Titre : |
Credit default risk scoring models in P2P Lending Platforms |
Type de document : |
Mémoire |
Auteurs : |
Jihane WADI, Auteur |
Année de publication : |
2020 |
Importance : |
25 p. |
Note générale : |
Pour accéder aux fichiers PDF, merci de vous identifier sur le catalogue avec votre compte Office 365 via le bouton CONNEXION en haut de page. |
Langues : |
Anglais (eng) |
Mots-clés : |
Management FINANCE DE MARCHE ; EMPRUNT ; PRET
|
Résumé : |
This Seminar Paper aims to examine the credit default assessment models used by P2P platforms as “Alternative Finance” entities and their effectiveness in predicting consumer credit defaults. The objective is to prove how these platforms play a major role as information intermediaries between borrowers and lenders, and how this information is reflected through the credit scores and grades attributed to loan applications. P2P platforms claim being different from traditional financial institutions in their business model, but they still have to revendicate the role of credit risk expert to ensure the success of their industry. This paper aims to explore to what extent the credit default scoring models used by P2P platforms are similar to those used in the traditional banking system and their performance in predicting defaults. For this purpose, a data set comprised of loan listings from the 2 largest P2P platforms in the US is used to test the discriminative power of credit default risk classifiers used by these P2P platforms. The results of this study suggest that P2P lending platforms indeed succeed in differentiating between “good and bad borrowers” through the use of the borrower and loan characteristic information disclosed by borrowers, just like the traditional credit grading systems used by banks. |
Programme : |
PGE-Rouen |
Spécialisation : |
Finance d’Entreprise - Corporate Finance |
Permalink : |
https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=531698 |