An empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (P2P) lending in China
As a new model of Internet finance, P2P lending provides a new financing channel to the individuals and SMEs who are facing financing difficulties. P2P lending has become an important supplement to China’s traditional financial model. But with the rapid development of P2P lending, its hidden risks c...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2019
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| Online Access: | https://eprints.nottingham.ac.uk/57844/ |
| _version_ | 1848799506725863424 |
|---|---|
| author | Huang, Xinyu |
| author_facet | Huang, Xinyu |
| author_sort | Huang, Xinyu |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | As a new model of Internet finance, P2P lending provides a new financing channel to the individuals and SMEs who are facing financing difficulties. P2P lending has become an important supplement to China’s traditional financial model. But with the rapid development of P2P lending, its hidden risks cannot be ignored, especially the borrower’s default risk. This problem not only causes the loss of capital to the lenders but also has a great negative impact on the reputation of P2P lending, which seriously hinders the further development of P2P lending. Therefore, the main objectives of this dissertation are to analyze the reasons for the borrower’s default risk, the influencing factors of borrower’s default risk, and how to prevent the default risk.
Based on the previous research results, this dissertation uses logistic regression to test the influencing factors of borrower’s default risk. The results show that gender, marital status, working experience, and income are significantly positively associated with the default risk. Age, education level, loan amount, and credit rating are significantly negatively associated with the default risk. Finally, the writer proposed some suggestions to prevent the borrower’s default risk, hoping to contribute to the sustainable and healthy development of P2P lending in the future.
Keywords: P2P lending, logistic regression, credit risk, default risk |
| first_indexed | 2025-11-14T20:36:45Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-57844 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:36:45Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-578442022-12-02T09:47:56Z https://eprints.nottingham.ac.uk/57844/ An empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (P2P) lending in China Huang, Xinyu As a new model of Internet finance, P2P lending provides a new financing channel to the individuals and SMEs who are facing financing difficulties. P2P lending has become an important supplement to China’s traditional financial model. But with the rapid development of P2P lending, its hidden risks cannot be ignored, especially the borrower’s default risk. This problem not only causes the loss of capital to the lenders but also has a great negative impact on the reputation of P2P lending, which seriously hinders the further development of P2P lending. Therefore, the main objectives of this dissertation are to analyze the reasons for the borrower’s default risk, the influencing factors of borrower’s default risk, and how to prevent the default risk. Based on the previous research results, this dissertation uses logistic regression to test the influencing factors of borrower’s default risk. The results show that gender, marital status, working experience, and income are significantly positively associated with the default risk. Age, education level, loan amount, and credit rating are significantly negatively associated with the default risk. Finally, the writer proposed some suggestions to prevent the borrower’s default risk, hoping to contribute to the sustainable and healthy development of P2P lending in the future. Keywords: P2P lending, logistic regression, credit risk, default risk 2019-12-01 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/57844/1/4339845%20N14030%20An%20empirical%20analysis%20of%20the%20determinants%20of%20borrowers%E2%80%99%20default%20risk%20in%20peer-to-peer%20%28P2P%29%20lending%20in%20China.pdf Huang, Xinyu (2019) An empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (P2P) lending in China. [Dissertation (University of Nottingham only)] |
| spellingShingle | Huang, Xinyu An empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (P2P) lending in China |
| title | An empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (P2P) lending in China |
| title_full | An empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (P2P) lending in China |
| title_fullStr | An empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (P2P) lending in China |
| title_full_unstemmed | An empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (P2P) lending in China |
| title_short | An empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (P2P) lending in China |
| title_sort | empirical analysis of the determinants of borrowers’ default risk in peer-to-peer (p2p) lending in china |
| url | https://eprints.nottingham.ac.uk/57844/ |