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

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.