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. Requirements 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 #J-18808-Ljbffr