The role of FinTech in enhancing bank loan performance in Bangladesh through the UTAUT model

This paper discusses how Financial Technology (FinTech) can perceived improvement in loan performance within the Bangladesh banking industry through the Unified Theory of Acceptance and Use of Technology (UTAUT). Structural Equation Modeling (SEM) using SmartPLS and STATA was used based on survey information of 354 professionals in state-owned, private, and specialized banks. The findings indicate that Performance Expectancy (PE), Effort Expectancy (EE), and Social Influence (SI) have strong impacts on the Behavioral Intention (BI) whereas Facilitating Conditions (FC) and BI have strong effects on Use Behavior (UB). Loan Performance (LP) is highly predicted by UB, which proves that the adoption of FinTech enhances the speed of loan disbursement, improved recovery efficiency, and reduced default risks. EE and FC also proved to be the most powerful predictors, which highlights the role of user-friendliness and infrastructural support as the strong force in Bangladesh. Both mediating and direct effects underscore BI and UB as one of the main channels through which adoption can be connected to performance. The analysis expands UTAUT by incorporating LP as an outcome and offers useful insights to banks and policymakers to speed up the process of digital lending.