How do machine learning and non-traditional data affect credit scoring? : new evidence from a Chinese fintech firm
Year of publication: |
28 December 2019
|
---|---|
Authors: | Gambacorta, Leonardo ; Huang, Yiping ; Qiu, Han ; Wang, Jingyi |
Publisher: |
London : Centre for Economic Policy Research |
Subject: | Fintech | credit scoring | non-traditional information | Machine Learning | credit risk | Künstliche Intelligenz | Artificial intelligence | Kreditwürdigkeit | Credit rating | Finanztechnologie | Financial technology | Kreditrisiko | Credit risk | China | Kreditgeschäft | Bank lending |
Extent: | 1 Online-Ressource (circa 24 Seiten) Illustrationen |
---|---|
Series: | Discussion papers / CEPR. - London : CEPR, ZDB-ID 2001019-9. - Vol. DP14259 |
Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Graue Literatur ; Non-commercial literature ; Arbeitspapier ; Working Paper |
Language: | English |
Source: | ECONIS - Online Catalogue of the ZBW |
-
Gambacorta, Leonardo, (2019)
-
How Magic a Bullet Is Machine Learning for Credit Analysis? An Exploration with FinTech Lending Data
Wang, J. Christina, (2021)
-
Wang, J. Christina, (2019)
- More ...
-
Gambacorta, Leonardo, (2019)
-
Gambacorta, Leonardo, (2020)
-
Digital technology and economic impacts of COVID-19 : experiences of the People's Republic of China
Huang, Yiping, (2021)
- More ...