scholarly journals Research on the Risk Measurement Algorithm of Supply Chain Order Financing Based on Insurance Actuarial

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Gushuo Li ◽  
Menglin Yin
Keyword(s):  
Supply Chain ◽  
Financial Risk ◽  
Foreign Currency ◽  
Risk Measurement ◽  
Raw Material ◽  
Financial Risks ◽  
Efficient Operation ◽  
Supply Chain Finance ◽  
Chain Order ◽  
New Perspective

In today’s globalized economy, all the links of supply chain are interlinked. Most of the upstream raw material manufacturers or producers in the said chain are small- and medium-sized enterprises (SMEs) that provide the basis for the efficient operation of the whole supply chain. However, SMEs in China, especially those playing a pivotal role in China’s export-oriented economy at this stage, do not have access to the corresponding financial treatment. Supply chain finance provides a new perspective to solve this contradiction. Henceforth, this paper introduces modern financial engineering risk measurement tools to measure the financial risk in supply chain finance, specifically while evaluating the single financing business. Moreover, the chief objective of this paper will be the analysis of the characteristics and connotations of order financing business model. In addition, the focus will be to analyze the risk of order financing from the perspective of banks and other financial institutions. Additionally, this paper will use the CreditRisk + model based on insurance actuarial principles to manage credit risk in order financing business based on foreign currency settlement, in conjunction with the characteristics of supply chain finance and multinational supply chain. Furthermore, a risk measurement method for the application of order financing in multinational supply chains will be provided. Ultimately, the experiments show that the solution of this paper defines and analyzes the financial risks brought by order financing business to bank financing.

scholarly journals RESEARCH ON RISK MEASUREMENT OF SUPPLY CHAIN FINANCE BASED ON FRACTAL THEORY

Fractals ◽  
2020 ◽  
Vol 28 (08) ◽  
pp. 2040013
Author(s):  
XUN LIU ◽  
XIA PENG ◽  
MARTIN STUART
Keyword(s):  
Supply Chain ◽  
Financial Risk ◽  
Fractal Theory ◽  
Measurement Model ◽  
Risk Measurement ◽  
Random Structure ◽  
Supply Chain Finance ◽  
Volatility Model ◽  
Study Results ◽  
Capital Services

Supply chain finance is a new financing model tailored for small and medium-sized enterprises, which integrates capital flow into supply chain management, providing commercial trade capital services for enterprises in all aspects of the supply chain and providing new loan financing services for vulnerable enterprises in the supply chain. Fractal originally is a general term for a graph, structure or phenomenon that does not have a feature length but has a statistically significant self-similarity; fractal theory is an emerging edge science that describes the complex system with a random structure and has been widely used in physics, chemistry, geography, economics and many other fields. On the basis of summarizing and analyzing previous published literature works, this paper expounded the research situation and significance of risk measurement in supply chain finance, elaborated the development background, current status and future challenges of fractal theory, proposed the improved fractal volatility model and financial evaluation model, performed risk analysis of supply chain finance through evaluation modeling and elastic fractal dimension, constructed a financial risk measurement model based on fractal theory, and discussed the importance of model parameter estimation, residual test and accuracy examination in risk measurement of supply chain finance. The final empirical analysis shows that the improved fractal volatility model and the proposed financial risk measurement model has better risk measurement ability under different out-of-sample prediction periods, and obtain more accurate conclusion of asymmetry determination of financial assets gains under the common inspection level. The study results of this paper provide a reference for the further researches on risk measurement of supply chain finance based on fractal theory.

scholarly journals Supply Chain Financial Risk Evaluation of Small- and Medium-Sized Enterprises under Smart City

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Keyu Wang ◽  
Fuhai Yan ◽  
Yangjingjing Zhang ◽  
Yunlong Xiao ◽  
Lexi Gu
Keyword(s):  
Supply Chain ◽  
Financial Institutions ◽  
Smart City ◽  
Evaluation System ◽  
Financial Risk ◽  
Evaluation Model ◽  
Stable Operation ◽  
Financial Risks ◽  
Supply Chain Finance ◽  
Promethee Method

