Case · 03 / LQX dashboard
LQX dashboard
- Equity management
- Presale proposal
- Pipeline analytics
- Risk monitoring
My role
Research and synthesis of lender workflows and KPIs based on initial data. Translation of complex loan and risk metrics into a coherent dashboard logic through iterative prototyping and stakeholder validation.
Outcome
Decision-oriented dashboard framework visualising loan pipeline performance, portfolio health, risk exposure, and LTV distribution that enables lenders to monitor trends and take informed portfolio actions.
01
Overview
This project focused on designing data-driven lender dashboards for an AI-powered mortgage platform, translating complex loan and risk data into clear, actionable insights for informed lending decisions.
02
Process
Step 01 / 06
The process
Studied the initial input from the team — a raw ChatGPT conversation outlining core workflows and personas based on workshop with the client. Extracted key details, clarified scope, and defined dashboard directions.
03
Wireframes
Mapping the structure
After a few iterations, I landed on wireframes that offer clearer visual grouping, refined chart readability, and better balance between numerical data and interactive controls for lenders.
Final iteration04
UI
Elements
Building the surface
05
Final
Solution
Decision-oriented dashboards
06
Summary
Final thoughts
This project highlighted how thoughtful design can turn complex financial data into clarity and confidence for users. Collaborating closely with stakeholders to align product goals, data priorities, and user needs reinforced the importance of iteration and feedback. It showed that great dashboard design isn't just about visualization — it's about creating shared understanding between lenders, data, and decisions.
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