Application of innovative risk early warning mode under big data technology in Internet credit financial risk assessment

Article


Du, Guansan, Liu, Zixian and Lu, Haifeng. 2021. "Application of innovative risk early warning mode under big data technology in Internet credit financial risk assessment ." Journal of Computational and Applied Mathematics. 386. https://doi.org/10.1016/j.cam.2020.113260
Article Title

Application of innovative risk early warning mode under big data technology in Internet credit financial risk assessment

ERA Journal ID228
Article CategoryArticle
AuthorsDu, Guansan, Liu, Zixian and Lu, Haifeng
Journal TitleJournal of Computational and Applied Mathematics
Journal Citation386
Article Number113260
Number of Pages11
Year2021
PublisherElsevier
Place of PublicationNetherlands
ISSN0377-0427
Digital Object Identifier (DOI)https://doi.org/10.1016/j.cam.2020.113260
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S0377042720305513
Abstract

In the era of big data, it is aimed to use big data technology to form an effective early warning and prevention of Internet credit. The BP neural network algorithm is applied to determine the number of nodes, activation function, learning rate, and other parameters of each layer of the BP neural network. Also, many data samples are used to build an early warning model of Internet credit risk. The constructed model is trained and tested. Finally, the genetic algorithm (GA) is used to optimize the neural network to improve the accuracy of early warning. The results show that based on 450 data samples from 90 enterprises over five years and the risk interval divided by the ‘‘3σ’’ rule, the Internet credit risk level is initially determined. Then, the neural network is trained and tested. The network output rate is as high as 85%. To avoid the defect of the BP neural network falling into local extreme value, GA is used to optimize the neural network. The warning is more accurate, and the error is smaller. The accuracy rate can reach 97%. Therefore, the use of BP neural network for early warning and assessment of Internet credit risk has good accuracy and computing efficiency, which expands the application of BP neural network in the field of Internet finance, and provides a new development direction for the early warning and assessment of Internet credit risk.

KeywordsBig data technology; BP neural network; Internet credit; Risk early warning model
Related Output
Is part ofInternet Financial Risk Management Study
Public Notes

This article is part of a UniSQ Thesis by publication. See Related Output.

Files associated with this item cannot be displayed due to copyright restrictions.

Byline AffiliationsUniversity of Southern Queensland
Liaoning University, China
People’s Bank of China, China
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Related outputs

Correction to: Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network
Liu, Zixian, Du, Guansan, Zhou, Shuai, Lu, Haifeng and Ji, Han. 2024. "Correction to: Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network ." Computational Economics. https://doi.org/10.1007/s10614-024-10600-w
Internet Financial Risk Management Study
Du, Guansan. 2023. Internet Financial Risk Management Study. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z1wvx
Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network
Liu, Zixian, Du, Guansan, Zhou, Shuai, Lu, Haifeng and Ji, Han. 2022. "Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network." Computational Economics. 59 (4), pp. 1481-1499. https://doi.org/10.1007/s10614-021-10229-z