Application of genetic algorithm and BP neural network in supply chain finance under information sharing

https://doi.org/10.1016/j.cam.2020.113170Get rights and content

Abstract

The supply chain finance industry will generate the flow of funds and commodities when providing financing services to small and medium-sized enterprises (SMEs). At this time, banks will face multiple risks such as policy, operation, market and credit. The investigation on supply chain finance under information sharing from the aspect of credit risk assessment will be conducted. The genetic algorithm combined with support vector machine and BP neural network is selected to evaluate the credit risk of supply chain finance. In the support vector machine method, the parameter selection method adopts genetic algorithm. In the included data, the gap in growth capacity of SMEs is relatively large. The standard deviations of main business, net profit and total assets are all above 30%, and the standard deviations of current ratio and quick ratio are small, which means that the two are more stable and healthier. In addition, among all the investigated enterprises, the cost gap is large, and the standard deviation of the inventory decline price reserve is small, which means that most enterprises have good inventory quality. After classification, 32 high-quality enterprises, 46 neutral enterprises and 55 risk enterprises are obtained in the total sample. In the test sample, there are 21 high-quality enterprises, 12 neutral enterprises, and 26 risk enterprises. The overall classification accuracy of the support vector machine method optimized by genetic algorithm is relatively lower than that of the BP neural network method. The classification accuracy of the support vector machine method optimized by genetic algorithm is 76.27%, and the classification accuracy of BP neural network method is 89.83%. The supply chain financial risk assessment of SMEs is mainly explored from the perspective of banks. The results can provide theoretical support for reducing the probability of bank’s profit damage and increasing the bank’s profitability.

Introduction

Supply chain finance, to put it simply, is a financing mode in which banks link core enterprises with upstream and downstream enterprises to provide flexible use of financial products and services [1], [2], [3]. That is to use funds as a solvent in the supply chain to increase its liquidity. Generally speaking, the supply chain of a specific commodity ranges from the purchase of raw materials to the production of intermediate and final products. Finally, the sales network delivers the products to consumers. The suppliers, manufacturers, distributors, retailers, and end users are connected into a whole [4], [5]. In this supply chain, core enterprises with strong competitiveness and large scale are in a strong position. They often have strict requirements on upstream and downstream supporting enterprises in terms of delivery, price, and account terms, which has caused tremendous pressure on these enterprises [6]. The upstream and downstream supporting enterprises are mostly small and medium-sized enterprises (SMEs). It is difficult for these enterprises to raise funds from banks. As a result, the capital chain is tight and the entire supply chain is out of balance. The biggest feature of “supply chain finance” is to find a large core enterprise in the supply chain, and use the core enterprise as the starting point to provide financial support for the supply chain. On the one hand, the funds are effectively injected into the relatively weak upstream and downstream supporting SMEs to solve the problems of financing difficulties and supply chain imbalances. On the other hand, the bank credit is integrated into the purchase and sale of upstream and downstream enterprises to enhance their commercial credit. Then, it promotes the establishment of long-term strategic synergy between SMEs with core enterprises, enhancing the competitiveness of the supply chain [7]. To support the benign relationship between SMEs and banks, the credit risk assessment of the supply chain is required. Moreover, the assessment indicators also need to be adjusted in a large amount and in real time. The investigation on supply chain finance under information sharing from the aspect of credit risk assessment will be conducted.

Information sharing is the sharing of information between supply chains. The higher the degree of information sharing, the closer cooperation between upstream and downstream of the supply chain or between enterprises [8]. Thereby, it is more beneficial to improve the performance of the supply chain and optimize the management of the supply chain. Ultimately, it enables both parties to share information to obtain the most optimal benefits [9]. As the growth mode of SMEs changes from endogenous to networked, the investigation on enterprise behavior also extends from internal to external networks. Theoretical analysis believes that the network embedding behavior of SMEs can alleviate the constraints of their credit financing through the information sharing mechanism. The efficiency of information sharing depends on the technological development of information systems and the improvement of transmission technology [10]. It must be implemented strictly under the conditions of information security and confidentiality. The degree of information sharing is different in different countries. The lack of information sharing has greatly hindered the cooperation in terms of work and data requirements in scientific research between various departments and industries.

The investigation on supply chain finance is conducted under the background of information sharing. The financing mode of supply chain finance is analyzed to obtain the risk assessment model of supply chain finance.

Section snippets

Literature review

If the trusted enterprises default, it will cause the banks to lose money. The good operation of trusted enterprises also generates good profits for banks. Therefore, for banks, taking risks is a necessary premise for profit. Thus, in the supply chain financial business, the correct control of credit risk is greatly significant to banks. Scholars from various countries have conducted detailed investigations on supply chain finance.

Chen et al. (2020) explored the supply chain financial platform

Financing mode of supply chain finance

Vulnerable member enterprises in the supply chain usually have to supply to core enterprises and bear the delay of accounts receivable. Or they may pay funds in advance to the core enterprises in the form of shop spreads and deposits before the sale begins [17], [18]. Many upstream and downstream enterprises in the supply chain believe that “capital pressure” is the biggest pressure they encounter in supply chain cooperation. The upstream and downstream enterprises in the supply chain shares

Descriptive statistical results of various financial indicators

Descriptive statistics of various financial indicators are conducted and the results are shown in Fig. 4.

It can be seen from Fig. 4 that among the included data, the gap in growth capacity of SMEs is relatively large. The standard deviations of main business, net profit and total assets are all above 30%, and the standard deviations of current ratio and quick ratio are small, which means that the two are more stable and healthier. In addition, among all the investigated enterprises, the cost

Discussion

At present, China is in a critical period of economic transformation, and the environment of the supply chain has undergone major changes. Also, the economic situation and financial situation fluctuate seriously. To support the benign relationship between the real economy and banks, the credit risk assessment of the supply chain is required. Assessment indicators also need to be adjusted in a large amount and in real time with the times [42], [43]. Due to the current development of the Internet

Conclusions

At present, with the development of the Internet industry, all industries are in contact with the Internet industry, including finance and supply chain finance. Therefore, according to the above factors, banks should also make more targeted index adjustments. The SMEs in the automotive industry are taken as the research object to analyze the characteristics of supply chain finance and financing modes. The credit risk assessment system of the supply chain finance and assessment indicators are

Acknowledgments

This work was supported by the Zhejiang Provincial Philosophy and Social Science Planning Project, the Hangzhou Philosophy and Social Science Planning Project under Grant Z20YD020, and the Visiting Scholar Program of Zhejiang Provincial Department of Education under Grant FX2019081.

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