SAS^® Fraud Framework for Insurance

Detecting, preventing and managing claims fraud across all lines of business

Overview
Benefits
Features
Demos & Screenshots

Fraud costs the P&C industry $30 billion each year in the US alone, and that figure is projected to rise as both opportunistic and professional fraud continue to grow. It is estimated that more than 10 percent of all insurance claims are fraudulent, but insurers often accept fraud as a cost of doing business since it isn't cost-effective to pursue fraudulent claims after settlement. That's why SAS developed the SAS Fraud Framework for Insurance, an end-to-end solution for preventing, detecting and managing claims fraud across the various lines of business within today's insurers.

Benefits

Detect more fraudulent activity than ever before.
Prevent fraud losses before settlement.
Lower loss-adjustment expenses.
Gain a consolidated view of fraud risk.
Improve your competitive position.

Fraud data management
Rule and analytic model management
Detection and alert generation
Alert management
Social network analysis
Case management

Product Demo

Learn about our hybrid approach to detecting and preventing both opportunistic and professional insurance claims fraud.

View Demo

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 that combines rules, anomaly detection, predictive models and network analytics.
Text analytics for analyzing unstructured data like claims notes, customer service logs, police reports, medical records, etc.
Social network analysis, which lets you uncover organized fraud rings that might otherwise take years to identify.
An insurance-specific data model and fraud engine, along with prepackaged heuristic rules, anomaly detection and predictive models specifically tailored for insurance fraud, so you can get up and running quickly.
The flexibility to configure the system to meet your specific needs, as well as update models and adapt the system to address changes in insurance fraud trends.

Benefits

Detect more fraudulent activity than ever before.
- Insert advanced analytics into the process, in addition to rules engines.
- Process all claims data (not just a sample) through rules and analytical models in real time or in batch.
- Use customized anomaly detection methods to detect previously unknown schemes.
- Spot linked entities and crime rings, which can help stem larger losses.
- Overcome poor data quality issues associated with imperfect matching and highly linked entities.
Prevent fraud losses before settlement.
- Stop fraud before claims are paid using online real-time scoring or daily batch scoring.
- Detect loss padding in similar claims using anomaly detection and loss comparisons.
- Identify repeat offenders and more accurately score incoming claims by searching databases of known fraudsters and capturing all fraud outcomes, referrals and suspects within the system for reuse.
- Uncover insider or collusive fraud by integrating staff data and audit records that show who handled which claims.
- Apply risk- and value-based scoring models to prioritize output before presenting to investigators.
- Insert analytical models into your process workflow, enabling real-time access to information.
Lower loss-adjustment expenses.
- Greatly reduce false positives using a sophisticated fraud scoring engine.
- Improve investigator efficiency with advanced case management tools.
- Increase investigator ROI per investigator by prioritizing higher value networks and conducting more efficient and accurate investigations.
- Capture all claims settlement amounts within the system for reuse with similar claims in the future.
Gain a consolidated view of fraud risk.
- Identify cross-brand/product fraud by seeing customer claims and policies for all lines of business.
- Continuously improve models and adapt the system as needed to address changes in fraud trends.
- Understand new claim threats and prevent substantial losses early using social network diagrams and sophisticated data mining capabilities.
Improve your competitive position.
- Generate fewer false positives, which leads to greater customer satisfaction for legitimate customers.
- Drive fraudsters to target other insurers with less diligent and effective fraud detection methods.
- Satisfy regulatory and rating agency requirements through enhanced fraud management.

Features

Fraud data management

Consolidates historical data from internal and external sources for fraud analysis and investigation.
Includes data quality tools that can reduce or eliminate data inconsistencies or redundancies.
Supports integration with third-party fraud applications.

Rule and analytic model management

Enables you to logically manage rules, models and alerts for investigators.
Allows you to create and manage business rules, analytical models and known fraudster lists.
Lets you maintain simple or complex routing and suppression rules.

Detection and alert generation

Scores claims in real time with an online scoring engine that combines business rules, anomaly detection and advanced analytic techniques.
Calculates the propensity for fraud at first notice of loss, then rescores claims at each settlement stage as new claims data is captured.
Goes beyond claims fraud detection by deploying at policy inception to prevent fraudsters from taking out policies in the first place.

Alert management

Assembles alerts from multiple monitoring systems, associates them with common claimants and gives investigators a more complete perspective on the risk of specific claimants.
Calculates risk scores based on specific characteristics of the activity, and includes transparent reason codes.
Prioritizes alerts and automatically assigns them to appropriate team members based on user-set rules and requirements.

Social network analysis

Provides a unique network visualization interface that lets investigators identify linkages among seemingly unrelated claims and uncover previously unknown relationships.
Lets investigators go beyond transaction and account views to analyze all related activities and relationships at a network dimension.
Automatically identifies suspicious networked behavior in the data.
Gives investigators fast access to full details on claims and all related parties and networks.
Allows investigators to merge and delete network entities as well as add annotations (text and images) to specific entities in a network.

Case management

Provides a systematic means for facilitating investigations, using a configurable workflow.
Captures and displays all information pertinent to a case, including interview notes and evidence needed for criminal or civil prosecution, restitution and collections.
Assesses your overall fraud exposure, including losses due to fraud as well as fraud detected or prevented.