Human–Robot Interaction: When Investors Adjust the Usage of Robo-Advisors in Peer-to-Peer Lending
点对点
服务(商务)
投资(军事)
业务
违约
财务
营销
计算机科学
万维网
政治学
政治
法学
作者
Ruyi Ge,Zhiqiang Zheng,Xuan Tian,Li Liao
出处
期刊:Information Systems Research [Institute for Operations Research and the Management Sciences] 日期:2021-07-20卷期号:32 (3): 774-785被引量:79
标识
DOI:10.1287/isre.2021.1009
摘要
We study the human–robot interaction of financial-advising services in peer-to-peer lending (P2P). Many crowdfunding platforms have started using robo-advisors to help lenders augment their intelligence in P2P loan investments. Collaborating with one of the leading P2P companies, we examine how investors use robo-advisors and how the human adjustment of robo-advisor usage affects investment performance. Our analyses show that, somewhat surprisingly, investors who need more help from robo-advisors—that is, those encountered more defaults in their manual investing—are less likely to adopt such services. Investors tend to adjust their usage of the service in reaction to recent robo-advisor performance. However, interestingly, these human-in-the-loop interferences often lead to inferior performance.