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Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM

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 S...

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Detalles Bibliográficos
Autores principales: Fu, Weiqiong, Zhang, Hanxiao, Huang, Fu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782329/
https://www.ncbi.nlm.nih.gov/pubmed/35061798
http://dx.doi.org/10.1371/journal.pone.0262222
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author Fu, Weiqiong
Zhang, Hanxiao
Huang, Fu
author_facet Fu, Weiqiong
Zhang, Hanxiao
Huang, Fu
author_sort Fu, Weiqiong
collection PubMed
description 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.
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spelling pubmed-87823292022-01-22 Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM Fu, Weiqiong Zhang, Hanxiao Huang, Fu PLoS One Research Article 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. Public Library of Science 2022-01-21 /pmc/articles/PMC8782329/ /pubmed/35061798 http://dx.doi.org/10.1371/journal.pone.0262222 Text en © 2022 Fu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Fu, Weiqiong
Zhang, Hanxiao
Huang, Fu
Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM
title Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM
title_full Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM
title_fullStr Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM
title_full_unstemmed Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM
title_short Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM
title_sort internet-based supply chain financing-oriented risk assessment using bp neural network and svm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8782329/
https://www.ncbi.nlm.nih.gov/pubmed/35061798
http://dx.doi.org/10.1371/journal.pone.0262222
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