A Novel Reject Inference Model Using Outlier Detection and Gradient Boosting Technique in Peer-to-Peer Lending

A Novel Reject Inference Model Using Outlier Detection and Gradient Boosting Technique in Peer-to-Peer Lending

Credit scoring is an efficient tool in handling the information asymmetry of peer-to-peer (P2P) lending. Credit scoring models are typically built only with the accepted applicants, which may cause sample bias and further hinder the predictive performances. Reject inference methods utilize the infor...

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Bibliographic Details
Main Author: Yufei Xia
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Credit scoring
gradient boosting decision tree
outlier detection
P2P lending
reject inference
Online Access:https://ieeexplore.ieee.org/document/8758218/

Internet

https://ieeexplore.ieee.org/document/8758218/

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