Santander — reverse factoring

A reverse-factoring platform used across business units and geographies had grown without coherent design logic, with silos blocking direct access to end users.

This was my first project with Santander, and also Globant's. That context mattered more than it might sound: the margin for error on a first engagement with a global banking client is essentially zero, and everyone in the room knows it. The tool managed reverse factoring flows across multiple business units and geographies, a B2B financial instrument with a user base scattered across different branches of one of the world's largest banks. The platform had grown without a coherent design logic, and the task was to bring clarity to something that had accumulated complexity over years.

The defining constraint was structural. Organizational silos inside a large bank made direct access to users and key stakeholders impossible. We couldn't run user interviews. We couldn't reach the people actually operating the tool day-to-day. In most projects that would be a blocker. Here it became a design problem to solve before the design problem.

I led a design duo and we built an indirect research framework instead: competitive benchmarking across equivalent B2B financial tools, combined with rigorous analysis of the usage data we were given access to. Benchmarking in this context wasn't a consolation prize for not having users. It was a legitimate way to extract signal about expectations and interaction patterns from adjacent contexts, and we treated it with the same rigour we'd have applied to direct research.

That data informed a complete restructure of the information architecture, prioritizing the workflows that appeared most frequently and were most prone to error, and simplifying the navigation logic around actual task completion rather than system architecture. Managing stakeholder expectations throughout, while also carrying the internal pressure of a first-impression engagement, required constant calibration between what was designable, what was evidenced, and what was politically viable. It's the kind of project that doesn't show up neatly in a case study, but it taught me more about operating under ambiguity than almost anything else in my career.