SimInvest
Designing a decision-support tool for brokers to communicate the value of a capital guarantee on an investment in live client consultations.
Fintech
B2B2C
UX/UI
This case study is based on professional experience in a regulated enterprise environment. Visuals have been deliberately generalized and simplified. The content reflects my design approach and decision‑making.
Role
Lead Product Designer
(sole designer, led design end-to-end)
Team
Platform
Desktop
Duration
4 months
Intro
Turning a communication problem into a decision-support tool
Brokers had to sell an investment paired with a capital guarantee, but clients struggled to see what the guarantee actually protected. Advice varied from broker to broker, and preparing each session took 1–2 hours.
As the sole product designer, I turned the brief into a live decision-support tool in 4 months.
Impact 2
Prep time: 1–2 hours → minutes
Broker-reported: they stopped building scenarios before every consultation, and now set them up live, with the client.
Context
The problem
Why it mattered
The capital guarantee was the product's main value, but it is hard to explain to retail investors. The business wanted to digitalise advisory sessions, make advice consistent across brokers, and improve uptake of the guarantee product.
Regulatory constraints
As a regulated retail investment, the tool had to show the plan's past performance and carry mandatory warnings that simulated outcomes are not a reliable indicator of future performance. The warnings sat directly below the graph, and past performance had its own view, separate from the forward scenarios. Compliance reviewed and signed off the warnings and plain-language summaries.
Research
Where consultations broke down
Broker consultation journey analysis, based on existing product documentation and conversations with brokers about where clients got stuck
Main Findings
Finding 3
High preparation, low flexibility
Brokers spent 1–2 hours building scenarios before each consultation, then couldn't adapt them when the client asked something new. They found it time-consuming and frustrating.
The problem wasn't the product: it was the absence of a clear visual reference during the conversation. Brokers and clients had no common ground to explore outcomes together.
My role
How I solved it
Discovery
The brief was open: build a tool to help brokers sell the product. Starting from the known broker struggles, I worked with the PM to map where consultations broke down, then turned this into a clear problem and design direction.
Design
I led concept development and direction, owning the interaction model and the feasibility dialogue with developers.
Alignment
I worked closely with the PM, brokers and developers to bring product, commercial and client perspectives together.
Validation
Before handoff, I ran informal sessions with two brokers to sense-check clarity and usability. Both responded positively to the comparison framework and the visual language.
Design direction
From insight to direction
The findings pointed directly to three design principles that became the foundation of the solution.
Guaranteed and non-guaranteed outcomes on one graph: the gap between them shows what the guarantee protects.
The framing I pushed back on
The PM wanted two separate graphs, one for the guaranteed outcome and one for the non-guaranteed. I pushed back: in separate views, brokers couldn't clearly show the difference, or the benefits and trade-offs of the guarantee, and non-expert clients could easily misread it. I proposed a single graph showing both, so the gap between the two outcomes shows what the guarantee is worth. It also kept the comparison fair and clear, which is what regulators expect. Brokers later named this the most valuable part of the tool.
The plain-language summary explains the chart, so clients don't have to read the numbers alone.
Brokers change the scenario during the session, and the graph updates as they go.
Reflections
What I learned
Designing SimInvest reinforced that financial tools are fundamentally about trust.
In advisory contexts, clarity directly affects credibility and decision confidence; it is not just a usability goal.
This project strengthened my approach to designing systems that make complex concepts understandable and trustworthy for non-specialist users.
What worked well
Designing for the conversation, not the screen
Treating the live consultation as the real use case shaped every decision, from live scenarios to plain-language summaries.
Turning regulation into a design input
The required warnings and negative scenarios weren't obstacles. The crisis scenario became the clearest argument for the guarantee.
What I'd do differently
Involve end clients
The process was broker-led throughout, but I had no access to the end clients. For the future, I would involve them.
Agree success metrics up front
Impact was based on broker feedback. Today I'd agree metrics like guarantee uptake with the PM before launch, so impact can be measured beyond adoption.
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