Open AccessGreen Credit Risk Assessment under the Background of Water Ecological Civilization City Construction——Based on BP Neural Network Model
Author(s) -
Xin Fan,
Qingguo Li,
Zhao Xu
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/446/3/032076
Subject(s) - ecological civilization , business , construct (python library) , credit risk , artificial neural network , analytic hierarchy process , china , finance , environmental resource management , computer science , engineering , environmental science , geography , operations research , artificial intelligence , archaeology , programming language
The construction of water ecological civilized cities requires a large amount of capital, but at the same time, the project itself has certain risks. Commercial banks are not only the main providers of credit funds, but also the main bearers of project risks. Strengthening the credit risk management of water ecological civilized urban construction projects and enhancing the financial support of commercial banks for water ecological civilized urban construction projects have become the key to further promoting the construction of water ecological civilized cities. At present, the credit risk assessment of commercial banks in China is based on traditional methods, and it is difficult to achieve the desired effect. This paper applies the AHP method to construct the credit risk index system of water conservancy projects, and establishes a credit risk assessment model through BP neural network technology. Finally, it combines 39 listed companies. The data is empirically analyzed for the model to verify the accuracy of the predictions.