This paper aims to study the impact of FinTech development on the liquidity mismatch of commercial banks.
This paper builds a commercial bank’s FinTech development index based on the annual reports using text learning and machine learning techniques. It empirically investigates the relationship between banks’ FinTech development level and their liquidity mismatch and corresponding mechanism using a fixed-effects regression model. The panel data of 146 Chinese banks span the years 2009–2023.
Empirical results show that higher bank FinTech development correlates with lower liquidity mismatch, achieved through increased non-interest income, expanded credit scales and improved risk management. Joint-stock banks are most affected, followed by state-owned, rural and urban commercial banks. Banks with FinTech subsidiaries also experience lower liquidity mismatches. Furthermore, the asset side’s liquidity mismatch is more sensitive to FinTech development, demonstrating a clear single-threshold effect.
This paper adopts a novel research perspective to focus on the impact of FinTech on bank liquidity mismatch to fill the knowledge system of relevant research. It provides the theoretical basis and practical guidance for banks to use FinTech to improve liquidity management. It points out that banks should solve liquidity problems and improve operations by investing in technology, optimizing business structure, expanding credit scale and enhancing risk tolerance.
