FinTech Platforms and Asymmetric Network Effects: Theory and Evidence from Marketplace Lending / Lin William Cong, Ke Tang, Danxia Xie, Weiyi Zhao.

Format:

Book

Author/Creator:

Cong, Lin William.

Contributor:

Tang, Ke.

Xie, Danxia.

Zhao, Weiyi.

National Bureau of Economic Research.

Series:

Working Paper Series (National Bureau of Economic Research) no. w33173.

NBER working paper series no. w33173

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2024.

Summary:

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.

Notes:

November 2024.

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