Prevention and control of risks are an eternal theme of financial institutions. Although, to some extent, the emergence of supply chain finance can enhance the financing capacity of small- and medium-sized enterprises (SMEs) and reduce financial risks of financial institutions, with the development of smart city and smart finance, the financial risks of SMEs are more complex, infectious, dormant, and difficult to accurately identify and measure. Facing this status, financial institutions have been required to understand and evaluate the financial risks of SMEs from a new perspective. Therefore, this paper, based on the study of financial risks assessment of SMEs under the smart city and smart finance, innovatively constructs a new index evaluation system for supply chain finance, based on improved hesitant fuzzy linguistic PROMETHEE method, and the effectiveness and advantages of the model have been verified through an example. To a certain degree, the SMEs financing the evaluation model and improved PROMETHEE method can not only help financial institutions reduce the risks in the specific financial transactions but also reduce the survival threat of financial institutions. Moreover, it is of positive significance to the stable operation of the financial system.

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 Research on Risk Measurement of Supply Chain Emergencies in International Capacity Cooperation

2019 ◽  
Vol 11 (19) ◽  
pp. 5184
Author(s):  
Bo-Rui Yan ◽  
Qian-Li Dong ◽  
Qian Li
Keyword(s):  
Supply Chain ◽  
Financial Risk ◽  
Fuzzy Ahp ◽  
Risk Index ◽  
Risk Measurement ◽  
Country Risk ◽  
Analytic Hierarchy ◽  
Analytic Hierarchy Process Method ◽  
Measurement Index System ◽  
Hierarchy Process

International capacity cooperation is easily affected by the interweaving of its internal and external environment. As the risk accumulation exceeds the threshold, a supply chain crisis and even emergency will occur and serious losses will be caused. Regarding multinational operation and international capacity cooperation, 208 cases were summarized to identify risk types and high-incidence areas, and a risk measurement index system was established. A Fuzzy AHP (Analytic Hierarchy Process) method was used to evaluate the importance of each risk index. It was found that country risk was the main cause of supply chain emergencies in international capacity cooperation. Construction, water and electricity supply, mining and manufacturing were major areas of emergencies. In international capacity cooperation, country risk and cross-cultural risk were more important in external risks, while in internal risk, financial risk and decision risk were more important.

scholarly journals Application of Blockchain Technology in Supply Chain Finance of Beibu Gulf Region

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
RenLan Wang ◽  
Yanhong Wu
Keyword(s):  
Supply Chain ◽  
Financial Risk ◽  
Chain Structure ◽  
Beibu Gulf ◽  
Application Research ◽  
Gulf Region ◽  
Processing Efficiency ◽  
Blockchain Technology ◽  
Supply Chain Finance ◽  
A Chain

Blockchain technology is a database that is operated by multiple parts and forms a chain structure through hash index. The blockchain uses multiple nodes and distributes multiple accesses to data, thereby reducing the dependence on the central Internet server and avoiding the possibility of damage to the central server point due to data and data loss. Encryption technology is used to ensure its integrity and ensure that the data files stored in the blockchain are not tampered with or deleted maliciously. Blockchain technology has inherent advantages in supply chain finance with its technical attributes such as nontampering, distributed ledger, and traceability and has great potential to build trust to solve the main problems of supply chain finance, which is conducive to promoting financial development in the Beibu Gulf region. This article mainly introduces the application research of blockchain technology in supply chain finance in the Beibu Gulf region and intends to provide some ideas for the development of supply chain finance in the Beibu Gulf region combined with blockchain technology. This article proposes the application research methods of blockchain technology in supply chain finance in the Beibu Gulf region, including blockchain technology, supply chain financial risk evaluation on the blockchain, and supply chain finance game for relevant experiments. The experimental results of this article show that the average processing time of the algorithm of the designed blockchain supply chain financial system is 4.10 seconds, the algorithm processing efficiency is faster, and the relevant risks can be better assessed.

