The vendor system had 22 active scenarios for CASA deposit and loan portfolios. The client needed to ensure the accuracy of data flow, validate the soundness of the model, and assess the effectiveness of the AML system in detecting true positive alerts while minimizing false positives.

Implemented a comprehensive validation process for AML scenarios.

1. Input Data Analysis: Validated data integrity and quality, reconciled data between the source system and TMS for 7-14 days to ensure accurate data flow.

2. Model Conceptual Soundness: Conducted typology assessment of existing scenarios to understand coverage of common red flags, assessed risk coverage of rules based on transaction and product types, and replicated active rules outside of TMS to verify alert accuracy.

3. Model Output Effectiveness: Evaluated true positives and false positives based on alert and SAR data, derived new thresholds for rules through ATL/BTL testing.

4. Model Governance: Assessed control measures and governance framework to mitigate risks in the TM system lifecycle.

Enhanced AML system effectiveness and reduced false positives.

- Reduced false positives and ensured that scenarios operated according to business requirements.

- Typology and risk coverage analysis improved understanding of existing TMS rules.

- Model governance assessment identified gaps in the control framework.