The credit analysis of transportation capacity supply chain finance based on core enterprise credit radiation

2021 ◽  
pp. 1-14
Author(s):  
Xu Lili ◽  
Liu Feng ◽  
Chu Xuejian
Keyword(s):  
Supply Chain ◽  
Financial Institutions ◽  
Profit Maximization ◽  
Credit Guarantee ◽  
The Core ◽  
Credit Line ◽  
Supply Chain Finance ◽  
Enterprise Credit ◽  
Transportation Capacity ◽  
Core Enterprise

This study examines the application of the business model of supply chain finance depending on the core enterprise, to the credit financing of transportation capacity enterprises. It studies the credit transmission characteristics regarding core enterprise credit radiation, presents the core enterprise credit segmentation and credit pricing, and transforms them into the calculation of credit guarantee and the default probability of core enterprises. Credit guarantee is regarded as a constraint of financial institutions’ credit decisions. Using probability density and logistic tools, we construct a profit maximization model for financial institutions and solve their optimal credit decision for a specific interest rate. Through numerical experiments, we verify the validity of the model and conclude that increasing the business volume between financing enterprises and core enterprises or reducing the probability of default can effectively improve financial institutions’ credit line.

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.

Immune System Research Based on the Core Enterprise of Supply Chain Finance

2012 ◽  
Vol 174-177 ◽  
pp. 2798-2801
Author(s):  
Rui Zhang ◽  
Guo Ping Cheng
Keyword(s):  
Supply Chain ◽  
Immune System ◽  
System Research ◽  
The Core ◽  
Supply Chain Finance ◽  
Biological Immune System ◽  
Core Enterprise

This paper first compares the mapping relationship between biological immune and risk immunization of the core enterprise in supply chain finance.And then it establishes the risk immune system of the core enterprise in supply chain finance by referencing the concept of biological immune system. The main innovation point of the paper is that it realizes the hyperlink between biological immune and risk immunization of core enterprise in supply chain finance.

scholarly journals Research on the Influence Mechanism of Block Chain on the Credit of Transportation Capacity Supply Chain Finance

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lili Xu ◽  
Yubin Yang ◽  
Xuejian Chu
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Credit Access ◽  
Credit Line ◽  
Influencing Mechanism ◽  
Supply Chain Finance ◽  
Transportation Finance ◽  
Supply Chain Financing ◽  
Transportation Capacity ◽  
Block Chain

This paper aims at the promotion of the application of inclusive financing into transportation capacity financing by combining transportation capacity supply chain with block chain technology as a brand-new financing topic. It focuses on the influencing mechanism by block chain on credit access, credit line, and credit supervision. From the perspective of “transportation” finance, the application of block chain in different scenarios is demonstrated after analyzing the attenuation process of credit transmission in the supply chain, the reviewing of two credit line evaluation methods of business self-compensation and credit guarantee, and the reviewing of regulatory requirements in transaction closed-loop, delivery closed-loop, and capital closed-loop; therefore the 3 major influencing mechanisms by block chain on the transportation capacity supply chain financing credit granting are discovered, indicating the effective improvement of financial institutions participation and better credit line for the financing of micro, medium, and small transportation enterprises (SMEs) by the application of block chain technology.

scholarly journals The Sustainable Development of Financial Topic Detection and Trend Prediction by Data Mining

2021 ◽  
Vol 13 (14) ◽  
pp. 7585
Author(s):  
Yunmei Liu ◽  
Shuai Zhang ◽  
Min Chen ◽  
Yenchun Wu ◽  
Zhengxian Chen
Keyword(s):  
Data Mining ◽  
Supply Chain ◽  
Financial Institutions ◽  
Clustering Algorithm ◽  
Development Trend ◽  
Research Field ◽  
Trend Prediction ◽  
Blockchain Technology ◽  
Supply Chain Finance ◽  
The Government

Blockchain technology is the most cutting-edge technology in the field of financial technology, which has attracted extensive attention from governments, financial institutions and investors of various countries. Blockchain and finance, as an interdisciplinary, cross-technology and cross-field topic, has certain limitations in both theory and application. Based on the bibliometrics data of Web of Science, this paper conducts data mining on 759 papers related to blockchain technology in the financial field by means of co-word analysis, bi-clustering algorithm and strategic coordinate analysis, so as to explore hot topics in this field and predict the future development trend. The experimental results found ten research topics in the field of blockchain combined with finance, including blockchain crowdfunding, Fintech, encryption currency, consensus mechanism, the Internet of Things, digital financial, medical insurance, supply chain finance, intelligent contract and financial innovation. Among them, blockchain crowdfunding, Fintech, encryption currency and supply chain finance are the key research directions in this research field. Finally, this paper also analyzes the opportunities and risks of blockchain development in the financial field and puts forward targeted suggestions for the government and financial institutions.

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 Supply chain finance

Bankarstvo ◽  
2020 ◽  
Vol 49 (4) ◽  
pp. 100-111
Author(s):  
Radmila Gaćeša
Keyword(s):  
Supply Chain ◽  
Financial Institutions ◽  
Technical Equipment ◽  
Financial Instruments ◽  
International Financial Institutions ◽  
Working Capital ◽  
Supply Chain Finance ◽  
Supply Channel ◽  
Supply Chain Financing ◽  
Trained Staff

Supply channel financing or reverse factoring can be defined as the use of financial instruments and technologies to optimize the management of working capital and liquidity, which are linked to the supply chain. This type of transaction includes the following participants: the supplier, the buyer and the factor as an intermediary. Given the available expertise, professionally trained staff, structured experience, technical equipment and some other functionalities, banks are, as factors, ideal participants in supply chain financing. The support provided by international financial institutions, some of which will be mentioned more specifically in the following text, can be a valuable opportunity to improve existing models, and to initiate new projects and install appropriate platforms, which would certainly benefit both clients and the banks themselves.

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