FinTech Platforms and Asymmetric Network Effects: Theory and Evidence from Marketplace Lending

75 Pages Posted: 4 Oct 2019 Last revised: 25 Nov 2024

See all articles by Lin William Cong

Lin William Cong

Cornell University - Samuel Curtis Johnson Graduate School of Management; Cornell SC Johnson College of Business; National Bureau of Economic Research (NBER)

Ke Tang

Institute of Economics, School of Social Sciences, Tsinghua University

Danxia Xie

Tsinghua University - Institute of Economics

Weiyi Zhao

Tsinghua University

Date Written: November 10, 2024

Abstract

We conceptually identify and empirically verify using marketplace lending data the features distinguishing FinTech platforms from non-financial platforms: (i) Long-term contracts introducing default risk at both the individual and platform levels; (ii) Lenders’ investment diversification to mitigate individual default risk; (iii) Platform-level default risk leading to greater asymmetric user stickiness and rendering platform-level cross-side network effects (p-CNEs), a novel metric we introduce, crucial for adoption and market dynamics. We incorporate these features into a model of two-sided FinTech platform with potential failures and endogenous participation/fees. The model predicts lenders’ single-homing, occasional lower fees for borrowers, asymmetric p-CNEs, and the predictive power of lenders’ p-CNEs in forecasting platform failures. Marketplace lending in China empirically corroborate our model predictions in this dynamic industry characterized by entries, exits, and network externalities. Specifically, lenders’ p-CNEs are empirically lower on declining or more established platforms compared to growing or new ones. Moreover, lenders’ p-CNEs predict platforms’ survival likelihood among others, even at very early stages. Our findings provide novel economic insights on multi-sided FinTech platforms for both practitioners and regulators.

Keywords: Cross-Side Network Effect, FinTech, Marketplace Lending, Platform Failure

JEL Classification: G19; G23; L13; L81

Suggested Citation

Cong, Lin and Tang, Ke and Xie, Danxia and Zhao, Weiyi, FinTech Platforms and Asymmetric Network Effects: Theory and Evidence from Marketplace Lending (November 10, 2024). Available at SSRN: https://ssrn.com/abstract=3461893 or http://dx.doi.org/10.2139/ssrn.3461893

Lin Cong (Contact Author)

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States

HOME PAGE: http://www.linwilliamcong.com/

Cornell SC Johnson College of Business ( email )

Ithaca, NY 14850
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Ke Tang

Institute of Economics, School of Social Sciences, Tsinghua University ( email )

No.1 Tsinghua Garden
Beijing, 100084
China

Danxia Xie

Tsinghua University - Institute of Economics ( email )

MingZhai Building
Beijing, 100084
China

HOME PAGE: http://sites.google.com/site/xiedanxia/

Weiyi Zhao

Tsinghua University ( email )

Beijing, 100084
China

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