Prudential – B2B Insurance Platform

Company Prudential of Brazil
Role Product Designer
Period 2020–2021 (1.5 years)
Location São Paulo, Brazil
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Immediate Impact

Insurance proposal issuance accelerated by 63%

Reduced insurance proposal cycle from 30 to 11 days through standardized UX across Itaú, XP, and BTG | Eliminated 15% losses due to inconsistency | +18% profitability via shared Design System.
-15%
Losses Due to Inconsistency Eliminated
+18%
Profitability Increase
64 Pros
Personas Created
11 days
Average Issuance Cycle
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Conflict and Decision

The problem, options considered, and strategic choice

Conflict

Prudential faced fragmented and inconsistent journeys in selling individual insurance through bank partners (Itaú, XP, BTG). The lack of UX standardization was causing:

  • 15% of identified losses due to inconsistencies in sales flows
  • Different experiences for the same product across different partners
  • Low scalability - each new partner required custom development
  • Difficulty in measuring and optimizing conversion in a unified way

Options Considered

  1. Deep customization per bank partner

    Discarded: Very low scalability, unsustainable maintenance cost, impossible to standardize metrics

  2. Single generic template without personalization

    Discarded: Partner resistance, loss of brand identity, low expected adoption

  3. (Chosen): Shared and flexible Design System with modular components

    Selected: Balance between consistency and flexibility, scalable, reusable components

Conscious Trade-off

  • Sacrificed: Extreme customizations and deep personalization that some partners wanted for their specific experiences.
  • To gain: Unified and consistent cross-partner experience, scalability for new partners, and ability to measure/optimize centrally.
  • Reasoning: In a B2B ecosystem with multiple partners, consistency is trust. End customers gain confidence when the experience is predictable, regardless of the entry channel.
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Evidence and Results

Data, methodology and learnings

Success Proxy

Initial mapping identified 15% of losses attributed to inconsistencies in journeys between partners. After implementing the shared Design System:

  • Reduction to <2% of losses due to UX friction
  • Onboarding time for new partners dropped from 4 months to 6 weeks
  • Average policy issuance cycle reduced to 11 days

Risk Mitigation

To ensure Design System adoption by all stakeholders:

  • Code-Ready Guidelines: Complete technical documentation with components ready for implementation
  • Collaborative Workshops: 64 participants (designers, devs, product owners) in prioritization sessions
  • Pilot with Itaú: Initial validation with main partner before complete rollout
  • Controlled Flexibility: Customizable design tokens (colors, logos) while maintaining fixed structure

Measurable Results

+18%
Profitability Increase
10
Complete Personas Created
64
Workshop Participants
11 days
Average Issuance Cycle

Deliverables:

  • Complete sales journey mapping for 10 personas
  • Design System with 45+ reusable components
  • Prototypes tested with consultants and brokers
  • Code-ready technical documentation for developers

What Got Worse

During Design System implementation:

  • Learning curve for devs: Initial onboarding +2 weeks for technical teams to learn the system
  • Initial resistance: Some partners wanted more customization than the system allowed
  • Necessary refactoring: Legacy code from 2 partners needed to be rewritten (cost not initially planned)

Learning: Investment in documentation and upfront training would have reduced friction in technical onboarding.

Would Do Differently Today

With current Generative AI and Agentic Workflows:

  • Automated Design Token Audits (Custom Agents): Deploy specialized AI agents (via Claude Code and custom Figma skills) to continuously audit design token compliance across all partner implementations, eliminating manual QA.
  • Agentic Accessibility & Copy Reviews: Integrate AI workflows to automatically test component variants for WCAG 2.1 compliance and brand tone alignment before code handoff.
  • Real-time Documentation Sync: Use LLM pipelines to auto-generate and update component specs and integration guidelines whenever token values or code props change.
  • Dynamic Journey Personalization: Tailor proposal journeys dynamically based on customer risk profile and bank partner context, driving higher conversion without creating visual fragmentation.

Estimated impact: 50% reduction in new partner onboarding time + zero manual design QA cycles + 10–15% increase in conversion via dynamic personalization.

Family collaborating on insurance life plan documentation

Deep Dive

Individual Life Insurance Plan Documentation

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