Webinar: From Guesswork to Precision: Simulation in Practice
by Cathrin Habel on
22 Oct. 2026
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At this year’s Siron User Group Conference, attendees had the challenge of choosing between several breakout sessions running in parallel. If you missed this session, attended another breakout, or couldn’t join us in Zurich, here’s your chance to experience the session.
Join Natalie Hürler and Tammy DSilva for a practical look at how simulation helps compliance teams move beyond assumptions and make smarter, data-driven decisions.
Event Details:
📅 Date:04 November 2026 ⏰ Time: 10:00 AM (CEST)
📍 Online
In today’s environment, fine-tuning detection scenarios is a constant balancing act. Adjust too little, and risks can go undetected. Adjust too much, and teams can become overwhelmed with alerts. Simulation offers a way to validate changes before they go live, helping organizations improve performance with confidence.
What you’ll learn
Move from assumptions to data-driven calibration
Refine detection performance using simulation insights
Balance compliance effectiveness and operational efficiency
Understand how simulation can support more informed decision-making and reduce uncertainty
Through real-world examples and practical guidance, you’ll discover how simulation can help optimize detection strategies while maintaining operational efficiency.
What is simulation-driven threshold tuning in AML?
Simulation-driven threshold tuning uses historical data to test how changes to AML detection thresholds and scenarios would perform before they are deployed. This helps compliance teams replace assumptions with evidence and evaluate the potential impact on detection effectiveness, alert volumes, and operational workloads.
How can simulation improve AML detection performance?
Simulation allows compliance teams to compare different detection settings against historical data and understand their potential impact before making changes in production. This supports more precise calibration, helps identify detection gaps, and enables teams to improve performance while maintaining appropriate risk coverage.
How can financial institutions reduce false positives without increasing risk?
Financial institutions can use simulation and data-driven calibration to understand which threshold or scenario changes reduce unnecessary alerts without weakening risk detection. Testing adjustments before deployment helps teams balance lower alert volumes with effective identification of genuinely suspicious activity.
Why is threshold tuning important in transaction monitoring?
Threshold tuning helps ensure transaction monitoring scenarios remain effective as customer behaviour, transaction patterns, and financial crime risks evolve. Thresholds that are too sensitive can create excessive alerts, while thresholds that are too high may miss relevant activity. Regular, data-driven calibration helps maintain the right balance.
How does simulation help compliance teams make better decisions?
Simulation provides compliance teams with evidence of how proposed changes could affect detection performance and alert volumes before implementation. This gives investigators and compliance leaders greater transparency, reduces uncertainty, and supports more informed decisions about AML scenarios and detection strategies.
What will attendees learn during the live demonstration?
Attendees will see how simulation can be used to test and refine AML detection scenarios before changes go live. The demonstration will show how simulation insights support data-driven threshold tuning, help assess the impact on alert volumes and detection performance, and enable more informed compliance decisions.
