Abstract
In this work, we systematically investigate the pricing mechanism change from auction to big data pricing on one of the major marketplace lending platforms in China. We find that big data pricing reduces the average interest rate while the borrowers with delinquency or default histories are assigned higher interest rates. However, repeat borrowers are also faced with growing interest rates, even though they have been paying their debts on time. Further analysis shows that repeat borrowers have lower income and education levels. Moreover, investor returns become less dispersed after pricing with big data, which can be a result of homogeneous loans on the market. The implications of the above findings are discussed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
