Portfolio dashboard
Pipeline volume, approval mix and turnaround trends with drill-through to any case.
CONCEPT
Self-Initiated Concept
Digital Lending Platform
Product Concept / Fintech UX
A concept exploring how a lending platform could pair a plain-language application journey with an underwriter workspace built for decisions, not data entry.
- Product Concept
- Fintech UX
- Enterprise Dashboard
- Decision Support
- Design System
Project overview
A self-directed exploration of digital lending as two connected products: a save-and-resume application for borrowers, and an underwriting workspace where credit signals, risk insights and documents live in one case view.
- Type
- Self-Initiated Concept
- Discipline
- Fintech UX
- Year
- 2026
The opportunity
Most lending interfaces are forms bolted to legacy decisioning. The interesting design problem is not the form — it is presenting a credit picture so a human can make a defensible decision quickly, and telling the applicant the truth while they wait.
The challenge
Regulated products punish ambiguity. The concept had to show risk signals in context without implying automated approval, keep an audit trail visible, and stay legible at the data density underwriters actually work in.
Design approach
- Modelled a service blueprint across applicant, underwriter and risk-review paths
- Studied published lending guidance and accessibility requirements for dense financial tables
- Designed against realistic synthetic case data rather than lorem placeholders
- Tested two workspace layouts — queue-first and case-first — in internal critique
Product strategy
- Design for the decision: surface the signals that change an outcome, suppress the rest
- Give applicants a status they can trust, with the next required action always named
- Componentise regulated patterns — disclosure, consent, audit trail — so they are consistent by default
- One system across application, assessment and portfolio views
FLOWS
User experience
- A four-step application with save-and-resume and requirements stated up front
- Credit assessment shown as a score with the factors behind it, never a bare number
- AI-assisted decision support labelled as a suggestion with the evidence attached
- Status language written for someone who has never read a credit policy
Key user flows
- 01
Apply
Personal, employment and financial sections with inline validation and clear document asks.
- 02
Assess
Score, factor breakdown and risk insight cards assembled into one case view.
- 03
Decide
Underwriter reviews suggestion, evidence and policy checks, then records a rationale.
- 04
Track
Applicant sees stage, expected timing and the exact item blocking progress.
- 05
Monitor
Portfolio dashboard for pipeline, exposure and turnaround trends.
UI exploration
Credit assessment
A score gauge paired with contributing factors and comparison to prior assessment.
Risk insights
Ranked insight cards with severity, prevalence and a link to the underlying rule.
Mobile application
Stepped form with progress, secure-entry cues and a persistent save state.
Design system
- Dense data components: tables, status pills, filter bars and pagination tuned for long sessions
- A financial chart set with consistent axis, legend and empty-state behaviour
- Colour tokens tested for AA contrast on status and severity indicators
- Documented disclosure, consent and audit-trail patterns
Prototype
A connected prototype covering the borrower application on mobile and the underwriter workspace on desktop, including empty, pending, additional-info and declined states.
Tools & technologies explored
- React
- TypeScript
- Storybook
- Design tokens
- Figma
- Synthetic data modelling
Design outcomes
What the exploration produced. No commercial launch, no performance claims — design artefacts and thinking.
A case-first workspace
One column that holds documents, credit signals and policy checks without tab-hopping.
Explainable assessment
A score-plus-factors pattern that keeps the human accountable for the decision.
Honest status
An applicant-facing tracker that names the blocking item instead of a generic 'in review'.
A dense-data kit
Table, chart and pill components that hold up at real record counts.
Key learnings
- Density is a legibility problem, not a spacing problem — rhythm matters more than padding
- A suggestion without evidence gets ignored; with evidence it gets read first
- Status copy is product design; vague waiting states generate the support load
- Regulated patterns are easier to design once, centrally, than to review case by case
Future opportunities
- Collections and servicing views built on the same case model
- Policy simulation: preview how a rule change would shift the pipeline
- Multi-product origination beyond a single loan type
- Deeper accessibility work on dense tables with assistive technology