Fraud Decisioning Analyst

Responsibilities

• Analyze fraud decisioning performance across enterprise alert volumes, evaluating alert drivers, decision outcomes, false positive rates, and queue dynamics to identify performance gaps and inefficiencies.
• Assess end-to-end alert lifecycle and workflow performance, including queue throughput, capacity utilization, and case handling efficiency, to improve operational effectiveness and scalability.
• Conduct root‑cause analysis on alert behavior and decision outcomes, identifying drivers of unnecessary alerts, missed detection opportunities, and workflow bottlenecks.
• Develop and maintain performance metrics and reporting frameworks that provide transparent, consistent views of alert effectiveness, benefit, decision accuracy, and operational impact.
• Identify and quantify optimization opportunities to improve fraud detection outcomes, reduce customer friction, and balance workload across fraud mitigation teams, using data‑driven analysis.
• Translate complex, execution‑level analytics into actionable insights and recommendations, enabling stakeholders to improve decisioning outcomes and workflow efficiency.
• Partner with Fraud Mitigation Solutions (FMS) and Fraud Strategy teams to align on performance insights, validate findings, and support continuous improvement initiatives.
• Support evaluation of fraud controls and decisioning approaches in production, providing analytical input on performance impacts without directly designing or implementing rules.
• Monitor emerging trends, anomalies, and shifts in alert behavior to identify new risks, changing fraud patterns, or degradation in performance.
• Ensure analytical rigor and data integrity, validating assumptions, methodologies, and outputs to support confident, decision‑ready insights.

• Bachelor’s degree, or equivalent work experience
• Typically more than eight years of applicable experience
• Comprehensive knowledge of all departmental data sources, and of fraud risk and operations management associated with the product lines
• Strong analytical skills relative to evaluating fraud prevention infrastructure and forecasting fraud loss trends
• Strong project management skills
• Effective verbal and written communication skills
• Proficient computer navigation skills using a variety of software packages including Microsoft Office applications and data analysis software