Designing Trust at Scale: Adobe's Fraud Detection Platform
Product Strategy / AI-Driven Systems
Client:
Adobe
Role:
Product Designer
Year:
2024
Challenge
Fraud is invisible until it hits the bottom line. At Adobe, misuse was occurring in quiet, yet in costly ways! One user sharing an account with ten others, bots mass-creating fake trials, and suspicious spikes in activity. I was brought in to help build a Zero-Trust UX that identified and applied friction only to malicious intent, maintaining seamlessness everywhere else, not just to detect patterns, but to design a system that understood intent.
Approach
Defined the design framework that classified user intent to inform the calibrated security response.
Designed the control-center UX for Operations and Product teams, transforming complex data into a visual, decision-making tool for rapid intervention.
Developed the internal communication strategy (microsite) to secure essential cross-organizational buy-in for the new system's operational UX.
Results
📊 Dashboard adoption significantly reduced time-to-resolution.
🧠 AI logic turned into a reusable strategic UX framework
📣 Microsite built internal traction for systemwide buy-in
🔍 Uncovered ~1.6M+ shared accounts (~5M device-level opportunity)
Learnings
This project stretched my thinking beyond UX into systems, edge cases, and intent. It reminded me that when you're designing for trust, nuance matters, and the best tools are the ones that guide good decisions without oversimplifying human behavior.
This is just a glimpse, the full story runs much deeper. It's sensitive work and honestly, some work is too meaningful to just leave on the internet. Reach out and I'll take you through the whole thing!
