scholarly journals Credit Risk Analysis and Evaluation of Internet Supply Chain Finance Listed Companies -- Based on Structural Entropy Weight TOPSIS Method

2021 ◽  
Author(s):  
Xudong Cai ◽  
Hongmei Zhang
Keyword(s):  
Supply Chain ◽  
Risk Analysis ◽  
Credit Risk ◽  
Listed Companies ◽  
Topsis Method ◽  
Entropy Weight ◽  
Analysis And Evaluation ◽  
Supply Chain Finance ◽  
Structural Entropy ◽  
Credit Risk Analysis

scholarly journals Credit Risk Assessment of e-Commerce Supply Chain Finance of SMEs Based on Dynamic Reward and Punishment Perspective

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Baitong Chen ◽  
Xinzhong Bao ◽  
Kun Xu
Keyword(s):  
Supply Chain ◽  
Credit Risk ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Development Trend ◽  
Topsis Method ◽  
Research Subjects ◽  
Supply Chain Finance ◽  
Dynamic Perspective ◽  
Rewards And Punishment

In view of problems such as lack of dynamism, limited research subjects, and lack of future development trends in previous studies, the paper takes small and microenterprises (SMEs) as research objects under the background of e-commerce supply chain finance. Based on the perspective of dynamic rewards and punishments, credit rewards and punishment value and time weights are embedded in the static evaluation results obtained by the traditional TOPSIS method. The Grey relative analysis method is used to reflect the development trend of enterprises’ credit and to build the traditional TOPSIS model and the credit risk evaluation model of e-commerce supply chain finance of SMEs by the improved TOPSIS method based on the dynamic perspective of rewards and punishments. Finally, the model is applied to SMEs credit risk evaluation of e-commerce supply chain finance to verify the feasibility and rationality of the model.

scholarly journals Hydrological Layered Dialysis Research on Supply Chain Financial Risk Prediction under Big Data Scenario

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Jia Liu ◽  
Shiyong Li ◽  
Xiaoxia Zhu
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Risk Analysis ◽  
Risk Prediction ◽  
Financial Institutions ◽  
Surface Runoff ◽  
Financial Risk ◽  
Supply Chain Finance ◽  
Runoff Model

In recent years, internet development provides new channels and opportunities for small- and middle-sized enterprises’ (SMEs) financing. Supply chain finance is a hot topic in theoretical and practical circles. Financial institutions transform materialized capital flows into online data under big data scenario, which provides networked, precise, and computerized financial services for SMEs in the supply chain. By drawing on the risk management theory in economics and the distributed hydrological model in hydrology, this paper presents a supply chain financial risk prediction method under big data. First, we build a “hydrological database” used for the risk analysis of supply chain financing under big data. Second, we construct the risk identification models of “water circle model,” “surface runoff model,” and “underground runoff model” and carry on the risk prediction from the overall level (water circle). Finally, we launch the supply chain financial risk analysis from breadth level (surface runoff) and depth level (underground runoff); moreover, we integrate the analysis results and make financial decisions. The results can enrich the research on risk management of supply chain finance and provide feasible and effective risk prediction methods and suggestions for financial institutions.

scholarly journals Financial Credit Risk Evaluation Based on Core Enterprise Supply Chains

2018 ◽  
Vol 10 (10) ◽  
pp. 3699 ◽  
Author(s):  
WeiMing Mou ◽  
Wing-Keung Wong ◽  
Michael McAleer
Keyword(s):  
Supply Chain ◽  
Credit Risk ◽  
Supply Chains ◽  
Risk Evaluation ◽  
Operating Conditions ◽  
The Core ◽  
Supply Chain Finance ◽  
Enterprise Credit ◽  
Financial Credit ◽  
Core Enterprise

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.

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