Dynamic Risk Classification for Anti-Money Laundering
Posted: 30 December 2010 | Source: SAS
Financial institutions are finding it necessary to strengthen their anti-money laundering (AML) platforms to stem the tide of illicit financial transactions and meet new regulatory mandates. For enterprises with moderate to high risk
exposures, this calls for a rigorous automated system based on dynamic risk assessment.
Financial institutions need a way to adapt rules, parameters and scenarios to match the risk profile for any given account or individual in order to monitor differentially based on risk. This requires being able to:
• Integrate a customer’s initial “on-board” risk classification into ongoing transaction monitoring.
• Automatically reassess risk rating and support a risk-based monitoring process.
• Adjust scenarios and risk factors to minimize the incidence of false positives.
• Combine multiple scenarios and risk factors to generate high-quality alerts.
• Identify cases that are significant, rather than chasing all simple alerts.
• Identify the highest priority cases to be investigated, based on a customer’s risk classification.
SAS Anti-Money Laundering provides all of these capabilities. Institutions can create an enterprisewide view of customer relationships and risks, monitor activity using multiple detection methods, adapt that monitoring as appropriate for each customer’s risk classification, investigate and document suspicious cases, and produce required regulatory reports – all within an integrated solution built on award-winning SAS data management and analytic capabilities.