Step 1 – Transaction Monitoring Implementation Best Practices
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We can all agree that it is critical for financial institutions (FIs) to have an effective transaction monitoring (TM) system in place. Continuous regulatory changes, technology enhancements, and increased scrutiny from regulators and internal control functions on measures taken to address financial crime are driving the need for continuous improvement of transaction monitoring systems (TMS).
Based on our experience of 200+ transaction monitoring implementation projects, we are proposing certain best practices that will help combat some of the biggest challenges currently faced by financial institutions. The challenges posed by a combination of untuned systems, lack of available data, cost overages, and other complications can be addressed by four key phases:
- Rule selection
- Data preparation
- Segmentation
- Tuning & operational optimization
1. Rule Selection
The selection and implementation of smart detection rules are at the heart of a successful TM implementation project. AML risks need to be carefully evaluated by the FIs along with identifying what type of models and rules should be defined to assure there is comprehensive coverage for suspicious activity monitoring.
2. Data Preparation
Data drives the success of the TM process. For a successful TM implementation, FIs need to assure that the data quality is properly validated. However, ensuring the continued quality of data is far more complex and requires discipline. That is why it is important to build a comprehensive and holistic data environment, with adequate data quality, data lineage, and data model metadata controls.
3. Segmentation
Segmentation is one area that has been going through a significant transformation in recent times. When implementing or upgrading a TMS, it is recommended that FIs move away from the traditional approach of creating segments using static KYC attributes such as customer type and customer category. Combining smart detection rules with activity-based intelligent segmentation, and risk-focused thresholds will result in high-quality alerts and reduced false positives.
4. Tuning & Operational Optimization
Tuning and operational optimization is another area that has been going through a significant change. We recommend FIs to leverage new techniques, such as consolidating alerts, workflow optimization, and Robotic Process Automation to reduce manual processing times associated with (but not limited to) data gathering, excel processing, third-party system access. The integration of workflow optimization with intelligent automation will not only help to make investigations consistent but will also help to reduce the operational cost for the bank.
