Mastercard Fraud Analysis Dashboard

By: Jennifer Ma, Taylor Zhou, Inayat Inayat, Alexandra Svoboda, Harjot Singh
Course: IAT 333 Interaction Design Methods

Description: Mastercard is a global payments technology company enabling secure transactions worldwide. In partnership with the Vancouver Technology Hub, this project focuses on improving fraud investigations for Mastercard’s Fraud Operations team, who monitor suspicious transactions, tune fraud rules, and work to reduce financial loss.

The existing workflow was fragmented across multiple dashboards, cluttered tables, and complex filters, making it difficult for analysts to quickly spot fraud spikes or identify underperforming rules. With over 50 active rules and delayed data, analysts needed clearer aggregation, simpler filtering, and a workflow aligned with real investigative steps.

The redesigned Fraud Analysis Dashboard centralizes key insights into a single, structured view that guides analysts from high-level trends to rule-level detail. Clear, consistent visuals surface anomalies and missed fraud patterns at a glance, while standardized terminology such as “Missed Fraud” improves clarity and decision-making.

Scalable rule comparison, simplified date controls, and refined visual hierarchy reduce cognitive load and support faster analysis. Detailed rule breakdowns provide context, financial impact, and recommended fixes backed by real transaction examples, increasing confidence in investigative decisions.

Overall, the solution delivers faster, more accurate fraud investigations, greater trust in dashboard insights, and a more intuitive workflow that integrates seamlessly with Mastercard’s existing tools.

View the Project Presentation

Check out the Project Prototype