Uno (AWS Fintech)
As the lead UX Designer for a major cloud services provider's fintech division, I spearheaded the development of a groundbreaking financial platform that revolutionized how finance teams access and analyze critical financial data worth billions of dollars. Working across parallel tracks with a cross-functional team of designers, I orchestrated the rapid delivery of this complex system, transforming a fragmented multi-system workflow into a unified, intuitive platform that now serves as the backbone for over a thousand finance professionals' daily operations. The project's success was recognized with a prestigious UX Design Award in the Product category for Spring 2025, selected from 162 nominated projects across 38 countries. This accolade underscores the platform's innovative approach to simplifying complex financial workflows and its significant impact on user productivity and data accessibility.
AWS Fintech Data Catalog - UX Case Study
Problem
AWS Fintech's finance division struggled with severe data fragmentation that forced 58% of finance professionals to navigate nine disconnected systems for routine analyses. This fragmentation resulted in 2-4 hour timeframes for basic customer analyses, high error rates due to inconsistent data definitions, and significant operational bottlenecks across three key persona groups: Strategic Finance Planning & Analysis teams lacking forecast visibility, Service Finance professionals wasting time on manual reconciliation, and Senior Leadership making decisions with inconsistent financial data.
Process
My approach began with in-depth contextual inquiries across 15 finance managers, revealing critical pain points in three workflows: planning, monthly financial reviews, and customer analysis. I translated these insights into detailed journey maps and collaborated with data engineers to develop a comprehensive taxonomy through cross-functional workshops. User testing with interactive prototypes helped refine our information architecture, validating preferences for context-aware search, calendar-based planning views, and anticipatory agentic features that would fundamentally transform how users accessed financial data.
Solution
The solution unified fragmented systems through an intelligent, agentic-powered interface featuring dynamic process filtering, personalized action cards, and AI-enhanced calendar views. At its core, the reimagined homepage serves as a command center with "Search by Jarvis" functionality interpreting natural language queries while displaying complete data lineage. Process-specific workflows for SFP&A teams enable calendar-based planning with AI assistance, while Service Finance users benefit from notification-driven reconciliation tools. The system further empowers users with automated reporting featuring AI-suggested narratives and customer analysis tools with peer benchmark comparisons – all within a secure framework that maintains data relationships while ensuring appropriate access controls.
Technical Implementation
Implementation required building a sophisticated metadata layer that maintained complex relationships between financial entities while supporting role-based permissions without hampering discoverability. Working closely with engineering teams, I created a design system that accommodated progressive enhancement as new data sources were integrated, ensuring data freshness indicators built trust while the unified taxonomy allowed consistent representation across previously siloed systems. This architectural approach not only solved immediate user needs but created a foundation for future AI and predictive analytics capabilities.
Impact
The reimagined data catalog transformed financial operations with quantifiable results: customer analysis time plummeted from 4 hours to 45 minutes (81% improvement), teams handled 30% more analyses without additional headcount, and user satisfaction scores surged from 65% to 92%. SFP&A teams reported significantly improved forecasting confidence, while Service Finance managers praised the system's ability to automatically surface critical variances. Beyond these immediate gains, the project established a foundation for advanced analytics, created a scalable framework for integrating new data sources, and enabled the predictive insights that now power AWS Fintech's strategic decision-making capabilities.
