Credit risk identification of high-risk online lending enterprises based on neural network model
The rapid development of online lending alleviates the difficulty of financing for small and micro enterprises to a certain extent,but it also exposes the credit risk identification problem of online lending platform.In order to fully identify the characteristics of high-risk network lending enterpr...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
POSTS&TELECOM PRESS Co., LTD
2017-12-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2017.00222 |
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| Summary: | The rapid development of online lending alleviates the difficulty of financing for small and micro enterprises to a certain extent,but it also exposes the credit risk identification problem of online lending platform.In order to fully identify the characteristics of high-risk network lending enterprises,small and medium-sized network lending companies were selected as samples,and indicators that were highly correlated with risk identification were chosen as indicators variables.And by using the BP neural network algorithm model,the credit risk identification rate and credit risk classification accuracy rate of high risk network lending enterprises,under different conditions,were obtained.The results show that the credit risks of high-risk network lending enterprises are highly recognized,and have the characteristics of high recall rate and high accuracy. |
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| ISSN: | 2096-109X |