Analyse large datasets to identify fraud patterns, anomalies, and emerging internal fraud risks, and translate insights into actionable detection rules and controls
Monitor fraud alerts, trends and key metrics (e.g. detection effectiveness, case outcomes) through dashboards and reporting
Support investigations through data analysis, evidence gathering, and hypothesis testing
Conduct root cause analysis by linking data signals with underlying business processes and identifying control gaps
Partner with cross‑functional teams (e.g. operations, product, business intelligence) to enhance detection capabilities and close control gaps
Recommend and support scalable improvements to fraud detection and monitoring, balancing effectiveness and operational efficiency
Identify opportunities to enhance detection logic, workflows and automation
Travel up to ~30% to support investigations, stakehold...
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