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

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