TY - GEN
T1 - A social recommendation mechanism for peer-to-peer lending
AU - Hwang, Ting Kai
AU - Li, Yung-Ming
AU - Wan, Jun Fei
N1 - Publisher Copyright:
© 2018 Association for Information Systems. All rights reserved.
PY - 2018
Y1 - 2018
N2 - Compared with traditional bank, Peer-to-Peer (P2P) lending is claimed to benefit both borrowers and lenders. However, because of the information asymmetry online, much fewer investors dare to use this new alternative finance comparing to the potential market. Moreover, for borrowers, they always spend much more time to wait for the bidders during the initial phase than the other phases. This research has proposed a social recommendation mechanism to help borrowers to find suitable lenders based on the theory of social capital and techniques of social computing and to attract more potential lenders to join in the P2P lending utilizing the theory of social influence. An experiment simulating the process of P2P lending has been executed in this paper. With comparisons in multiple dimensions, it shows our proposed mechanism can effectively improve the bidding rate for borrowers and the lenders are willing to lend out more money in each bid when they have social relationships with borrowers.
AB - Compared with traditional bank, Peer-to-Peer (P2P) lending is claimed to benefit both borrowers and lenders. However, because of the information asymmetry online, much fewer investors dare to use this new alternative finance comparing to the potential market. Moreover, for borrowers, they always spend much more time to wait for the bidders during the initial phase than the other phases. This research has proposed a social recommendation mechanism to help borrowers to find suitable lenders based on the theory of social capital and techniques of social computing and to attract more potential lenders to join in the P2P lending utilizing the theory of social influence. An experiment simulating the process of P2P lending has been executed in this paper. With comparisons in multiple dimensions, it shows our proposed mechanism can effectively improve the bidding rate for borrowers and the lenders are willing to lend out more money in each bid when they have social relationships with borrowers.
KW - Information asymmetry
KW - Peer-to-Peer lending
KW - Social influence
KW - Social recommendation
UR - http://www.scopus.com/inward/record.url?scp=85054229401&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85054229401
SN - 9780996683166
T3 - Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018
BT - Americas Conference on Information Systems 2018
PB - Association for Information Systems
T2 - 24th Americas Conference on Information Systems 2018: Digital Disruption, AMCIS 2018
Y2 - 16 August 2018 through 18 August 2018
ER -