Overview
In this project, I worked on Ada Analytics, an AI-powered financial insights platform designed to help users make informed investment decisions.
My primary focus was on research, understanding how users interact with financial data, identifying pain points, and uncovering opportunities to simplify complex information.
The goal was to present AI-driven insights in a way that feels clear, trustworthy, and actionable.
Many financial tools present data in ways that are difficult to interpret, leading to confusion and low user confidence.
My contribution
User research
User interviews
Persona development
Insights synthesis
UX strategy & definition
Scope
John M., UX/UI Lead
Selene D., UX Researcher
Lu F., UX/UI Designer
Dr. Ray H., Founder
James, Data Eng.
Year
2025
Process
Research & Insights
I conducted qualitative user interviews and analyzed existing AI-driven financial tools to understand how users interpret and act on financial data.
A key insight was that users often feel overwhelmed by complex information and need clear, structured insights they can quickly trust and act on.
Strategy
Based on these findings, I defined principles for how financial insights should be communicated more clearly.
I translated research into design principles focused on simplicity, transparency, and reducing cognitive load through clear hierarchy and concise content.
Concept Development
I contributed to shaping how AI-generated recommendations are presented, exploring how to make them more understandable and actionable.
This included defining key interaction moments such as risk selection, recommendation clarity, and follow-up actions.
Outcome
The final concept demonstrates how AI-powered financial insights can be presented in a clear and digestible way.
By focusing on simplicity and structure, the experience helps users better understand recommendations and make more confident decisions.
It highlights how complex financial data can be transformed into a more approachable and user-friendly experience.