Supply chain finance is not for everyone

2020 ◽  
Vol 50 (9/10) ◽  
pp. 775-807
Author(s):  
Viktor Hugo Elliot ◽  
Christiaan De Goeij ◽  
Luca Mattia Gelsomino ◽  
Johan Woxenius
Keyword(s):  
Supply Chain ◽  
Service Providers ◽  
Value Added ◽  
Case Study Methodology ◽  
Content Type ◽  
Operational Conditions ◽  
Supply Chain Finance ◽  
Transit Times ◽  
Resources And Capabilities ◽  
New Perspective

PurposeLogistics service providers (LSPs) have unique resources and capabilities that position them to deliver supply chain finance (SCF) solutions. The study aims to discuss and illustrate the necessary resources and process of value creation and capture of LSPs, potentially offering SCF solutions.Design/methodology/approachRelying on a theoretical framework, combining a resource-based view (RBV) with the literature on SCF, the authors apply an abductive case study methodology, including 11 interviews with representatives from four LSPs.FindingsThe main findings are as follow: (1) although an LSP has sufficient resources for value-added SCF solutions, it may not capture enough value to motivate realising them; (2) an LSP considering offering SCF should account for the interaction between its resources and cargo transit times, risk and regulatory restrictions and (3) future studies should distinguish between financing the logistics services and the moved products.Research limitations/implicationsThe authors contribute to the growing field of SCF research by analysing motives and barriers for LSPs to offer SCF service to their customers. Because none of our case companies decided to move beyond experimentation further research is needed on the resources and capabilities needed for LSPs to successfully venture into SCF.Practical implicationsThe study provides LSPs with clear indications of the difficulties involved when contemplating a move into SCF solutions and discusses the potential value of offering such services.Originality/valueDespite evidence of LSPs engaging in SCF in various industries, academic contributions do not go beyond operational conditions or quantification of benefits. The authors add evidence on how LSPs are currently evaluating the prominence of adding SCF to their value offerings, including a new perspective on resources, value generation and capture mechanisms.

Regression analysis of supply chain financial risk based on machine learning and fuzzy decision model

2020 ◽  
pp. 1-11
Author(s):  
Fan Xuan
Keyword(s):  
Supply Chain ◽  
Financial Institutions ◽  
Financial Services ◽  
Index System ◽  
Financial Risk ◽  
Control Measures ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Supply Chain Finance ◽  
Strong Control

Supply chain financial risk control has become the biggest obstacle restricting financial institutions from developing supply chain financial services. If financial institutions want to make a difference in the supply chain finance business, they need to implement strong control measures against supply chain finance risks. Based on the research of supply chain finance and risk related theories, this paper uses fuzzy preference relations and selects the main risk criteria to construct a risk evaluation index system. Moreover, this paper takes the development of J company’s supply chain finance business as a background to conduct an empirical analysis and proposes the risk management measures and development strategies of J company’s actual supply chain finance business. The combination of quantitative analysis and qualitative evaluation is more comprehensive and operational value for the research and management of supply chain financial risks. In addition, this paper uses the evaluation index system constructed in this paper to conduct a more comprehensive summary and analysis of the internal and external environment of risk influencing factors. The research results show that the performance of the model constructed in this paper is good.

scholarly journals Evolutionary Game Analysis of Blockchain Technology Preventing Supply Chain Financial Risks

2021 ◽  
Vol 16 (7) ◽  
pp. 2824-2842
Author(s):  
Rui Sun ◽  
Dayi He ◽  
Huilin Su
Keyword(s):  
Supply Chain ◽  
Credit Risk ◽  
Financial Institutions ◽  
Evolutionary Game ◽  
Decisive Role ◽  
Financial Risks ◽  
Factors Affecting ◽  
Blockchain Technology ◽  
Supply Chain Finance ◽  
Before And After

