Adoption Factors of FinTech: Evidence from an Emerging Economy Country-Wide Representative Sample

Abstract

Adoption factors of Financial Technology (Fintech) services have been the subject of investigation in a growing body of extant literature. Macro-level as well as user-specific factors that contribute to the adoption of customer-facing fintech services have been studied. Emerging market studies mostly considered targeted demographic and socio-economic segments, limiting their ability to reflect a wide spectrum of relevant factors. We conducted a nationwide representative survey of 1282 individuals in Bangladesh. A total of 16 administrative districts from all 8 administrative divisions were included. Addressing sample imbalance with Synthetic Minority Oversampling Technique (SMOTE), we deployed Recursive Feature Elimination (RFE) to reduce number of customer features down to the most important. Using Library of Large Linear Classification (LIBLINEAR) for multivariate Logistic Regression, we identified significant features that predict customer-facing fintech adoption among individual respondents. We found that customers were less likely to adopt fintech services if they had higher reported levels of concern with security, information secrecy, limited government control, and high levels of reported service intuitiveness obstacles. Our evidence suggests these concern factors constitute the prominent factor behind fintech adoption, as opposed to demographic variables, for example. Our findings hold insights for fintech services providers and policy makers.

Expediting financial inclusion in Tanzania using FinTech: the perspective of diffusion of innovation theory

“…Findings show that complexity has a negative influence on the adoption of FinTech adoption. This finding is consistent with previous studies, which also found that complexity negatively influences the adoption of FinTech (Anouze and Alamro, 2019; Hwang and Kim, 2018; Mahmud et al ., 2022). This finding suggests that FinTech services should be easy to use to attract more people to adopt them.…”

Social and facilitating influences in fintech user intention and the fintech gender gap

“…Furthermore, according to the UTAUT2 model, sociodemographic variables such as age, income and experience have been hypothesised to moderate the effect of fintech on behavioural intention [ 20 ]. Mahmud et al [ 37 ] found that the Fintech adoption rate was higher among the young and males, meaning that the number of females accessing fintech services was lower than that of males, thus indicating a gender gap.…”

Determinants of FinTech Service Utilization and Access Factors: Case of Palestine

“…Scholars have attempted to analyze this behavior from multiple angles, including Ajzen's (1991) theory of planned behavior (TPB). Khanal Mahmud et al 2023). This study used three behavioral factors to investigate customers' behavioral effects on access to and usage of FinTech services:…”

“…for example, used TPB to investigate the impact of behavioral intention, attitude toward behavior, and perceived behavior on customer satisfaction. Other researchers have combined trust with other variables to re ect customers' behavior toward technology applications, digital payments, and FinTech services(Hassan et al 2023;Kurniasari et al 2022;Nathan et al 2022;Mahmud et al 2023…”