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Analysis of Regional Financial Risk in Guangdong Province Based on the DCN Deep Learning Model

In the free flow of financial factors oriented to capital, returns will be accompanied by the concentration and diffusion of financial resources to form regional financial spatial differences, which is an objective phenomenon of regional financial practice. Localized regional financial risks may app...

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Autor principal: Yuan, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328980/
https://www.ncbi.nlm.nih.gov/pubmed/35909857
http://dx.doi.org/10.1155/2022/9274737
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author Yuan, Yan
author_facet Yuan, Yan
author_sort Yuan, Yan
collection PubMed
description In the free flow of financial factors oriented to capital, returns will be accompanied by the concentration and diffusion of financial resources to form regional financial spatial differences, which is an objective phenomenon of regional financial practice. Localized regional financial risks may appear in the process of regional financial practice in each region. To address the abovementioned problems, we propose a model for regional financial risk analysis based on the DCN deep learning model. The main contents are as follows: elaborating the financial risk transmission mechanism involving intra- and interregional financial risks, sorting out the relationship between sectors as clues; the designing process of regional financial risk index as well as the measurement method, and the regional financial risk index for typical regions is measured and found to be at peak in 2017 with a risk index of 0.58; and the construction of an early warning model based on the value of the regional financial risk index and the expansion of the RNN network applied to the construction of the regional financial risk early warning system. Based on the construction of the RNN network application risk early warning system, the three types of risks, payment risk, loan loss risk, and market risk with the percentages of 49.62%, 26.82%, and 23.56%, respectively, are derived, and the focus is on their supervision and management in the follow-up work.
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spelling pubmed-93289802022-07-28 Analysis of Regional Financial Risk in Guangdong Province Based on the DCN Deep Learning Model Yuan, Yan Comput Intell Neurosci Research Article In the free flow of financial factors oriented to capital, returns will be accompanied by the concentration and diffusion of financial resources to form regional financial spatial differences, which is an objective phenomenon of regional financial practice. Localized regional financial risks may appear in the process of regional financial practice in each region. To address the abovementioned problems, we propose a model for regional financial risk analysis based on the DCN deep learning model. The main contents are as follows: elaborating the financial risk transmission mechanism involving intra- and interregional financial risks, sorting out the relationship between sectors as clues; the designing process of regional financial risk index as well as the measurement method, and the regional financial risk index for typical regions is measured and found to be at peak in 2017 with a risk index of 0.58; and the construction of an early warning model based on the value of the regional financial risk index and the expansion of the RNN network applied to the construction of the regional financial risk early warning system. Based on the construction of the RNN network application risk early warning system, the three types of risks, payment risk, loan loss risk, and market risk with the percentages of 49.62%, 26.82%, and 23.56%, respectively, are derived, and the focus is on their supervision and management in the follow-up work. Hindawi 2022-07-20 /pmc/articles/PMC9328980/ /pubmed/35909857 http://dx.doi.org/10.1155/2022/9274737 Text en Copyright © 2022 Yan Yuan. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yuan, Yan
Analysis of Regional Financial Risk in Guangdong Province Based on the DCN Deep Learning Model
title Analysis of Regional Financial Risk in Guangdong Province Based on the DCN Deep Learning Model
title_full Analysis of Regional Financial Risk in Guangdong Province Based on the DCN Deep Learning Model
title_fullStr Analysis of Regional Financial Risk in Guangdong Province Based on the DCN Deep Learning Model
title_full_unstemmed Analysis of Regional Financial Risk in Guangdong Province Based on the DCN Deep Learning Model
title_short Analysis of Regional Financial Risk in Guangdong Province Based on the DCN Deep Learning Model
title_sort analysis of regional financial risk in guangdong province based on the dcn deep learning model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328980/
https://www.ncbi.nlm.nih.gov/pubmed/35909857
http://dx.doi.org/10.1155/2022/9274737
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