Work place: Department of Management Studies, Sri Manakula Vinayagar Engineering College, Pondicherry, India
E-mail: arivazagan@gmail.com
Website: https://orcid.org/0000-0002-1452-7650
Research Interests:
Biography
Arivazagan Jayabalan is an Assistant Professor in the Department of Management Studies at Sri Manakula Vinayagar Engineering College, Pondicherry. He holds a Ph.D. in Management with a specialization in Banking Technology (Interdisciplinary). With over 15 years of professional experience and 5 years in academia, he brings both industry and teaching expertise to his work. His research interests span Finance, FinTech, Entrepreneurship, Strategic Management, Logistics and Supply Chain Management, International Business, and Corporate Governance. A certified Entrepreneurship Educator, he has published articles in peer‑reviewed journals indexed in ABDC, UGC‑CARE, and Scopus.
By Arivazagan Jayabalan Shahrukh Saleem Prem Kumar Sudalaimuthu Shanmugam
DOI: https://doi.org/10.5815/ijieeb.2026.02.10, Pub. Date: 8 Apr. 2026
The rise of FinTech lending in India has transformed credit access, yet studies examining customer experiences with artificial intelligence (AI)-enabled FinTech lending platforms remain limited. This study investigates the key drivers of user experience and the evolving sentiment toward AI-enabled lending platforms by analysing online reviews from 2017 to 2024 using LDA topic modelling and lexicon-based longitudinal sentiment analysis. Twelve key topics emerged, revealing significant negative sentiment around customer support, eligibility checks, documentation, repayment, and app trustworthiness. In contrast, app usability and interface design maintained strong positivity, while loan approval and disbursement processes saw declining sentiment. Despite these pain points, overall user experience remained positive, indicating that the perceived benefits such as speed, efficiency, and convenience provided by these platforms outweighed concerns like high interest rates, privacy risks, and poor customer service. The findings highlight a nuanced balance between technological advantages and operational shortcomings, offering insights for improving AI-enabled lending platforms.
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