Biography
Daniel Tan is a post-exit founder, scholar-practitioner, adjunct faculty member, financial services veteran, trainer, speaker, film and TV actor, and standup comedian. He brings a rare blend of abilities as a scholar-practitioner with emotional intelligence at the core. With over 30 years as an award-winning entrepreneur, corporate trainer, adjunct lecturer, and senior financial services leader, he bridges real-world execution, academic rigour, and authentic human connection. As Managing Director and Co-Founder of Click Colours Singapore, he designs practical, results-driven corporate learning programmes grounded in the company's proprietary behavioural framework. He currently serves as Global Professor of Practice at Golden Gate University and Adjunct Professor at European City University Paris. He holds a DBA from Golden Gate University, San Francisco, with concentrations in Leadership, Consumer Behaviour, and Artificial Intelligence (AI). He serves as an Adjunct Lecturer in Singapore and has published journal articles and book chapters on AI, trust, and decision-making.
Conference contributions 1
NAVIGATING THE DIGITAL FINANCIAL FRONTIER:
Generation x's perceptions of SGFinDex in Singapore's retirement planning ecosystem
Singapore's demographic landscape is increasingly defined by the dual pressures of an accelerating ageing population and a critically low fertility rate, necessitating a strategic shift toward individualised retirement adequacy. Within the "Smart Nation" framework, the Singapore Financial Data Exchange (SGFinDex) was established as the world's first foundational public digital infrastructure to resolve data fragmentation for the "sandwich generation" (Generation X). This qualitative study examines the perceptions of this cohort (born 1965–1980) through three semi-structured focus groups and reflexive thematic analysis. The findings reveal five core themes: Visibility Without Guidance identifies a structural lacuna between data consolidation and the "algorithmic production of meaning" necessary for actionable retirement insights; Trust as Context suggests that while high institutional trust serves as a baseline, it remains decoupled from the perceived security of downstream data usage by private entities; Usability Friction highlights barriers in re-linking requirements and mobile interface habits; Fragmentation Anxiety illustrates how partial data integration creates a significant "cognitive burden"; and Advisor Mediation positions human intermediaries as essential "adoption multipliers." These results expand the Technology Acceptance Model (TAM) by critiquing "pure" digital-only governance models. As the MyMoneySense application is decommissioned, this research advocates for the integration of Human-AI hybrid models and Explainable AI (XAI) to provide the interpretive guidance currently missing. By addressing the intersection of social responsibility and digital governance, the study offers a critical perspective on how public trust in technological solutions is maintained through mediated interaction within complex socio-technical systems.