Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending
By Riza Emekter, Yanbin Tu, B. Jirasakuldech, Min Lu. 2015
489 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/9f848af3f9592e4ac2c45277c69886bed35dc2ee
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Xiaolong Li
- Zhongyu Zheng
- Xu-chen Lin
- Vural Aksakalli
- Milad Malekipirbazari
- Weiming Zhang
Citations in the corpus
- Evaluating borrower’s default risk in peer-to-peer lending: evidence from a lending platform in China (2017, methodology): “It is interesting to note that there is high correlation between high debt-to-income ratio and low default rate, and this finding is consistent with the empirical result of the study of Riza et al. (Emekter et al. 2014), which use the data from the Lending Club.”
- Risk assessment in social lending via random forests (2015, methodology): “In this regard, subsequent to a risk and return efficiency analysis, Emekter et al. (2015) suggest that ‘‘the lenders would be better off to lend only to the safest borrowers with the highest LC grades’’.”