Project overview
Nut Finance, a microloan service for emerging markets, approached me to develop their first MVP. Their mission: provide small loans to borrowers without traditional credit in developing regions. The goal was to create assessment surveys powered by data science to predict creditworthiness based on personality responses.
Key users:
- Loan recipients: Users seeking financial assistance, transitioning from applicant to borrowers.
- Loan agents: Employees who assist users in applying for loans.
- Banks: Financial institutions that oversee loan agents and disperse loans.
Key goals:
- Develop an MVP allowing loan agents to survey users in remote areas with limited WiFi access.
- Focus on survey completion and credit score creation for this phase.
- Ensure scalability for multiple international markets.
Team:
- The client team included two product managers and a development team.
- Patty was the sole UX and UI Designer for this project.
Experience mapping
Unraveling a customer lifecycle through understanding the customer journey in the application process.
We started by mapping user flows for the loan application process. As we identified key events, we developed a customer lifecycle that outlined essential stages based on the assessment process. To simplify this concept, we used a metaphor: a user starts as a candidate (caterpillar) and transforms into a borrowers (butterfly) along the way.
This structured framework with defined stages for both the user and the assessment provided default and readily digestible statuses that made filtering and navigation for loan agents simple while ensuring system scalability.
Defining the lifecycle, key event triggers, and user roles shaped the Information Architecture. This step-by-step loan process helped users and agents navigate from application to borrowing throughout any stage and status.
Built for rural environments
Loan agents often worked in low-tech, offline environments, assisting borrowers with varying levels of digital literacy. We considered several different user challenges to support different use cases.. The UI needed to be intuitive, accessible, and simple.
- Offline accessibility → We enabled data storage when offline, with clear sync notifications for when back online.
- Batch data entry for kiosks → Allowed agents to switch quickly between multiple candidates when creating several back to back applications.
- Outdoor visibility → High-contrast design with accessibility requirements met for readability in bright conditions.
- Responsiveness → Mobile-friendly input fields for on the field data entry.
Built for scale
As an MVP, it’s the seed for growth. We feature proofed designs to support multi-market expansion including:
- Internationalization → Established best practices UX writing and internationalization and used Noto font for broad linguistic compatibility.
- Lightweight design system → Defined brand styles and created a component library.
- Consistent UX patterns → Ensured usability interactions across different views.
- Key screen templates → Designed basic templates that supported most use cases.
Result
As the sole UX/UI designer, I helped transformed a logo, pitch deck, and PRDs into their first functional product.
After several iterations, we finalized the designs and prepared them for development. The MVP, built in 2023, integrated a powerful algorithm that converted qualitative data into usable credit scores. It provided loan agents with a structured and accessible interface for evaluating applicants. While intentionally limited in scope, the MVP laid the foundation for a scalable borrower management system and future loan servicing capabilities.
Loan agents were able to collect surveys, analyze applicant data, and manage user profiles. The platform was successfully deployed across Southeast Asia—including Indonesia, Thailand, and neighboring countries—to gather real-world insights.
