Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithm
The rapid development of Chinese online loan platforms (OLPs), as well as their risks, has attracted widespread attention, increasing the demand for a complete credit rating mechanism. The present study establishes a credit rating indicator system for 130 mainstream Chinese OLPs that combines 12 qua...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2023-09-01
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| Series: | Journal of Management Science and Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2096232023000161 |
| _version_ | 1797769767021445120 |
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| author | Rongda Chen Shengnan Wang Zhenghao Zhu Jingjing Yu Chao Dang |
| author_facet | Rongda Chen Shengnan Wang Zhenghao Zhu Jingjing Yu Chao Dang |
| author_sort | Rongda Chen |
| collection | DOAJ |
| description | The rapid development of Chinese online loan platforms (OLPs), as well as their risks, has attracted widespread attention, increasing the demand for a complete credit rating mechanism. The present study establishes a credit rating indicator system for 130 mainstream Chinese OLPs that combines 12 quantitative metrics of online loan operations similar to commercial bank credit rating indicators, including platform transaction volume and average expected rate of return. We also consider two qualitative indicators of online loan background, namely platform background and guarantee mode, that reflect Chinese characteristics. Subsequently, a factor analysis was conducted to reduce the 14 indicators’ dimensions. The loads of the rating indicators in the resulting rotating component matrix were refined into an OLP operation scale factor, fund dispersion factor, security factor, and profitability factor. Finally, a K-means clustering algorithm was employed to cluster the factor scores of each OLP, thereby obtaining credit rating results. The empirical results indicate that the proposed machine learning–based credit rating method effectively provides early warnings of problem platforms, yielding more accurate credit ratings than those provided by two mainstream online loan rating websites in China, namely, Wangdaitianyan and Wangdaizhijia. |
| first_indexed | 2024-03-12T21:13:45Z |
| format | Article |
| id | doaj.art-398d6ec1d66145e19aafa3ef360dc302 |
| institution | Directory Open Access Journal |
| issn | 2096-2320 |
| language | English |
| last_indexed | 2024-03-12T21:13:45Z |
| publishDate | 2023-09-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Management Science and Engineering |
| spelling | doaj.art-398d6ec1d66145e19aafa3ef360dc3022023-07-30T04:22:18ZengKeAi Communications Co., Ltd.Journal of Management Science and Engineering2096-23202023-09-0183287304Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithmRongda Chen0Shengnan Wang1Zhenghao Zhu2Jingjing Yu3Chao Dang4School of Finance, Zhejiang University of Finance and Economics, Hangzhou, 310018, China; Financial Innovation and Inclusive Finance Research Center, Zhejiang University of Finance and Economics, Hangzhou, 310018, China; Zhejiang Double-Eight Strategy Research Institute, Hangzhou, 310018, ChinaSchool of Finance, Zhejiang University of Finance and Economics, Hangzhou, 310018, ChinaSchool of Finance, Zhejiang University of Finance and Economics, Hangzhou, 310018, ChinaSchool of Finance, Zhejiang University of Finance and Economics, Hangzhou, 310018, ChinaSchool of Finance, Zhejiang University of Finance and Economics, Hangzhou, 310018, China; Corresponding author.The rapid development of Chinese online loan platforms (OLPs), as well as their risks, has attracted widespread attention, increasing the demand for a complete credit rating mechanism. The present study establishes a credit rating indicator system for 130 mainstream Chinese OLPs that combines 12 quantitative metrics of online loan operations similar to commercial bank credit rating indicators, including platform transaction volume and average expected rate of return. We also consider two qualitative indicators of online loan background, namely platform background and guarantee mode, that reflect Chinese characteristics. Subsequently, a factor analysis was conducted to reduce the 14 indicators’ dimensions. The loads of the rating indicators in the resulting rotating component matrix were refined into an OLP operation scale factor, fund dispersion factor, security factor, and profitability factor. Finally, a K-means clustering algorithm was employed to cluster the factor scores of each OLP, thereby obtaining credit rating results. The empirical results indicate that the proposed machine learning–based credit rating method effectively provides early warnings of problem platforms, yielding more accurate credit ratings than those provided by two mainstream online loan rating websites in China, namely, Wangdaitianyan and Wangdaizhijia.http://www.sciencedirect.com/science/article/pii/S2096232023000161Internet financeOnline loan platformCredit ratingsMachine learning |
| spellingShingle | Rongda Chen Shengnan Wang Zhenghao Zhu Jingjing Yu Chao Dang Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithm Journal of Management Science and Engineering Internet finance Online loan platform Credit ratings Machine learning |
| title | Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithm |
| title_full | Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithm |
| title_fullStr | Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithm |
| title_full_unstemmed | Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithm |
| title_short | Credit ratings of Chinese online loan platforms based on factor scores and K-means clustering algorithm |
| title_sort | credit ratings of chinese online loan platforms based on factor scores and k means clustering algorithm |
| topic | Internet finance Online loan platform Credit ratings Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2096232023000161 |
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