AI-Powered FinTech Adoption in India: A Comparative Study of Paytm and Groww

Abstract

The incorporation of Artificial Intelligence (AI) into the financial technology (FinTech) industry has significantly changed the interaction between users and digital financial platforms. This research examines customer views and adoption patterns concerning AI-driven services—like tailored robo-advisory, automated fraud detection, and chatbots—in two prominent Indian FinTech platforms: Paytm (mobile payments) and Groww (investment services). Employing a descriptive and comparative research framework, primary data was gathered from a sample of university students in Himachal Pradesh (N = 122). The research tool exhibited strong internal consistency (alpha = 0.88). Inferential statistical analysis, such as regression and independent samples t-tests, shows that perceived utility (beta = 0.565, p < 0.001) along with institutional trust are the key factors influencing user satisfaction and platform adoption. Notably, the results indicate a \"Privacy-Convenience Paradox,\" where elevated digital literacy fails to reduce perceived data security risks, even with ongoing platform engagement. The research offers important revelations for financial service providers, indicating that although utility encourages adoption, lasting retention hinges on connecting technological ease with data privacy.

Introduction

The text examines the growing integration of Artificial Intelligence (AI) in the FinTech sector and its influence on consumer perception, trust, and adoption in India. AI-powered FinTech is transforming financial services by enabling personalized, efficient, and scalable solutions such as fraud detection, automated credit assessment, chatbots, robo-advisory, and predictive analytics. In India, platforms like Paytm and Groww illustrate this shift—Paytm using AI mainly for payment security and risk management, and Groww applying AI for investment recommendations and advisory services. Despite rapid adoption, empirical research on how Indian consumers perceive AI-driven features and how these perceptions affect behavior remains limited.

The literature review shows that prior studies largely focus on platform growth, usability, backend automation, or general FinTech adoption, with limited emphasis on AI as a front-end experiential factor shaping trust and satisfaction. Research highlights benefits such as convenience, speed, and personalization, while also noting concerns around data privacy, algorithmic opacity, and digital literacy. The review identifies a clear research gap in understanding how AI transparency, trust, and user control influence sustained FinTech usage in the Indian context.

To address this gap, the study compares AI adoption patterns between Paytm (payments) and Groww (investments) among university students in Himachal Pradesh. Using a quantitative, descriptive, and comparative research design, primary data were collected through a structured questionnaire from 122 respondents. Statistical tools such as Cronbach’s Alpha, regression analysis, and t-tests were employed to test hypotheses related to perceived usefulness, trust, digital literacy, and adoption intentions.

Key findings indicate high daily usage of FinTech apps among Gen-Z users, with payment platforms like Paytm showing near-universal adoption, while investment platforms like Groww remain underutilized. AI features are positively associated with transaction speed, ease of use, and user satisfaction, though adoption of AI-driven investment services is still at an early stage. Overall, the study underscores AI’s growing role not just as a backend enabler but as a critical factor shaping user experience, trust, and adoption in India’s FinTech ecosystem.

Conclusion

This study concludes that AI is the primary catalyst for FinTech satisfaction among Gen-Z students. However, adoption is currently \"transaction-led.\" For platforms like Groww to achieve the same ubiquity as Paytm, they must leverage AI to lower the financial literacy barrier.

References

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Copyright

Copyright © 2026 Nishtha Maheshwari, Jai Singh Panwar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.