scholarly journals The Research of Third-party B2B Supply Chain Finance Credit Risk Identification & Evaluation System

Author(s):  
Bao-sen WANG ◽  
Zi-jin WANG ◽  
Rui WEI
2017 ◽  
Vol 7 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Daniela Marasova ◽  
Miriam Andrejiova ◽  
Anna Grincova

AbstractRisk management facilitates risk identification, evaluation, control, and by means of appropriate set of measures, risk reduction or complete elimination. Therefore, the risk management becomes a strategic factor for a company’s success. Properly implemented risk management system does not represent a tool to avoid the risk; it is used to understand the risk and provide the bases for strategic decision-making.Risk management represents a key factor for the supply chain operations. Managing the risks is crucial for achieving the customer satisfaction and thus also a company’s success. The subject-matter of the article is the assessment of the supply chain in the automobile industry, in terms of risks. The topicality of this problem is even higher, as after the economic crisis it is necessary to revaluate the readiness of the supply chain for prospective risk conditions. One advantage of this article is the use of the Saaty method as a tool for the risk management within the supply chain.


2018 ◽  
Vol 10 (10) ◽  
pp. 3699 ◽  
Author(s):  
WeiMing Mou ◽  
Wing-Keung Wong ◽  
Michael McAleer

Supply chain finance has broken through traditional credit modes and advanced rapidly as a creative financial business discipline. Core enterprises have played a critical role in the credit enhancement of supply chain finance. Through the analysis of core enterprise credit risks in supply chain finance, by means of a ‘fuzzy analytical hierarchy process’ (FAHP), the paper constructs a supply chain financial credit risk evaluation system, making quantitative measurements and evaluation of core enterprise credit risk. This enables enterprises to take measures to control credit risk, thereby promoting the healthy development of supply chain finance. The examination of core enterprise supply chains suggests that a unified information file should be collected based on the core enterprise, including the operating conditions, asset status, industry status, credit record, effective information to the database, collecting related data upstream and downstream of the archives around the core enterprise, developing a data information system, electronic data information, and updating the database accurately using the latest information that might be available. Moreover, supply chain finance and modern information technology should be integrated to establish the sharing of information resources and realize the exchange of information flows, capital flows, and logistics between banks. This should reduce a variety of risks and improve the efficiency and effectiveness of supply chain finance.


2021 ◽  
Vol 275 ◽  
pp. 01061
Author(s):  
Zeping Tong ◽  
Shuo Yang

Agriculture is a basic industry that supports the construction and development of the national economy and plays an important role in promoting rural revitalization. And in the current post-COVID-19 era, agricultural SMEs have difficulty in obtaining the favours of financial institutions in normal lending due to their weak credit guarantee capabilities and high credit management costs. Difficulty in financing has become a bottleneck problem that plagues the development of enterprises and restricts the development of agricultural modernization. How to evaluate and control its credit risk is not only a major way to solve the financing difficulties of agricultural SMEs, but also the basis for the stable development of supply chain financial services. This paper analyzes three typical financing modes of agricultural SMEs from the perspective of supply chain finance, and takes the agricultural SMEs in the New OTC Market as an example to construct a Logistic model, and uses factor analysis to effectively predict the credit risk of supply chain finance. The results show that the operational efficiency factors, growth factors and related core corporate profitability of agricultural SMEs financing enterprises significantly affect their credit risk. After testing, the model is highly accurate in predicting the financing risks of agricultural SMEs.


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