Time:2019.05.08, 12:30 PM

Location:Room 615, Main Building

KeynoteSpeaker:Dr. ZhangXiaodan, Postdoctoral Fellow, Department of Marketing, Guanghua School ofManagement, Peking University  

Abstract:Difficulty in exercisingformal (court-enforced) solutions of default still remains. This study exploresin what extent and how the exposure of different types of social connectionsinfluences online borrower’s repayment behavior, including borrower intrinsicrepayment and company collection. Specifically, we divide“social others”as three types: family members, friends and colleagues. Our predictionis that online borrowers are less likely to default when disclosing his/her colleagueinformation than disclosing only family members’ information or close friendinformation to the lender. For collection, sending the borrowers messageseliciting the potential contacts increases the likelihood that the loans willbe repaid. We test our theory in the context of Chinese online lending companywith historical data and field experiments. Preliminary results provideevidence of our hypotheses, demonstrating the predictive effect of socialconnections and the potential importance of such interventions in enhancingloan repayment for the online lending platform.