Designing Hyper-Personalized Financial Co-Pilots
An Artifact for Building Trust through Conversational Advice
Current digital financial advice often fails to build the deep, competence-based trust required for meaningful user adoption. While my previous research highlighted the role of humor and personality in driving engagement, high-stakes domains like finance require a different approach, grounding advice in a deep understanding of the user’s specific goals. To address this socio-technical gap, we are developing a hyper-personalized financial co-pilot using a Design Science Research approach.
The artifact leverages a stateful, session-based memory to ground a Large Language Model’s responses, enabling a deep, conversational understanding of a user’s unique goals. This research aims to contribute a set of refined design principles that address the critical challenges of robustness, institutional transparency, and graceful failure management in trust-aware financial AI.
Working Paper.