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

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  • Jiaqi Yan

    (University of Zurich)

  • Wayne Yu

    (City University of Hong Kong)

  • J. Leon Zhao

    (City University of Hong Kong)

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.

Suggested Citation

  • Jiaqi Yan & Wayne Yu & J. Leon Zhao, 2015. "How signaling and search costs affect information asymmetry in P2P lending: the economics of big data," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-11, December.
    • Handle: RePEc:spr:fininn:v:1:y:2015:i:1:d:10.1186_s40854-015-0018-1
    DOI: 10.1186/s40854-015-0018-1
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    References listed on IDEAS

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    Cited by:

    1. Ji-Yoon Kim & Sung-Bae Cho, 2019. "Towards Repayment Prediction in Peer-to-Peer Social Lending Using Deep Learning," Mathematics, MDPI, vol. 7(11), pages 1-17, November.
    2. Jiang, Cuixia & Xu, Qifa & Zhang, Weiming & Li, Mengting & Yang, Shanlin, 2018. "Does automatic bidding mechanism affect herding behavior? Evidence from online P2P lending in China," Journal of Behavioral and Experimental Finance, Elsevier, vol. 20(C), pages 39-44.
    3. Xueru Chen & Xiaoji Hu & Shenglin Ben, 2021. "How do reputation, structure design and FinTech ecosystem affect the net cash inflow of P2P lending platforms? Evidence from China," Electronic Commerce Research, Springer, vol. 21(4), pages 1055-1082, December.
    4. Svatopluk Kapounek & Zuzana Kucerová, 2019. "Overfunding and Signaling Effects of Herding Behavior in Crowdfunding," CESifo Working Paper Series 7973, CESifo.
    5. Dömötör, Barbara & Ölvedi, Tímea, 2021. "A személyközi hitelezés létjogosultsága a pénzügyi közvetítésben [The relevance of peer-to-peer lending in financial intermediation]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 773-793.
    6. Benjamin Käfer, 2016. "Peer-to-Peer Lending – A (Financial Stability) Risk Perspective," MAGKS Papers on Economics 201622, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    7. Käfer Benjamin, 2018. "Peer-to-Peer Lending – A (Financial Stability) Risk Perspective," Review of Economics, De Gruyter, vol. 69(1), pages 1-25, April.
    8. Shuai Li & Hao Yu, 2020. "RETRACTED ARTICLE: Big data and financial information analytics ecosystem: strengthening personal information under legal regulation," Information Systems and e-Business Management, Springer, vol. 18(4), pages 891-909, December.
    9. Hyunwoo Woo & So Young Sohn, 2022. "A credit scoring model based on the Myers–Briggs type indicator in online peer-to-peer lending," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-19, December.
    10. Zhao Wang & Cuiqing Jiang & Huimin Zhao, 2022. "Know Where to Invest: Platform Risk Evaluation in Online Lending," Information Systems Research, INFORMS, vol. 33(3), pages 765-783, September.
    11. Ahmet F. Aysan & Zhamal Nanaeva, 2022. "Fintech as a Financial Disruptor: A Bibliometric Analysis," FinTech, MDPI, vol. 1(4), pages 1-22, December.
    12. Samuel Ribeiro-Navarrete & Juan Piñeiro-Chousa & M. Ángeles López-Cabarcos & Daniel Palacios-Marqués, 2022. "Crowdlending: mapping the core literature and research frontiers," Review of Managerial Science, Springer, vol. 16(8), pages 2381-2411, November.
    13. Xin Li & Xiujuan Tian, 2022. "Research on SMEs’ Reputation Mechanism and Default Risk Based on Investors’ Financial Participation," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    14. Yinqiao Li & Renée Spigt & Laurens Swinkels, 2017. "The impact of FinTech start-ups on incumbent retail banks’ share prices," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-16, December.
    15. Wang, Jin & Li, Rui, 2023. "Asymmetric information in peer-to-peer lending: empirical evidence from China," Finance Research Letters, Elsevier, vol. 51(C).
    16. Nanaeva, Zhamal & Aysan, Ahmet Faruk, 2021. "Fintech As a Financial Disruptor: The Bibliometric Analysis," MPRA Paper 115535, University Library of Munich, Germany.
    17. Elena Deryugina & Alexey Ponomarenko & Andrey Sinyakov, 2021. "Exploring the conjunction between the structures of deposit and credit markets in the digital economy under information asymmetry," Bank of Russia Working Paper Series wps78, Bank of Russia.
    18. Abbasi, Kaleemullah & Alam, Ashraful & Du, Min (Anna) & Huynh, Toan Luu Duc, 2021. "FinTech, SME efficiency and national culture: Evidence from OECD countries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).

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