Scanner
Designing a stock screening tool for every kind of trader — from first-timers to full-time analysts
Client
Industry
Product Name
TradeVed
Fintech
Scanner
The Brief
& The Ask
TradeVed is a fintech startup building a multi-product trading platform. As the sole designer on the team, I was given a clear but demanding challenge:
Ask: Design a stock screening tool that lets traders filter and discover high-performing stocks — built from scratch, shipped in 10 days.
This was my first time designing for the trading domain. Before I opened Figma, I had to understand the world I was designing for.
Learning the
Domain & Finding Gap
I didn't come in with a trading background. So the first thing I did was ask a lot of questions and immerse myself in the space. I spent time with my team — traders and product leads who knew the domain deeply — learning the vocabulary: what queries actually mean in a screening context, what filters matter to different kinds of traders, and why stock screening tools exist in the first place.
I also explored several live trading and stock screening platforms myself as a real user. The goal wasn't just to see what they looked like — it was to feel what it was like to use them.
What Competitive Research Revealed
I explored the leading stock screening platforms available to Indian traders — tools that are widely used and genuinely powerful. But using them as someone without a trading background was disorienting. The interfaces assumed you already knew what you were doing. There was no hand-holding, no entry point for someone new to the tool, and the query language felt like writing code with no documentation.
The Gap:
Existing screening tools are built for power users. They effectively lock out an entire segment — newer or casual traders who could benefit the most from a tool like this.
This was the opening. If TradeVed's Scanner could serve both experienced traders and beginners within the same product, it would have a clear differentiation in the market.
Defining The Problem- Persona wise
After research, I framed the core design challenge around three distinct user types that the product needed to serve simultaneously:
The Professional Trader
The Intermediate Trader
The Beginner
knows exactly what query to write, wants speed and full control with no friction
understands concepts but wants guidance or a starting point to build from
has no idea how to write a query but wants to explore and learn the tool progressively
A single interface had to accommodate all three without compromising on any. The solution wasn't a different product for each — it was a layered experience that met each user where they were.
Design Descisions
The Query Builder — For the Power User
The core feature is the ability to write custom stock screening queries — filtering by PE ratio, revenue growth, market cap, sector, and dozens of other parameters. For professional traders, this needed to be fast, familiar, and get out of the way.
I designed a clean, structured query builder with a light interface and high-contrast blue accents — intentionally referencing the visual language of trading terminals that professionals are already comfortable with. The inputs are clear, logical, and responsive. There's no clutter between the user and their work.
I also designed a clear empty-state and no-results state — for when a query returns no matching stocks. Rather than a dead end, these states guide the user to refine their query, which is a small but important usability detail that most existing tools handle poorly.
Empty state
Error state
UI components
Components were created post wireframing. There multiple variations of side nav bar was created based on the requirements we realised later.
What I'd Do Differently
With more time, I would have recruited 3–5 actual traders for usability testing — specifically watching beginners use the query builder for the first time to validate whether the progressive disclosure approach (Ready Made → AI Query → Manual Query) actually maps to how they naturally explore the product.I'd also explore onboarding more deeply. The tool is well-designed for users who land on it with some intent — but a thoughtful first-time user experience could significantly increase activation rates for traders who are new to stock screening altogether.
This project taught me that domain fluency is a design skill. Understanding trading concepts — even at a surface level — fundamentally changed the decisions I made. It's something I now actively pursue whenever I enter a new product space.