How signaling and search costs affect information asymmetry in P2P lending: the economics of big data

Jiaqi Yan*, Wayne Yu, J. Leon Zhao

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Abstract

In the past decade, online Peer-to-Peer (P2P) lending platforms have transformed the lending industry, which has been historically dominated by commercial banks. Information technology breakthroughs such as big data-based financial technologies (Fintech) have been identified as important disruptive driving forces for this paradigm shift. In this paper, we take an information economics perspective to investigate how big data affects the transformation of the lending industry. By identifying how signaling and search costs are reduced by big data analytics for credit risk management of P2P lending, we discuss how information asymmetry is reduced in the big data era. Rooted in the lending business, we propose a theory on the economics of big data and outline a number of research opportunities and challenging issues.
Original languageEnglish
JournalFinancial Innovation
Volume1
Issue number19
Online published29 Dec 2015
DOIs
Publication statusPublished - 2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Research Keywords

  • Lending industry
  • P2P lending
  • Big data
  • Economics of big data
  • Fintech
  • Information economics

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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