AML Rule Tuning

AML rule tuning involves adjusting the parameters and thresholds of an AML detection system to improve its accuracy and effectiveness. This process aims to reduce false positives while ensuring that suspicious activities are correctly flagged. AML rule tuning requires analyzing data, testing changes, and validating the results to optimize the balance between sensitivity and specificity in alert generation.

Regular tuning helps maintain a robust AML monitoring system that adapts to changing risk landscapes and reduces the workload associated with unnecessary alerts.