk control was studied. The implement of principal agent, information asymmetry theory, and self-compensated trade finance theory on realizing the risk avoidance in the actual development process was analyzed. Then, the business processes of the three basic financing models of supply chain finance and the shortcomings in the operation of each model were proposed. On this basis, risk sources and influencing factors of supply chain finance were analyzed, and operational risks were emphasized. Finally, a new financing mode of inventory pledge was designed based on the special function of Internet of Things (IoT) technology and the business process of inventory financing mode. The results showed that there was a big gap in the value of risk loss caused by various types of loss events in the operation risk of supply chain finance inventory pledge financing mode; among them, the biggest losses were from external fraud. By comparing the expected loss (ES) value of inventory pledge financing mode based on the IoT with the operation risk of traditional mode, it could be found that the supply chain finance mode based on the IoT technology effectively reduced the operation risk. Therefore, the system designed in this paper has certain reference and practical significance for financial risk management.

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Predicting China’s SME Credit Risk in Supply Chain Finance Based on Machine Learning Methods

Cited by 36 publications

References 22 publications

Risk Assessment of the SME Sector Operations during the COVID-19 Pandemic

Risk Assessment of the SME Sector Operations during the COVID-19 Pandemic

Multiview Graph Learning for Small‐ and Medium‐Sized Enterprises’ Credit Risk Assessment in Supply Chain Finance

Construction of Supply Chain Financial Risk Management Mode Based on Internet of Things

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