Economic Disruptions in Repayment of Peer Loans
Economic disruptions can alter the likelihood of defaults on peer-to-peer loans, causing those impacted to adjust. The option to declare economic hardship and temporarily reduce the payment burden can provide some relief. When this occurs, the borrower’s financial qualifications have changed. The qu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | International Journal of Financial Studies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7072/11/4/116 |
| _version_ | 1827384375997628416 |
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| author | David Maloney Sung-Chul Hong Barin Nag |
| author_facet | David Maloney Sung-Chul Hong Barin Nag |
| author_sort | David Maloney |
| collection | DOAJ |
| description | Economic disruptions can alter the likelihood of defaults on peer-to-peer loans, causing those impacted to adjust. The option to declare economic hardship and temporarily reduce the payment burden can provide some relief. When this occurs, the borrower’s financial qualifications have changed. The qualities instrumental in successfully securing the original loan terms must be reanalyzed to manage risk. This is a critical point in the life of the loan because the declaration of financial hardship can signal that the borrower’s ability to repay has diminished. We present a novel default detection scheme for borrowers experiencing an economic disruption based on the Two-Class Support Vector Machine, a data classification algorithm for supervised learning problems. The method utilizes data from actual loan records (15,355 loans from 2016 through 2020), specifically from borrowers who declared economic hardship. We provide a detailed description of the default detection process and present results that show defaults among borrowers experiencing financial hardship can be predicted accurately. |
| first_indexed | 2024-03-08T14:54:41Z |
| format | Article |
| id | doaj.art-c166a9549d20421f94f05ba27718e511 |
| institution | Directory Open Access Journal |
| issn | 2227-7072 |
| language | English |
| last_indexed | 2024-03-08T14:54:41Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Financial Studies |
| spelling | doaj.art-c166a9549d20421f94f05ba27718e5112024-01-10T17:49:12ZengMDPI AGInternational Journal of Financial Studies2227-70722023-09-0111411610.3390/ijfs11040116Economic Disruptions in Repayment of Peer LoansDavid Maloney0Sung-Chul Hong1Barin Nag2Department of Computer and Information Sciences, Towson University, Towson, MD 21204, USADepartment of Computer and Information Sciences, Towson University, Towson, MD 21204, USADepartment of Computer and Information Sciences, Towson University, Towson, MD 21204, USAEconomic disruptions can alter the likelihood of defaults on peer-to-peer loans, causing those impacted to adjust. The option to declare economic hardship and temporarily reduce the payment burden can provide some relief. When this occurs, the borrower’s financial qualifications have changed. The qualities instrumental in successfully securing the original loan terms must be reanalyzed to manage risk. This is a critical point in the life of the loan because the declaration of financial hardship can signal that the borrower’s ability to repay has diminished. We present a novel default detection scheme for borrowers experiencing an economic disruption based on the Two-Class Support Vector Machine, a data classification algorithm for supervised learning problems. The method utilizes data from actual loan records (15,355 loans from 2016 through 2020), specifically from borrowers who declared economic hardship. We provide a detailed description of the default detection process and present results that show defaults among borrowers experiencing financial hardship can be predicted accurately.https://www.mdpi.com/2227-7072/11/4/116machine learningeconomic disruptionpeer-to-peer lending |
| spellingShingle | David Maloney Sung-Chul Hong Barin Nag Economic Disruptions in Repayment of Peer Loans International Journal of Financial Studies machine learning economic disruption peer-to-peer lending |
| title | Economic Disruptions in Repayment of Peer Loans |
| title_full | Economic Disruptions in Repayment of Peer Loans |
| title_fullStr | Economic Disruptions in Repayment of Peer Loans |
| title_full_unstemmed | Economic Disruptions in Repayment of Peer Loans |
| title_short | Economic Disruptions in Repayment of Peer Loans |
| title_sort | economic disruptions in repayment of peer loans |
| topic | machine learning economic disruption peer-to-peer lending |
| url | https://www.mdpi.com/2227-7072/11/4/116 |
| work_keys_str_mv | AT davidmaloney economicdisruptionsinrepaymentofpeerloans AT sungchulhong economicdisruptionsinrepaymentofpeerloans AT barinnag economicdisruptionsinrepaymentofpeerloans |