1. Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM
- Author
-
Weiqiong Fu, Hanxiao Zhang, and Fu Huang
- Subjects
Optimization ,Computer and Information Sciences ,China ,Asia ,Support Vector Machine ,Neural Networks ,Economics ,Science ,Social Sciences ,Research and Analysis Methods ,Risk Assessment ,Machine Learning ,Geographical Locations ,Artificial Intelligence ,Support Vector Machines ,Computer Networks ,Research Errors ,Internet ,Multidisciplinary ,Commerce ,Biology and Life Sciences ,Research Assessment ,Public Finance ,Physical Sciences ,People and Places ,Money Supply and Banking ,Medicine ,Neural Networks, Computer ,Finance ,Mathematics ,Algorithms ,Research Article ,Neuroscience - Abstract
To better prevent the potential risks in Internet-based Supply Chain Financing (SCF) products, this paper optimizes and evaluates the Internet-based SCF-oriented Credit Risk Evaluation (CRE) method. Firstly, this paper summarizes 12 risk factors of SCF business, establishes a Risk Assessment Index System (RAIS) with good consistency and stability; then, the principles of Backpropagation (BP) Neural Network (NN) is expounded together with Support Vector Machines (SVM) and Genetic Algorithm (GA) model. Consequently, a CRE model is implemented by the NN tools in MATLAB based on the collection of multiple groups of SCF-oriented risk assessment samples. Subsequently, the assessment samples are trained and tested. Finally, the SCF-oriented CRE model is proposed and verified. The results show that the BP-GA model has presented high prediction consistency with the actual classification. According to the comparison of classification results of SVM, BP model, and BP-GA model, the classification accuracy of test samples of the proposed Internet-based SCF-oriented CRE system using BP-GA model reaches 97.19%; the Type I and Type II error rate of the CRE system based on BP-GA model is 7.2% and 14.21%, respectively. Therefore, a suitable SCF-oriented CRE method is put forward for China’s commercial banks along with scientific and feasible suggestions to manage SCF-oriented credit risks more reasonably and effectively.
- Published
- 2022