Menghui Chu, Shuyao Wu, Yalin Wei
Information Department, Shandong University of Science and Technology, Jinan, Shandong 250031, China
The BP neural network model is used to predict the credit records of enterprises without credit records, and the training data set is the relevant data of 123 enterprises with credit records in Appendix 1. Then, on the basis of question 1, it is given that the total annual credit is 100 million yuan, so the loan amount allocated to each enterprise can be calculated directly from the total credit amount and the enterprise credit line ratio. Taking the epidemic situation of COVID-19 as a sudden factor, it is also necessary to classify the industries and categories to which the enterprises belong. In quantifying and reflecting the impact of COVID-19 's epidemic situation on enterprises, we first investigated and quantified the data of different degrees of impact of the epidemic on enterprises of various industries and different sizes, and then quantified the data of different degrees into epidemic impact indicators by using fuzzy comprehensive evaluation method. Take the epidemic impact index, credit risk, enterprise type and output amount as indicators to make a fuzzy comprehensive evaluation to determine the comprehensive risk and adjust the credit strategy.
Fuzzy comprehensive evaluation model, BP neural network model, Optimization model
Menghui Chu, Shuyao Wu, Yalin Wei. Credit decision based on BP neural network. Academic Journal of Business & Management (2021) Vol. 3, Issue 5: 47-50. https://doi.org/10.25236/AJBM.2021.030508.
 Si Shoukui, Mathematical Modeling algorithm and Application textbook, Electronic version [DB], 350, 357
 Zhan Yongzhi, A study on bilateral interest rate pricing of supply chain finance platform [C], 2018-05-20, 22~41
 Huang Jing, Quantitative Research of Bank Credit Risk Based on Fuzzy AHP [C], Business Management, 2007, 22~41