Because of the risks existing in supply chain finance, taking accounts receivable factoring business as the research object, this paper uses the evolutionary game method to analyzes the factors affecting the decision-making of the participants in supply chain finance, constructs an evolutionary game model between small and medium-sized enterprises and financial institutions, and analyzes the mechanism of blockchain to solve the financial risks of the supply chain by comparing the changes of evolutionary stability strategies before and after the introduction of blockchain technology. This paper aims to reduce financing risks by analyzing the mechanism of blockchain technology in supply chain finance. It is found that, firstly, blockchain technology can reduce the credit risk of financial institutions and solve financing problem. Credit risk plays a decisive role in whether financial institutions accept financing business decisions. Blockchain technology can reduce the operational risk of financial institutions and improve the business income of financial institutions. Secondly, the strict regulatory environment formed by blockchain technology makes the default behavior of small and medium-sized enterprises and core enterprises in a high-risk state at all times. No matter the profit distribution proportion that small and medium-sized enterprises can obtain through collusion, they will not choose to default, which effectively solves the paradox that small and medium-sized enterprises cannot obtain loans from financial institutions despite the increased probability of compliance. Then, the evolutionary game between financial institutions and small and medium-sized enterprises is balanced in that financial institutions accept business applications, small and medium-sized enterprises abide by the contract, and the convergence effect is better. Therefore, blockchain technology not only reduces the financing risk of financial institutions but also helps to solve the financing problems of small and medium-sized enterprises.

scholarly journals The impacts of supply chain finance initiatives on firm risk: evidence from service providers listed in the US

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hugo K.S. Lam ◽  
Yuanzhu Zhan
Keyword(s):  
Supply Chain ◽  
Multinational Corporations ◽  
Financial Risk ◽  
Service Providers ◽  
The United States ◽  
Political Connections ◽  
Firm Capabilities ◽  
Content Type ◽  
It Capability ◽  
Supply Chain Finance

PurposeThis study empirically investigates how supply chain finance (SCF) initiatives together with different firm capabilities and resources (i.e. information technology (IT) capability, operational slack and political connections) affect the financial risk of service providers.Design/methodology/approachThis study collects secondary longitudinal data to test for a direct impact of SCF initiatives on service providers' financial risk. It further investigates the moderating effects of the service provider's IT capability, operational slack and political connections. Additional tests and analytical strategies are performed to ensure the robustness of the results.FindingsThe findings indicate that SCF initiatives help service providers mitigate financial risk. The risk reduction is greater for service providers with higher IT capability, operational slack and political connections, but the last factor applies only to multinational corporations, not domestic companies.Research limitations/implicationsThe data used in this research is limited to SCF service providers publicly listed in the United States, which may restrict the generalisability of the findings. Nonetheless, the research urges scholars to focus more on the financial risk implications of SCF in different market contexts.Practical implicationsThis study encourages service providers to embrace the power of SCF initiatives for mitigating financial risk and allows them to evaluate their SCF investments in light of different firm capabilities and resources.Originality/valueThis is the first study investigating the impacts of SCF initiatives and various firm capabilities and resources on service providers' financial risk. The empirical findings provide important implications for future research and practices.

scholarly journals Research on Supply Chain Financial Risks and Preventive Measures in the Era of Big Data

2020 ◽  
Vol 214 ◽  
pp. 03032
Author(s):  
Weiting Sun ◽  
Puxue Shen
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Financial Institutions ◽  
Financial Risk ◽  
Large Scale ◽  
Theory And Practice ◽  
Privacy And Security ◽  
Internet Applications ◽  
Supply Chain Finance ◽  
Big Data Technology

The emergence of supply chain finance has reduced the financing costs of SMEs. Due to the development of a diversified supply chain financial subject platform, there is a lack of risk control in terms of theory and practice. Big data is generated in Internet applications and combined with information technology to form big data technology. It can provide financial institutions with large-scale data analysis methods and can effectively improve the efficiency and ability of financial institutions to serve supply chain members. However, big data has some problems, such as higher processing cost, lower authenticity, and difficulty in effectively protecting the privacy and security of users. There are many problems with this new development model. This article focuses on the risk problems faced by supply chain finance. It discusses the use of big data technology to effectively solve the supply chain financial risk problems, and gives some measures that can be effectively solved for how to effectively avoid these risk factors. By effectively solving the financial risk problem in the era of big data, it provides guarantee for the benign development of enterprises, and provides a certain reference for researchers engaged in related fields and workers in this field.

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