Organized Fraud Rings

SAS gives you a holistic view of fraudulent activity – including related perpetrators – and a much clearer understanding of customer behavior. With SAS, you can:

• Draw in data from all relevant sources – including third parties – and parse the data to create a complete data model of all entities and their key linking attributes.
• Identify more fraud while reducing false positives with an advanced scoring engine that uses independent and combined scores to assess overall risk on a customer, product and network basis, then generates alerts that are automatically routed to the appropriate resources.
• Double or triple investigator efficiency with unique network visualization, data drill-down capabilities and other tools that enable investigators to:
  • Quickly review automatically generated network diagrams to determine if any account or transaction is fraudulent.
  • See patterns and symptoms that can lead to improved controls and new monitoring techniques.
  • Produce complete dossiers of networks surrounding a case using an intuitive interface that provides fast access to full customer details.
• Prevent criminals from masking their previous identities and repeatedly opening accounts by automatically applying risk scoring against known fraudulent networks.

No other fraud solution available provides the same level of detection, automation, ease of use and ROI for organized fraud rings. SAS provides:

• Advanced data network building and analytic techniques that can ingest existing risk scores or red flags and provide an aggregated score at the network level to identify subtle or hidden relationships that may indicate account bust-out or associate collusion.
• True, large-scale network analytics that work across internal and external data sources – e.g., fraud consortium databases – to link customers and accounts based on common attributes or more subtle patterns of behavior.
• Neural network and advanced modeling approaches that take you far beyond the limits of standard parameter-driven, rules-based systems and deliver more valid alerts that you can act on, enabling you to maintain extremely low false-positive rates while achieving unrivaled detection rates.
• Industry-leading predictive analytics that let you perform supervised and unsupervised scoring to spot anomalies in the data.
• A metadata configuration that links all records exhaustively based on combinations of attributes within the data; then, using statistical techniques, identifies and collapses common entities to produce single views of entities within networks.