Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/203198
Authors: 
Wang, Yao
Drabek, Zdenek
Wang, Zhengwei
Year of Publication: 
2018
Series/Report no.: 
IES Working Paper 20/2018
Abstract: 
Online peer to peer lending (P2P) - allows people who want to borrow money to submit their applications on the platform and individual investors can make bids on the loan listings. The quality of information in credit appraisal becomes paramount in this market. The existing research to assess the role of what is known as soft information in P2P markets has so far been very limited and, inconclusive due to differences in approaches and methodological limitations. The aim of the paper is to discuss the role of soft information channels in predicting defaults in the P2P lending market and to assess the importance of soft information in the Fintech companies' credit analysis. Using a unique data of the Chinese P2P lending platform RRDai.com and new approach based on sets of hard and soft information, we compare the predicting performance of soft information, hard information and the combined role of both hard and soft information. We show that soft information can provide a valuable input in credit appraisal. The predicting power of soft information in our test was high, and together with hard information it can even help improve the loan performance. In exceptional situations characterized by the absence of hard financial data, soft information could be used, with caution, as an alternative.
Subjects: 
Soft Information
P2P Lending
Fintech
Microfinance
Credit Analysis
Empirical Study
JEL: 
D82
E51
G02
G14
G21
G23
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.