Fintech Adoption and the Future of Banking in India: A Predictive Modeling Approach

Abstract

This research paper investigates whether customer adoption of FinTech/digital banking services can be predicted based on demographics, income, awareness, trust, and usage patterns. Using survey and synthetic datasets, predictive models such as Logistic Regression, Random Forest, and XG Boost are applied to determine adoption likelihood. Findings reveal that trust and awareness are primary determinants, followed by income and age. The model can help financial institutions identify high-probability adopters and design targeted campaigns. The study has strong industry relevance, providing actionable insights for digital transformation strategies in banking and fintech.