*Result*: Cybersecurity in Digital-Only Banks; How Entrepreneurs Are Shaping India's Digital Finance Ecosystem.

*India's financial landscape is undergoing a radical transformation driven by digital-only banks and fintech innovators. By leveraging Digital Public Infrastructure (DPI) and the "India Stack," these entities provide accessible, simplified, and high-speed banking services to millions. However, this rapid transition has expanded the attack surface, exposing the ecosystem to sophisticated threats such as AI-driven phishing, ransomware, and identity-centric frauds. As India moves toward a digital economy projected to contribute 20% of its GDP by 2026, the intersection of cybersecurity and user trust has become the primary frontier for financial stability. This case study investigates the application of advanced cybersecurity frameworks--specifically Zero-Trust Architecture (ZTA), multi-factor authentication (MFA), and AI-powered threat detection--within the digital-only banking environment. It highlights the pivotal role of entrepreneurs and innovators who are moving beyond mere regulatory compliance to foster a "secure-by-design" philosophy. These leaders are integrating behavioral analytics and end-toend encryption to safeguard the 48.5% share of global real-time payments that India now commands. Furthermore, the study incorporates user surveys and case studies (including data from 2024-2025) to analyze consumer behavior and awareness. Findings indicate that while trust in digital platforms is rising, a significant "awareness gap" remains regarding personal cyber hygiene. The research concludes that the sustainability of India's digital finance ecosystem depends on a collaborative model where entrepreneurs, regulators like the RBI, and consumers work in tandem to build a transparent, resilient, and fraud-resistant financial future. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Consumer Research is the property of Association for Consumer Research and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)*