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https://doi.org/10.21256/zhaw-23432| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Network based credit risk models |
| Autor/-in: | Giudici, Paolo Hadji Misheva, Branka Spelta, Alessandro |
| et. al: | No |
| DOI: | 10.1080/08982112.2019.1655159 10.21256/zhaw-23432 |
| Erschienen in: | Quality Engineering |
| Band(Heft): | 32 |
| Heft: | 2 |
| Seite(n): | 199 |
| Seiten bis: | 211 |
| Erscheinungsdatum: | 2019 |
| Verlag / Hrsg. Institution: | Taylor & Francis |
| ISSN: | 0898-2112 1532-4222 |
| Sprache: | Englisch |
| Schlagwörter: | Credit scoring model; Network model; Peer-to-peer lending |
| Fachgebiet (DDC): | 332: Finanzwirtschaft |
| Zusammenfassung: | Peer-to-Peer lending platforms may lead to cost reduction, and to an improved user experience. These improvements may come at the price of inaccurate credit risk measurements, which can hamper lenders and endanger the stability of a financial system. In the article, we propose how to improve credit risk accuracy of peer to peer platforms and, specifically, of those who lend to small and medium enterprises. To achieve this goal, we propose toaugment traditional credit scoring methods with “alternative data” that consist of centralitymeasures derived from similarity networks among borrowers, deduced from their financialratios. Our empirical findings suggest that the proposed approach improves predictiveaccuracy as well as model explainability. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/23432 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY-NC-ND 4.0: Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Datenanalyse und Prozessdesign (IDP) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2019_Giudici-etal_Network-based-credit-risk-models.pdf | 2.53 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
Giudici, P., Hadji Misheva, B., & Spelta, A. (2019). Network based credit risk models. Quality Engineering, 32(2), 199–211. https://doi.org/10.1080/08982112.2019.1655159
Giudici, P., Hadji Misheva, B. and Spelta, A. (2019) ‘Network based credit risk models’, Quality Engineering, 32(2), pp. 199–211. Available at: https://doi.org/10.1080/08982112.2019.1655159.
P. Giudici, B. Hadji Misheva, and A. Spelta, “Network based credit risk models,” Quality Engineering, vol. 32, no. 2, pp. 199–211, 2019, doi: 10.1080/08982112.2019.1655159.
GIUDICI, Paolo, Branka HADJI MISHEVA und Alessandro SPELTA, 2019. Network based credit risk models. Quality Engineering. 2019. Bd. 32, Nr. 2, S. 199–211. DOI 10.1080/08982112.2019.1655159
Giudici, Paolo, Branka Hadji Misheva, and Alessandro Spelta. 2019. “Network Based Credit Risk Models.” Quality Engineering 32 (2): 199–211. https://doi.org/10.1080/08982112.2019.1655159.
Giudici, Paolo, et al. “Network Based Credit Risk Models.” Quality Engineering, vol. 32, no. 2, 2019, pp. 199–211, https://doi.org/10.1080/08982112.2019.1655159.
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