Book traversal links for 2.7. Post-Implementation Testing, Tuning, and Validation
2.7. Post-Implementation Testing, Tuning, and Validation
Effective from 8/9/2021On a periodic basis and in the event of material system output or operational irregularities, LFIs should reassess the functionality of TM systems and processes, including the continued relevancy of detection scenarios and assumptions and the calibration of rule threshold values and parameters. As with pre-implementation testing, post-implementation testing should include checks for system integration, data quality, and operational functionality, and should additionally include back-testing of TM rules to ensure that they remain current and effective in targeting riskier transactions and activity. Any proposed tuning or adjustment to TM rules, particularly material adjustments, should be subject to pre-implementation testing using sample or historical data to ensure the proper functioning of the new or revised rules, and should be reflected in updated TM documentation.
TM model testing and validation should be performed by individuals with sufficient expertise and appropriate level of independence from the model’s development and implementation. Generally, validation should be done by people who are not responsible for the development or use of the TM model and do not have a stake in whether a model is determined to be valid. Independence may be supported by the separation of reporting lines (as where model validation is performed by an internal audit department as part of independent testing of the AML/CFT program) or by the engagement of an external party not responsible for model development or use. As a practical matter, some validation work may be most effectively done by model developers and users; it is essential, however, that such validation work be subject to critical review by an independent party, who should conduct additional activities to ensure proper validation. All model validation activities and identified issues should be clearly documented, and management should take prompt action to address model issues.