Allegra: An AI-Driven Fintech Interface Design Study

Note: Allegra is a design study, not a deployed product. The deliverable is UI mockups and prototype code (a proof of concept), not a live trading platform. This analysis is aimed at advanced retail traders (retail-pro users).

The Design Problem

Retail trading platforms (e.g. TradingView, IBKR, Thinkorswim) cram the screen with charts and widgets to serve power users. Every pixel is used. When new AI features appear, they often just add a chat sidebar and call it “AI-powered.” The result feels tacked on and confusing.

The Allegra study asks: What if the interface is designed AI-first? We assumed most interactions would be through conversation and one-tap suggestions rather than manual chart tweaks. The goal was to respect traders’ familiar workflows while making AI the active co-pilot, not a hidden feature.

Design Decisions

Layout – Chart on left, AI panel on right

On desktop we use a 50/50 split. The price chart stays front and center; the AI doesn’t replace it, it accelerates interpretation. The right panel holds query input, AI explanations, signal cards, and action confirmations. On mobile, we collapse these into tabs (chart is the default).

Action confirmation pattern

Whenever the AI recommends a trade (for example, “buy 100 shares of X at $Y”), we show a clear preview before execution. This preview lists order details, the AI’s reasoning, and any inferred risk or context. The user must explicitly confirm – there is no automatic execution. In short, AI speeds up analysis, but the user always commits the trade. This is mandatory for compliance and builds trust.

Honest risk display

We surface risk info alongside each suggestion instead of hiding it. Position size, potential drawdowns, and worst-case losses appear inline. Warnings are written plainly (for example, “If the trade goes wrong, you could lose a few percent of your portfolio.”) instead of legal boilerplate. Clear language here is more likely to be read and understood.

Progressive complexity

Expert traders like dense data, but newcomers get overwhelmed. Our default view is simple – one chart, one watchlist, one AI panel. As users engage more, they can add widgets and charts. This progressive disclosure lets the same product serve novices and pros without scaring anyone off at first.

Dashboard displaying rewards and investment statistics for Allegra, including available rewards, total earned, total withdrawn, and referral rewards. Visual elements include a bar graph and options for withdrawing or compounding rewards.

What We Built

UI component library: ~80 components covering charts, watchlists, order entry, AI chat, etc.
Prototype pages: HTML/CSS mockups of the main desktop view and mobile layout.
Sample widgets: AI suggestion cards, order preview screens, risk-visualization charts, and chat-driven query UI.
Accessibility specs: High-contrast mode, keyboard shortcuts, and screen-reader support for charts.

A trading dashboard displaying portfolio balance, total investment, ROI earned, and total withdrawal amounts, featuring graphs and market sentiment indicators.

Key Takeaways

AI-first interface: Allegra shows that an AI-driven fintech tool doesn’t have to be just a chatbox. The AI can be the main workspace, with the price chart as context.
Confirmation builds trust: Detailed pre-trade confirmations (with reasons and risk) keep the human in control and build confidence. Well-designed previews don’t feel like a delay.
Plain language matters: Being upfront about potential losses is a design choice. Users notice a clear warning much more than they do fine-print disclaimers.

What this study showed us

AI-driven fintech doesn’t need to look like a chatbot bolted onto a trading platform – the AI can be the workspace, with the chart as the primary contextual surface. Action confirmation patterns are the highest-trust design pattern in the AI-finance category, and they don’t have to feel friction-y if the preview itself is information-dense and useful. Regulatory honesty is a design choice, not a legal one; the language matters more than the legal team usually realizes.

Want a similar concept exploration?

EtherLabz can run paid design sprints for fintech and AI-powered products. [Book a discovery call] to explore a similar concept for your project.

Disclaimer: This study was conducted by Sanya and the EtherLabz team. Allegra is only a concept for design exploration, not a real trading product. Nothing here is financial advice or a regulated service.