Borrower’s Self-Disclosure of Social Media Information in P2P Lending

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dc.contributor.authorGe, Ruyi
dc.contributor.authorGu, Bin
dc.contributor.authorFeng, Juan
dc.date.accessioned2016-12-29T02:03:56Z
dc.date.available2016-12-29T02:03:56Z
dc.date.issued2017-01-04
dc.description.abstractIn peer-to-peer (P2P) lending, soft information, such as borrowers’ facial features, textual descriptions of loan applications and so on, are regarded as potential signals to screen borrowers. In this study, we examine the signaling effect of a new category of soft information- social media information. Leveraging a unique dataset that combines loan data from a large P2P lending company with social media presence data from a popular social media site, and two natural experiments, we find two forms of social media information that act as signals of borrowers’ creditworthiness. First, borrowers’ choice to self-disclose their social media account is a predictor of their default probability. Second, borrowers’ social media presence, such as their social network and social media engagement, are also predictors of default probability. This study proffers new insights for the screening process in P2P lending and novel usage of social media information.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.671
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41834
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectdefault probability
dc.subjectdifference-in-differences
dc.subjectnatural experiment
dc.subjectpeer-to-peer lending
dc.subjectpropensity score matching
dc.subjectsocial media
dc.subjectsoft information
dc.subjectsignaling
dc.titleBorrower’s Self-Disclosure of Social Media Information in P2P Lending
dc.typeConference Paper
dc.type.dcmiText

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