FinTech Lending, Social Networks and the Transmission of Monetary Policy

One of the main channels through which monetary policy stimulus affects the real economy is mortgage borrowing. This channel, however, is weakened by frictions in the mortgage market. The rapid growth of financial technology-based (FinTech) lending tends to ease these frictions, given the higher quality services provided under this new lending model. This paper establishes that the role of FinTech lending in the monetary policy transmission is further amplified by consumers’ social networks. I provide empirical evidence for this network effect using county-level data and novel identification strategies. A 1 pp increase in the FinTech market share in a county’s socially connected markets raises the county’s FinTech market share by 0.23-0.26 pps. Moreover, I find that in counties where FinTech market penetration is high, the pass-through of market interest rates to borrowers is more complete. To quantify the role of FinTech lending and its network propagation in the transmission of monetary policy shocks, I build a multi-region heterogeneous-agent model with social learning that embodies key features of FinTech lending. The model shows that the responses of consumption and refinancing to a monetary stimulus are 13% higher in the presence of FinTech lending. Almost half of this improvement is accounted for by FinTech propagation through social networks