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Client
InvestSuite (Interview Challenge)
Role in project
Product Designer Candidate
Scope
AI-powered search journey (6 screens)
Duration
2 days
About this project

Designing an AI-powered investment search for a fintech platform.

A product design challenge centered on building an AI-assisted search experience that balances automation with trust in a fintech context.

The Challenge

The brief asked me to reimagine investment search using AI. The challenge was translating natural, imperfect queries (like “green ETFs under 0.2% fee”) into structured financial results, while maintaining clarity and trust in a fintech environment.

The Approach

I framed the AI as an investment guide rather than a hidden filter. The flow makes its reasoning visible through parsed intent chips, result explanations, and guided personalization, ensuring the experience feels intelligent, transparent, and trustworthy.

Understanding user intent
Investment search is rarely precise. Users express goals, not taxonomy: “low risk,” “green,” “dividend income.”

The first step was identifying how natural language could be translated into structured financial filters without overwhelming the user with complexity.
Translating language into filters
I mapped potential queries into interpretable components:
• Asset type
• Risk level
• Fee structure
• Sustainability criteria
• Performance goals

The system parses intent and reflects it back through visible chips, allowing users to validate or adjust the interpretation.
Making AI explainable
Trust is critical in fintech. Instead of hiding AI logic, I designed the interface to show how results were generated, through “Why this matches” explanations and transparent filter states. Users don’t just see recommendations; they understand them.
Guided personalization
After presenting results, the system shifts from search to guidance. The AI invites users to refine preferences like risk level in a lightweight, conversational way, turning the experience into a collaborative investment guide rather than a static filter tool.
Designing for edge cases
AI search must handle ambiguity and failure.

I designed responses for:
• No results found
• Overly broad queries
• Conflicting constraints

Rather than showing empty states, the system suggests refinements to guide users forward.
Potential business impact
An intent-based, explainable search experience could improve product discovery and reduce friction in investment decisions.

Visible AI reasoning and guided refinement may increase engagement and strengthen user trust.

Forecast estimates based on industry benchmarks and AI-assisted modelling.

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