Predicting the Impact of Socio-Demographic Factors on Fintech Usage and Adoption

Abstract

Financial technology (FT) has played a crucial role in the delivery of financial services in India, especially in the more digitally advanced areas, such as Thrissur district, Kerala. Although the fintech adoption proliferated quickly, there remains inequality in the adoption of such technologies among socio-demographic classes. The current study examines how sociodemographic traits affect fintech adoption and uptake using the Technology Acceptance Model (TAM). The study design employed was descriptive-analytical. Using Google Forms, a structured questionnaire was distributed to a sample of 312 fintech users in the Thrissur district in order to collect primary data. In order to determine the associations and relationships between sociodemographic variables, perceived usefulness, perceived ease of use, fintech adoption, and usage, the statistical data were analyzed using a spreadsheet program with SPSS, including percentages, chi-square tests, and correlation analysis. The results demonstrate that age, gender, and education do not significantly correlate with the data; nevertheless, occupation (χ² = 123.463, p < 0.000) and income (χ² = 15.750, p < 0.015) are significantly correlated with fintech adoption and usage. The correlation research indicates that the use of fintechs has a strong positive correlation with adoption (r = 0.739) and perceived usefulness and ease of use a (r = 0.725). Moderately positive associations were perceived usefulness and financial usage (r = 0.591) and perceived usefulness (r = 0.566). According to the study, the large impact on the fintech uptake has been on the usability evaluation and social economic stability. The findings can be used to promote fair digital financial inclusion by policymakers and fintech firms.