Monte Carlo Simulation-Driven Quantitative Model of Dual Effects of Bank Operational Efficiency and Risk Management in FinTech

The rapid development of financial technology has had a profound impact on traditional banking, particularly in terms of improving operational efficiency.This paper collects publicly disclosed data from 35 listed banks between 2015 and 2024 and uses the EBM model to measure the operational efficiency of banks under fintech.Through literature review, appropriate input and output indicators are selected to calculate the Malquist index for the sample banks.Additionally, regression analysis is employed to conduct an empirical analysis of the impact of fintech on bank operational efficiency.The average total factor productivity of the sample banks from 2015 to 2024 was above 1, with an annual improvement rate of 19.44%, and technological efficiency was the primary factor driving this improvement.Additionally, state-owned large banks had the highest operational efficiency growth rate at 31.2%, while national joint-stock banks and city banks had growth rates of 17.7% and 9.3%, respectively.The intensity of fintech investment and the outcomes of fintech application significantly enhance banks' total factor productivity and technological progress.The coefficients of the impact of fintech application outcomes on the overall operational efficiency, technological progress index, and technical efficiency of state-owned large banks are 0.171, 0.164, and 0.017, respectively, indicating a significant positive effect.