We conceptually identify and empirically verify the features distinguishing FinTech platforms from non-financial platforms using marketplace lending data. Specifically, we highlight three key features: (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 and fee structures. Our 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. Empirical evidence from China’s marketplace lending industry, characterized by frequent market entries, exits, and strong network externalities, corroborates our theoretical predictions. We find that lenders’ p-CNEs are systematically lower on declining or well-established platforms compared to those on emerging or rapidly growing platforms. Furthermore, lenders’ p-CNEs serve as an early indicator of platform survival likelihood, even at the initial stages of market development. Our findings provide novel economic insights into the functioning of multi-sided FinTech platforms, offering valuable implications for both industry practitioners and financial regulators.

Using four datasets of individuals’ digital payment and mutual fund investment records from a dominating fintech platform, we observe a robust U-shaped relation between individuals’ consumption and their financial wealth shocks. Contrary to the prediction of the wealth effect, individuals increase their consumption shortly after experiencing large positive and negative wealth shocks. The unexpected increase in consumption following negative wealth shocks is particularly pronounced among consumption categories with a “hedonic” nature, such as entertainment-related items. We show that this effect, termed “financial retail therapy,” is consistent with a dynamic model of Prospect Theory and evidence from a controlled laboratory experiment.

We document a novel platform effect caused by the emergence of FinTech platforms in financial intermediation. In China, platform distributions of mutual funds emerged in 2012 and grew quickly into a formidable presence. Utilizing the staggered entrance of funds onto platforms, we find a marked increase of performance-chasing, driven by the centralized information flow unique to FinTech platforms. This pattern is further confirmed using proprietary data from a top platform. Examining the platform impact on fund managers, we find that, incentivized by the amplified performance-chasing, fund managers increase risk taking to enhance their probability of getting onto the top ranking.

This paper studies the economic impact of the emergence of FinTech platforms on financial intermediation. In China, platform distributions of mutual funds emerged in 2012 and grew quickly into a formidable presence. Utilizing the staggered fund entrance onto platforms, we find markedly increased flow sensitivities to performance. Akin to the winner-take-all phenomenon in the platform economy, net flow captured by top 10% performing funds more than triples its pre-platform level. This pattern of platform-induced performance chasing is further confirmed using private data from Howbuy, a top platform in China. Consistent with this added incentive of becoming top performers in the era of large-scale platforms, fund managers increase risk taking to enhance the probability of becoming top performers. Meanwhile, organizational cohesiveness of fund families weakens as platforms level the playing field for all funds.

Using a unique FinTech data containing monthly individual-level consumption, investments, and payments, we examine how FinTech can lower investment barriers and improve risk-taking. Seizing on the rapid expansion of offline usages of Alipay in China, we measure individuals’ FinTech adoption by the speed and intensity with which they adopt the new technology. Our hypothesis is that individuals with high FinTech adoption, through repeated usages of the Alipay app, would build familiarity and trust, reducing the psychological barriers against investing in risky assets. Measuring risk-taking by individuals’ mutual-fund investments on the FinTech platform, we find that higher FinTech adoption results in higher participation and more risk-taking. Using the distance to Hangzhou as an instrument variable to capture the exogenous variation in FinTech adoption yields results of similar economic and statistical significance. Focusing on the welfare-improving aspect of FinTech inclusion, we find that individuals with high risk tolerance, hence more risk-taking capacity, and those living in under-banked cities stand to benefit more from the advent of FinTech.