How do they react to monetary policy?



We investigate how fintech credit, which includes peer-to-peer and marketplace lending, as well as lending by major technology firms, responds to monetary policy changes. This is a relevant question given the rapid growth of fintech credit worldwide, particularly in countries like China, Korea, Malaysia, and Kenya, where it comprises up to 5% of total credit.


We explore the transmission of monetary policy through non-traditional forms of credit by employing a novel credit data set that spans 19 countries from 2005 to 2020. Using panel vector autoregression (PVAR) analysis, we compare the reactions of fintech and bank credit to policy rate changes. We discuss three key differences between fintech and bank credit that could influence their respective responses to monetary policy shocks: the use of data vs physical collateral, distinct regulatory frameworks, and the advanced monitoring and screening capabilities of fintech and big tech lenders.


Our primary finding reveals that fintech credit shows a lower (and statistically non-significant) responsiveness to monetary policy shocks compared with traditional bank credit. This result is consistent with a substitution effect of bank credit with fintech credit in response to a monetary tightening. It also suggests that the “collateral channel” has a limited impact on fintech credit. Concerning its current macroeconomic significance, we document that fintech credit contributes to less than 2% of the variability in real GDP. In contrast, bank credit accounts for approximately a quarter of this variability.


Fintech credit, which includes peer-to-peer and marketplace lending as well as lending facilitated by major technology firms, is witnessing rapid growth worldwide. However, its responsiveness to monetary policy shifts remains largely unexplored. This study employs a novel credit dataset spanning 19 countries from 2005 to 2020 and conducts a PVAR analysis to shed some light on the different reaction of fintech and bank credit to changes in policy rates. The main result is that fintech credit shows a lower (even non-significant) sensitivity to monetary policy shocks in comparison to traditional bank credit. Given the still marginal – although fast growing – macroeconomic significance of fintech credit, its contribution in explaining the variability of real GDP is less than 2%, against around one quarter for bank credit.

JEL classification: D22, G31, R30

Keywords: fintech credit, monetary policy, PVAR, collateral channel

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