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

Lin Cong, Ke Tang, Danxia Xie and Weiyi Zhao

No 33173, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: G19 G23 (search for similar items in EconPapers)
Date: 2024-11
New Economics Papers: this item is included in nep-cna, nep-fmk and nep-pay
Note: CF IO
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