Improved AHP Model and Neural Network for Consumer Finance Credit Risk Assessment
With the rapid expansion of the consumer financial market, the credit risk problem in borrowing has become increasingly prominent. Based on the analytic hierarchy process (AHP) and the long short-term memory (LSTM) model, this paper evaluates individual credit risk through the improved AHP and the o...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Multimedia |
| Online Access: | http://dx.doi.org/10.1155/2022/9588486 |
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| _version_ | 1832558405010587648 |
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| author | Yafeng Xi Qiu Li |
| author_facet | Yafeng Xi Qiu Li |
| author_sort | Yafeng Xi |
| collection | DOAJ |
| description | With the rapid expansion of the consumer financial market, the credit risk problem in borrowing has become increasingly prominent. Based on the analytic hierarchy process (AHP) and the long short-term memory (LSTM) model, this paper evaluates individual credit risk through the improved AHP and the optimized LSTM model. Firstly, the characteristic information is extracted, and the financial credit risk assessment index system structure is established. The data are input into the AHP-LSTM neural network, and the index data are fused with the AHP so as to obtain the risk level and serve as the expected output of the LSTM neural network. The results of the prewarning model after training can be used for financial credit risk assessment and prewarning. Based on LendingClub and PPDAI data sets, the experiment uses the AHP-LSTM model to classify and predict and compares it with other classification methods. Experimental results show that the performance of this method is superior to other comparison methods in both data sets, especially in the case of unbalanced data sets. |
| format | Article |
| id | doaj-art-a785a5d774054fa1b9c905618239a396 |
| institution | Kabale University |
| issn | 1687-5699 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Multimedia |
| spelling | doaj-art-a785a5d774054fa1b9c905618239a3962025-02-03T01:32:27ZengWileyAdvances in Multimedia1687-56992022-01-01202210.1155/2022/9588486Improved AHP Model and Neural Network for Consumer Finance Credit Risk AssessmentYafeng Xi0Qiu Li1Shijia Zhuang University of Applied TechnologyTraining Central of China Post GroupWith the rapid expansion of the consumer financial market, the credit risk problem in borrowing has become increasingly prominent. Based on the analytic hierarchy process (AHP) and the long short-term memory (LSTM) model, this paper evaluates individual credit risk through the improved AHP and the optimized LSTM model. Firstly, the characteristic information is extracted, and the financial credit risk assessment index system structure is established. The data are input into the AHP-LSTM neural network, and the index data are fused with the AHP so as to obtain the risk level and serve as the expected output of the LSTM neural network. The results of the prewarning model after training can be used for financial credit risk assessment and prewarning. Based on LendingClub and PPDAI data sets, the experiment uses the AHP-LSTM model to classify and predict and compares it with other classification methods. Experimental results show that the performance of this method is superior to other comparison methods in both data sets, especially in the case of unbalanced data sets.http://dx.doi.org/10.1155/2022/9588486 |
| spellingShingle | Yafeng Xi Qiu Li Improved AHP Model and Neural Network for Consumer Finance Credit Risk Assessment Advances in Multimedia |
| title | Improved AHP Model and Neural Network for Consumer Finance Credit Risk Assessment |
| title_full | Improved AHP Model and Neural Network for Consumer Finance Credit Risk Assessment |
| title_fullStr | Improved AHP Model and Neural Network for Consumer Finance Credit Risk Assessment |
| title_full_unstemmed | Improved AHP Model and Neural Network for Consumer Finance Credit Risk Assessment |
| title_short | Improved AHP Model and Neural Network for Consumer Finance Credit Risk Assessment |
| title_sort | improved ahp model and neural network for consumer finance credit risk assessment |
| url | http://dx.doi.org/10.1155/2022/9588486 |
| work_keys_str_mv | AT yafengxi improvedahpmodelandneuralnetworkforconsumerfinancecreditriskassessment AT qiuli improvedahpmodelandneuralnetworkforconsumerfinancecreditriskassessment |