- Enabled significant annual cost-savings
- Decreased initial time to decision
- Reduced case resolution time
A leading credit card issuer’s Financial Intelligence Unit (FIU) needed its anti-money laundering (AML) investigators to assess cases more quickly. Reducing time spent on traditional AML investigations would allow the client’s investigators to tackle a broader range of cases. Productivity needed to improve while maintaining existing regulatory standards.
A major deterrent to investigator productivity was a lack of unified customer view. Investigators received many new alerts every day that required evaluating individual customers for Suspicious Activity Reports (SARs). Investigating each alert required expansive customer data detailing transactional history, demographics, and their related associates. The majority of this data did not exist at the customer level, and instead was stored at the account level in many formats across siloed source systems. Retrieving and preparing this data for each customer was a time-consuming, manual process for investigators.
Manual data retrieval often delayed time-to-decision by 24 to 48 hours for each case. Lags in data retrieval forced investigators to work on multiple cases simultaneously, resulting in context-switching that increased the risk of errors. Without unified customer views the FIU could not automate initial data pattern and anomaly detection, as these processes required account data to be unified per customer.
Overall workflow management productivity was impeded by manual processes. Cases couldn’t be assigned programmatically on factors such as expertise, severity, or related product; alert inventory was managed manually through spreadsheets.
Enigma was selected to improve AML investigatory productivity after demonstrating an in-depth understanding of the business problem and the existing infrastructure. To provide unified customer views, Enigma built pipelines that link disparate account data. By linking relevant account data, investigators now have a dramatically-expanded view of a customer, the customer’s associates, and all related behavior. Unified customer data also provides the foundation for automated initial data pattern and anomaly detection through machine learning models.
Unified customer data is now automatically and immediately delivered to investigators for every alert for several major lines. Enigma built programmatic rules and algorithms that pre-fetch, clean, and analyze customer data upfront. Data is retrieved across siloed systems to provide investigators with complete and accurate information at the start of analysis, eliminating data lags and allowing each investigator to focus on one case at time.
The client now receives case data from Enigma that will allow alerts to be scored and assigned automatically based on relevant attributes such as expertise, driving better workflow productivity. This will will result in investigations being distributed more strategically, and provide operational insight in caseload distribution and case complexity.
Through unified customer views and programmatic data retrieval, the client’s AML investigation processes have experienced significant uplift. Initial time-to-decision was reduced and case resolution time has decreased as well. Overall productivity gains resulted in significant cost savings.
Automated data retrieval has eliminated data delays and related distractions from context switching, and improved the day-to-day work experience for investigators.
The client has achieved all of these productivity improvements while maintaining excellent regulatory standards.