Chris User

At Fiserv, I design fraud detection and decisioning strategies across prepaid debit card, ACH, ATM, disputes, and other payment transaction flows. I translate fraud trends and transaction behavior into detection logic, risk controls, and mitigation actions.

I've designed and implemented fraud prevention rules that prevented approximately $2.1M in fraud losses while balancing detection effectiveness, false positives, and legitimate customer impact. I also investigate suspicious activity, identify control gaps, and monitor rule performance across large-scale payment datasets.

I build scalable monitoring datasets, automated metrics, dashboards, and reporting for Fraud Operations, Risk, and leadership. Using SQL, Python, PySpark, and cloud data platforms, I've developed production-grade data models and pipelines supporting fraud investigations, payment risk monitoring, dispute operations, and enterprise reporting.

I partner with Fraud Strategy, AML, Cyber Security, Compliance, Product, Legal, Data Science, and Engineering teams to assess emerging risks and improve fraud controls. I also provide production support and root-cause analysis for mission-critical fraud decision systems on Palantir Foundry.