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

Jiaqi Yan (), Wayne Yu and J. Leon Zhao
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Jiaqi Yan: University of Zurich
Wayne Yu: City University of Hong Kong
J. Leon Zhao: City University of Hong Kong

Financial Innovation, 2015, vol. 1, issue 1, 1-11

Abstract: 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.

Keywords: Lending industry; P2P lending; Big data; Economics of big data; Fintech; Information economics (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (25)

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DOI: 10.1186/s40854-015-0018-1

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