In recent years, fintech has exploded in popularity and importance in the finan- cial industry. Its impacts have spread widely throughout the world, including Vietnam. This study aims to investigate the effect of fintech’s development on bank performance in Vietnam. Based on the unstructured data about fintech on the financial expert web- sites from Vietnam, the word frequency statistic technique of the text mining approach is applied for measuring fintech’s development under the support of Python-based solu- tions. The bank-level data of 15 Vietnamese banks for the period from the first quarter of 2019 to the second quarter of 2021 are collected from the quarterly financial statements in the Vietstock organization. Python programming and text mining techniques are used to compile this dataset by gathering information from popular and relevant websites. The generalized least squares method is used for estimating the panel models. The estimation result shows the significant impact of fintech’s development on bank profitability, but the net interest margin does not associate with the fintech variable. Besides, some interesting findings are revealed: The slow banking transformation to adapt to the rise of fintech and the COVID-19 pandemic increased bank profitability. Furthermore, suggestions for the banks and fintech companies are recommended, and the limitations and directions for further research are also proposed.