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Network centrality effects in peer to peer lending

Author

Listed:
  • Chen, Xiao
  • Chong, Zhaohui
  • Giudici, Paolo
  • Huang, Bihong

Abstract

This paper investigates the impact of network centrality on borrowers’ and lenders’ behavior in P2P lending. The empirical analysis on a leading Chinese lending platform reveals that the lenders who are in the center of a network not only invest by larger amounts but also more swiftly than their peers, reflecting the experience and information advantage arising from their position in the network. Furthermore central borrowers can borrow at lower interest rates with higher success rates, and have lower probability of default.

Suggested Citation

  • Chen, Xiao & Chong, Zhaohui & Giudici, Paolo & Huang, Bihong, 2022. "Network centrality effects in peer to peer lending," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    • Handle: RePEc:eee:phsmap:v:600:y:2022:i:c:s0378437122003818
    DOI: 10.1016/j.physa.2022.127546
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    2. Wang, Jin & Li, Rui, 2023. "Asymmetric information in peer-to-peer lending: empirical evidence from China," Finance Research Letters, Elsevier, vol. 51(C).

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    More about this item

    Keywords

    Network centrality; Peer-to-peer lending; Lending behavior; Loan outcomes;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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