Amazon

As a UX Design Intern at AWS FinTech, I redesigned the input management experience for financial planning, transforming a third-party legacy system into an AI-enhanced experience within the Uno platform. This details my journey of research, ideation, and design that contributed to AWS FinTech's broader AI transformation initiative.

Uno is AWS FinTech's central portal that provides a unified experience by intelligently connecting various financial applications. It serves as the gateway into AWS FinTech's suite of tools.

AWS FinTech is pivoting toward an AI-first experience to address several challenges. It was estimated that the current architecture of the third-party system can perform efficiently until the upcoming operational planning cycle in 2026, and can potentially cause more inaccurate data reporting in Finance teams.

This transformation aims to reduce time spent on routine tasks from hours to minutes, allowing finance teams to focus on driving actionable insights rather than data gathering and manipulation.

Finance teams were struggling with an outdated system that had accumulated decades of workarounds and patches. Users were making hundreds of manual entries through inefficient processes with zero real-time feedback, leading to errors and coordination challenges.

I conducted 8 user interviews across different finance teams to understand their workflows, pain points, and needs. I wanted to look more at a microscopic level to debrief and understand what problem is each user facing. This was an opportunity for me to see any patterns or trends across the finance space.

With research synthesized and pain points clearly mapped, the design opportunity came into focus.

To ground my design decisions, I explored how AI has been successfully integrated into other complex systems. Through desk research, I identified five recurring interaction patterns that illustrate how AI can assist, predict, and collaborate with users. These patterns became a framework for evaluating which approaches would bring the most value to financial input management.

Mapping the existing workflow against the proposed AI-enhanced version highlighted the stark contrast between manual inefficiencies and automated possibilities. I mapped the current workflow where users:

I identified specific agentic AI intervention points and showed how real-time validation, collaborative visibility, and scenario modeling could replace waiting and guesswork. Through conversations with product managers, I confirmed our shared understanding of the existing process and validated the proposed workflow against their long-term vision. This alignment ensured the design was grounded in both user realities and leadership priorities.

From a wide range of user pain points, I narrowed the design scope to two high-impact flows where the experience broke down most.

User testing feedback acted as a compass for refinement and validation. Hearing directly from finance analysts about what built trust — transparency, validation summaries, and manual override options — was vital for ensuring adoption.

Together, these contributions bridged legacy processes with modern, AI-first practices to ensure that the solutions were not only innovative but also aligned with broader organizational initiatives.

This project challenged me to grow far beyond my comfort zone as a designer. I learned to think in systems, understanding how a single change in one corner of the workflow could ripple across teams and influence business outcomes. I developed domain knowledge in complex financial planning practices, giving me the confidence to design with credibility in a space that was entirely new to me. Most importantly, I honed my storytelling skills — learning to communicate through narratives that made abstract processes tangible.