Concept of Peer-to-Peer Lending and Application of Machine Learning in Credit Scoring
Numerous applications of AI are found in the banking sector. Starting from the front-office, enhancing customer recognition and personalized services, continuing in the middle-office with automated fraud-detection systems, ending with the back-office and internal processes automatization. In this...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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University of Warsaw
2021-12-01
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| Series: | Journal of Banking and Financial Economics |
| Subjects: | |
| Online Access: | https://jbfe.wz.uw.edu.pl/resources/html/article/details?id=227963 |
| _version_ | 1797227036257812480 |
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| author | Aleksy Klimowicz Krzysztof Spirzewski |
| author_facet | Aleksy Klimowicz Krzysztof Spirzewski |
| author_sort | Aleksy Klimowicz |
| collection | DOAJ |
| description | Numerous applications of AI are found in the banking sector. Starting from the front-office,
enhancing customer recognition and personalized services, continuing in the middle-office
with automated fraud-detection systems, ending with the back-office and internal processes
automatization. In this paper we provide comprehensive information on the phenomenon of
peer-to-peer lending in the modern view of alternative finance and crowdfunding from several
perspectives. The aim of this research is to explore the phenomenon of peer-to-peer lending
market model. We apply and check the suitability and effectiveness of credit scorecards in the
marketplace lending along with determining the appropriate cut-off point.
We conducted this research by exploring recent studies and open-source data on marketplace
lending. The scorecard development is based on the P2P loans open dataset that contains
repayments record along with both hard and soft features of each loan. The quantitative part
consists in applying a machine learning algorithm in building a credit scorecard, namely logistic
regression. |
| first_indexed | 2024-04-24T14:34:25Z |
| format | Article |
| id | doaj.art-781815f2ac044a8ead8dffca35460307 |
| institution | Directory Open Access Journal |
| issn | 2353-6845 |
| language | English |
| last_indexed | 2024-04-24T14:34:25Z |
| publishDate | 2021-12-01 |
| publisher | University of Warsaw |
| record_format | Article |
| series | Journal of Banking and Financial Economics |
| spelling | doaj.art-781815f2ac044a8ead8dffca354603072024-04-03T01:36:52ZengUniversity of WarsawJournal of Banking and Financial Economics2353-68452021-12-0120212(16)255510.7172/2353-6845.jbfe.2021.2.2Concept of Peer-to-Peer Lending and Application of Machine Learning in Credit ScoringAleksy Klimowicz0Krzysztof Spirzewski1https://orcid.org/0000-0002-9646-5667University of Warsaw, Faculty of Economic SciencesUniversity of Warsaw, Faculty of Economic SciencesNumerous applications of AI are found in the banking sector. Starting from the front-office, enhancing customer recognition and personalized services, continuing in the middle-office with automated fraud-detection systems, ending with the back-office and internal processes automatization. In this paper we provide comprehensive information on the phenomenon of peer-to-peer lending in the modern view of alternative finance and crowdfunding from several perspectives. The aim of this research is to explore the phenomenon of peer-to-peer lending market model. We apply and check the suitability and effectiveness of credit scorecards in the marketplace lending along with determining the appropriate cut-off point. We conducted this research by exploring recent studies and open-source data on marketplace lending. The scorecard development is based on the P2P loans open dataset that contains repayments record along with both hard and soft features of each loan. The quantitative part consists in applying a machine learning algorithm in building a credit scorecard, namely logistic regression.https://jbfe.wz.uw.edu.pl/resources/html/article/details?id=227963artificial intelligencepeer-to-peer lendingcredit risk assessmentcredit scorecardslogistic regressionmachine learning |
| spellingShingle | Aleksy Klimowicz Krzysztof Spirzewski Concept of Peer-to-Peer Lending and Application of Machine Learning in Credit Scoring Journal of Banking and Financial Economics artificial intelligence peer-to-peer lending credit risk assessment credit scorecards logistic regression machine learning |
| title | Concept of Peer-to-Peer Lending and Application of Machine Learning in Credit Scoring |
| title_full | Concept of Peer-to-Peer Lending and Application of Machine Learning in Credit Scoring |
| title_fullStr | Concept of Peer-to-Peer Lending and Application of Machine Learning in Credit Scoring |
| title_full_unstemmed | Concept of Peer-to-Peer Lending and Application of Machine Learning in Credit Scoring |
| title_short | Concept of Peer-to-Peer Lending and Application of Machine Learning in Credit Scoring |
| title_sort | concept of peer to peer lending and application of machine learning in credit scoring |
| topic | artificial intelligence peer-to-peer lending credit risk assessment credit scorecards logistic regression machine learning |
| url | https://jbfe.wz.uw.edu.pl/resources/html/article/details?id=227963 |
| work_keys_str_mv | AT aleksyklimowicz conceptofpeertopeerlendingandapplicationofmachinelearningincreditscoring AT krzysztofspirzewski conceptofpeertopeerlendingandapplicationofmachinelearningincreditscoring |