Work

Borrower’s default and self-disclosure of social media information in P2P lending

Year: 2016

Type: article

Abstract: Background We examine the signaling effect of borrowers’ social media behavior, especially self-disclosure behavior, on the default probability of money borrowers on a peer-to-peer (P2P) lending site. Method We use a unique dataset that combines loan data from a large P2P lending site with the borrower’s social media presence data from a popular social media site. Results Through a natural experiment enabled by an instrument variable, we identify two forms of social media information that act as signals of borrowers’ creditworthiness: (1) borrowers’ choice to self-disclose their social media account to the P2P lending site, and (2) borrowers’ social media behavior, such as their social network scope and social media engagement. Conclusion This study offers new insights for screening borrowers in P2P lending and a novel usage of social media information.

Source: Financial Innovation

DOI: 10.1186/s40854-016-0048-3

Authors: Ruyi Ge, Juan Feng, Bin Gu

Institutions: Shanghai Business School, City University of Hong Kong, Arizona State University

Language: English

Topic: FinTech, Crowdfunding, Digital Finance

Subfield: Management Information Systems

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: diamond

Funders: City University of Hong Kong, National Natural Science Foundation of China

Awards: G2082013170, G8093013004