Alerts Triage
Graphyte APIs enable the efficiencies of automated risk-based alerts triage, with accurate risk summaries based on a comprehensive public data review. Graphyte automatically screens the subjects of all alerts through PEP lists, sanction lists, and adverse media, and leverages machine learning scoring algorithms to extract only the most accurate and relevant sources. Every alert can be confidently categorized based on its contents as well as the external exposure of the entities involved. Alerts with high-risk exposure can be fast-tracked and low-risk alerts hibernated. Investigators spend more time on the highest-risk cases, achieve consistency in researching, analyzing, and classifying suspicious activities, and prevent false negatives. Financial institutions stay in compliance by aligning with a risk-based approach, while SAR/STRs are made more actionable for law enforcement.
Alerts triage is enabled by a suite of application interfaces purpose-built for today’s AML analyst. A configurable dashboard enables aggregate analysis and reporting, while stack workflow views enable drilldown from a lineup of the day’s alerts down to risks on individual subjects.
Key Features
Risk ranking & categorization
of AML alerts based on identified risk signals
Comprehensive evaluation
of internal, external, structured & unstructured data
Out-of-the-box integration
with risk-relevant, external data sources
Intelligent workflow policies
that automate alert assignments based on risk
Hibernation of lower risk alerts
that ensure that they are not forgotten
Built-in dashboards and analytical tools
for reporting and tuning
Backlogs, Lookbacks, and Below-the-Line Testing
Risk-based automation of alerts triage incorporated into the AML workflow makes operations more predictable and can prevent unforeseen future costs. Graphyte has been shown to help eliminate 90% of an alert backlog within days with a one-time batch screening, while providing the automation necessary to prevent new backlogs from accumulating. Graphyte also provides for executive-level reporting of the process, with links to source documents, risk factors and scoring.
This automated approach to remediating backlogs can also be leveraged for lookback and below-the-line testing applications. A batch screening of external risk factors for the entire lookback period is an efficient way to help prioritize the typically limited number of cases that actually do require manual investigation.