SAS® Fraud Network Analysis
An integral component of the SAS® Enterprise Financial Crimes Framework for Banking
Organized fraud is a growing problem. And while the transaction monitoring systems employed by most banks work well for individual real-time, point-of-sale fraud, a different approach is needed for monitoring customer behavior across multiple accounts and systems in order to identify those that may appear normal, yet operate below the radar. SAS Fraud Network Analysis is the answer.
Benefits
- Detect more fraudulent activity, and decrease losses due to organized fraud.
- Reduce false positives while increasing investigator efficiency.
- Gain a consolidated view of fraud risk.
- Gain a greater competitive advantage.
Features
- Fraud data management
- Rule and analytic model management
- Detection and alert generation
- Alert management
- Social network analysis
- Optional, integrated case management
- Auditability
Product Demo
This executive-level demonstration shows SAS Fraud Network Analysis being used as part of the SAS Fraud Framework to identify potential fraud in a bank.
More Demos and Screenshots
How SAS® Is Different
Only SAS provides better fraud detection and greater operational efficiency with:
- A hybrid approach to fraud detection and prevention that combines rules, anomaly detection, predictive models and network analytics.
- Text analytics for analyzing unstructured data (e.g., call center or social media conversations).
- Social network analysis for exposing organized fraud rings that might otherwise take years to identify.
- A banking-specific data model, fraud engine, prepackaged heuristic rules, anomaly detection and predictive models to get you up and running quickly.
Benefits
- Detect more fraudulent activity, and decrease losses due to organized fraud.
- Process all data (not just a sample) through business rules and analytical models in near-real time or in batch so you can spot more suspicious activity with greater accuracy.
- Uncover previously unknown fraud schemes using customized anomaly detection methods.
- Detect repeat offenders and more accurately score incoming transactions by searching databases of known fraudsters and capturing all fraud outcomes, referrals and suspects within the system for reuse.
- Spot linked entities and crime rings – which can help stem larger losses – using a unique network visualization interface.
- Overcome poor data quality issues associated with imperfect matching and highly linked entities.
- Uncover insider or collusive fraud by integrating staff data and audit records that show who handled which transactions.
- Reduce false positives while increasing investigator efficiency.
- Reduce the amount of time investigators spend investigating false-positive alerts with a sophisticated fraud scoring engine that actually decreases the number of false positives.
- Prioritize events before presenting to investigators by applying risk- and value-based scoring models.
- Enable investigators to work many times the number of cases and focus on higher-value networks, which generate a higher ROI.
- Gain a consolidated view of fraud risk.
- Identify cross-brand/product fraud by seeing customer accounts and transactions for all lines of business.
- Stay on top of changes in fraud trends by improving models on an ongoing basis and continuously adapting the system.
- Better understand new fraud threats and prevent substantial losses early using social network diagrams and sophisticated data mining capabilities.
- Gain a greater competitive advantage.
- Provide a better customer experience to legitimate customers through fewer false positives, which leads to greater customer satisfaction.
- Discourage fraudsters from targeting your organization by employing more diligent and effective fraud detection methods.
- Satisfy growing regulatory requirements with enhanced fraud management.
Features
- Fraud data management
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- Consolidate historical data from both internal and external sources for fraud analysis and investigation.
- Reduce or eliminate data inconsistencies/redundancies with built-in, automated data quality tools.
- Integrate the system seamlessly with third-party fraud applications.
- Rule and analytic model management
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- Logically manage rules, models and alerts for investigators.
- Create and manage business rules, analytical models and known fraudster lists.
- Maintain simple or complex routing and suppression rules.
- Detection and alert generation
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- Score transactions with a scoring engine that uses a combination of business rules, anomaly detection and advanced analytic techniques.
- Calculate the propensity for fraud at account opening, then rescore accounts with each transaction as new data is captured.
- Go beyond fraud detection by deploying at account opening to prevent fraudsters from opening accounts in the first place.
- Alert management
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- Assemble alerts from multiple monitoring systems, associate them with common accounts and give investigators a holistic perspective on the risk of a particular account or individual.
- Calculate risk scores based on an activity's specific characteristics, including transparent reason codes.
- Prioritize alerts and route potentially fraudulent transactions to appropriate team members.
- Automatically assign work to investigators based on user-set rules and requirements.
- Social network analysis
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- Identify linkages among seemingly unrelated transactions and uncover unknown relationships with a unique network visualization interface.
- Go beyond transaction and account views to analyze related activities and relationships at a network dimension.
- Automatically identify suspicious networked behavior in the data.
- Gain fast access to full details on transactions, all related parties and networks.
- Merge or delete network entities, and add annotations (text and images) to specific entities in a network.
- Optional, integrated case management
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- Systematically facilitate investigations using a configurable workflow.
- Capture and display all information pertinent to a case, including interview notes and evidence needed for criminal or civil prosecution, restitution and collections.
- Assess your overall fraud exposure, including losses due to fraud, as well as fraud detected or prevented.
- Completely assess investigative workloads, investigator efficiency and ROI, and use that information to build a business case for expanding fraud investigation resources.
- Auditability
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- Run reports and produce a complete audit trail for all alerts and investigations, in accordance with compliance mandates.
- Show network evolutions and drill down into reports for more detail.
Demos
Fighting Bank Fraud with SAS Fraud Network Analysis
This executive-level demonstration shows SAS Fraud Network Analysis being used as part of the SAS Fraud Framework to identify potential fraud in a bank.
Screenshots
SAS Fraud Network Analysis provides detailed alerts.
SAS Fraud Network Analysis provides detailed alerts about potentially fraudulent activity.
View associations between people in a network view.
SAS Fraud Network Analysis shows connections between customers and accounts to help you identify suspicious activity.
A full expanded network view.
Using SAS Fraud Network Analysis a potential "bust out" fraud ring can be visualized by indicating multiple unsecured loans that are associated with a flagged individual.
Ready to learn more?
Call us at 1-800-727-0025 (US and Canada) or request more information.
