The challenge
Insurance products contain dense terminology, several decision points and sensitive personal data. The interface needed to make complex coverage information understandable without removing the detail that customers and agents rely on.
Life Insurance Platform
A comprehensive life insurance platform designed to simplify complex policy management. The process involved deep user research with policyholders and agents, resulting in an intuitive dashboard that leverages AI for personalized risk assessment and coverage recommendations.
My Role
The brief
Designing for people and business.
The brief was to rethink how first-time policyholders understand and manage life insurance. The business opportunity was to reduce support dependency while helping customers identify coverage gaps in a responsible, transparent way.
Key constraints
- Complex regulatory and insurance terminology
- Sensitive financial and health information
- AI recommendations needed explainability and user control
The solution
A modular dashboard organizes policies, recommendations and next actions around the user’s priorities. Progressive disclosure keeps the first view simple, while contextual AI guidance helps people understand risk and coverage options.
The impact
The concept creates a clearer path from policy overview to decision-making and establishes a scalable foundation for new products, recommendations and self-service journeys.
Approach
From complexity to clarity.
- 01User Research & Personas
- 02Information Architecture
- 03AI Integration Strategy
- 04High-Fidelity Prototyping
Discovery
Evidence before interface.
6 contextual interviews, competitor review, support-ticket analysis and a card-sorting exercise with 12 participants.
Users did not think in terms of policy modules. They wanted answers to three questions: Am I protected, what changed and what should I do next?
Reframe the dashboard around life events and protection status, while keeping policy-level details available on demand.
Design rationale
Decisions, not decoration.
Protection score with context
Instead of presenting an unexplained AI score, the interface shows the factors behind it, the data used and actions the customer can choose to take.
Progressive disclosure
Coverage details are grouped into scannable summaries, with definitions and exclusions revealed only when the user asks for more depth.
Human handoff by design
High-impact recommendations include a clear route to an adviser, ensuring automation supports rather than replaces informed decisions.
Iteration
The work evolved through feedback.
Two moderated usability rounds with 5 participants each. After the first round, I replaced insurance-led labels with customer language and moved the recommendation rationale into the primary flow.
OutcomeQuantitative outcomes are not currently available for public disclosure.
Selected screens
Inside the experience.
What I learned.
Trust was not created by making AI appear smarter. It improved when users could inspect its reasoning, correct inputs and reach a human specialist. In a next iteration, I would test the experience with a broader range of ages and accessibility needs.