Role
Product Designer Concept Exploration
Impact
Reduce Friction
Higher Retention
Platform
Neobanks
Timeline
1 month
Executive Summary
Retail investment platforms often struggle because they treat users like professional traders. Most users don't want to pick stock tickers or decode complex risk metrics. They want to achieve specific financial goals, such as building a passive monthly income.
Goals
Design a neobank feature that guides users through investment decisions using a goal-based approach, centered around a desired monthly income and flexible investment horizons.
Highlights
Cognitive overload: Users are asked to choose complex financial instruments (ETFs, bonds, risk profiles) before understanding their potential impact.
Abstract value: Investing €150/month can feel abstract when users can't visualize what their contributions could generate over 10 or 20 years.
Drop-off in onboarding: High friction during initial setup can lead to drop-off and lower conversion from savings accounts to investment products.
2. Strategy & Approach
The core idea was to invert the traditional mental model of retail investing.
Core Design Challenges
Goal-First Architecture: Start with the desired outcome (e.g., “I want €500/month in 15 years”) rather than the asset class.
Interactive Feasibility Feedback: Allow users to adjust their timeline and contribution amounts in real time, with immediate visual feedback.
Progressive Financial Literacy: Introduce financial concepts progressively through contextual, human-readable explanations.
Design Execution & Core Features
3a. The Interactive Target Setup
Process Architecture & Setup Journey: This logic map details the initial onboarding flow, showing how user inputs (target monthly income and investment horizon) are validated in real time by the calculation engine before moving into portfolio selection.
Dynamic Target Slider: Users set their target monthly income and desired investment horizon.
Instant Calculation Engine: Real-time calculations show the required initial deposit and monthly contributions needed to reach the target.
3b. Feasibility & Decision Engine
System Logic: The flowchart illustrates the closed-loop feedback mechanism triggered when user targets exceed market viability. Instead of simply rejecting the goal, the engine generates alternative scenarios and suggests small adjustments to keep it realistic and actionable.
When a goal is mathematically unrealistic based on historical market performance, the app gently nudges users toward actionable trade-offs:
Extend the timeframe.
Slightly lower the target monthly income.
Increase the recurring monthly contribution.
3c. Scenario Modeling & Volatility Visuals
Architecture & Complete User Journey: A macro view of the end-to-end UX architecture, connecting goal discovery, real-time risk simulation, scenario modeling, and portfolio activation through automated recurring contributions.
Expected & Conservative Scenarios: These replace abstract statistics with clear range visualizations that illustrate potential market fluctuations.
Microcopy & Disclaimers: Provides the necessary regulatory disclosures without disrupting the user experience.
Design Screens
Impact & Key Takeaways
Projected & Qualitative Impact
Reduced Friction: Shifting to an outcome-driven flow reduces cognitive load and can improve setup completion rates.
Higher Retention: Goal-oriented recurring investments can encourage long-term investing habits compared with one-off stock purchases.
Increased AUM (Assets Under Management): Clear projections can encourage users to commit to higher monthly contributions.
Learnings & Trade-offs
Simplicity vs. Accuracy: Balancing simple UI controls with realistic representations of market volatility required close alignment across design, product, and compliance.
Handling Extreme Inputs: Designing for unrealistic expectations and extreme inputs was critical to maintaining user trust without increasing drop-off.