Year: 2026
Type: article
Study design: Observational Study
Abstract: This study examines the adoption of digital platforms for distribution of financial products (banking, mutual funds, insurance, loans, and equities), identifies adoption drivers and operational gaps, and documents consumer perceptions that in6luence trust and sustained usage. The analysis is based on a primary survey of 154 respondents collected during a 45-day field period at Rukmani Financial Services, supplemented by secondary literature and statistical testing. Key findings show near-universal engagement with digital channels (reported adoption >97%), with mobile/online banking the dominant use case (≈75%), followed by investments (mutual funds ~41.6%) and insurance (~39%). While overall trust is moderate-to-high (≈65.6% trust digital platforms), security/privacy concerns and occasional service gaps are the leading barriers to deeper adoption. Timesaving, speed and convenience are the principal adoption drivers. Statistical tests confirm a significant association between perceived service gaps and trust (Pearson χ² p = 0.001). Based on the evidence, the paper offers practical recommendations for service providers and regulators: strengthen data-privacy and visible security measures, simplify compliance/ONBOARDING flows, investment in proactive customer support and multilingual UX (User-Experience), and pilot trust-building interventions (verified reviews, government certifications). The report also notes strong user interest in AI-driven personalized advisory and block-chain/biometric security as future enablers. This empirical, practitioner-anchored study contributes to the conference’s Digital Transformation and Innovation track by offering actionable insights on closing the “digitalization gap” in last-mile financial distribution, especially for mid-sized distributors and semi-urban markets.
Authors: Tanmoy Roy, Saugata Chakraborty, Samudyuti Ray
Institution: Brainware University
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7167239244