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. Today it is estimated that more than 10 percent of all insurance claims are fraudulent, and insurers often accept fraud as the 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

Decrease fraud losses.
Lower loss-adjustment expenses.
Gain a consolidated view of your fraud risk.
Improve your competitive position.

Fraud detection.
Alert management.
Social network analysis.
Case management.

Product Demo

SAS Social Network Analysis can be used as part of the SAS Fraud Framework to identify insurance claims fraud.

View Demo

More Demos and Screenshots

How SAS^® Is Different

The SAS Fraud Framework for Insurance provides enhanced claims fraud detection and improved operational efficiency while decreasing the total cost of ownership. Only SAS provides:

Rapid model development and deployment.
Advanced analytic capabilities, including data mining and link analysis and other cutting-edge methods for identifying new and existing fraud.
The ability to update and refresh business rules as needed.
A design that handles large volumes of data.
Integration with existing systems as needed.
A variety of deployment options, including complete hosting by SAS, deployment at your site or a combination of the two.

Benefits

Decrease fraud losses.
- Prevent fraud before claims are paid with online, real-time scoring.
- Compare similar claims for loss padding using anomaly and loss comparisons.
- Identify reoffenders and more accurately score incoming claims using database searches of known fraudsters.
- Detect insider or collusive fraud by integrating the solution with staff data and audit records regarding which staff handled which claims.
- Capture all fraud outcomes, referrals and suspects within the system for easier detection of repeat offenders and more accurate scoring of incoming claims.
Lower loss-adjustment expenses.
- Dramatically reduce false-positive rates.
- Improve the efficiency of investigations with advanced case management tools, including automatically generated network diagrams that let investigators review claims information in more detail.
- Increase ROI per investigator through fewer false positives, prioritization of higher-value networks and more accurate investigations. Capture all claims settlement amounts within the system and use them to estimate loss reserves for similar future claims.
Gain a consolidated view of your fraud risk.
- View all claims for a customer across all lines of business to identify cross-brand/product fraud.
- Benefit from collective learning across the industry and update/improve models on an ongoing basis due to the solution's ability to continuously adapt to the changing nature of fraud.
- Understand new emerging insurance claim threats and prevent substantial losses early on using social network diagrams and sophisticated data mining capabilities.
Improve your competitive position.
- Improve customer service and enhance your reputation by investigating fewer genuine customer claims.
- Discourage fraudsters from targeting your company.
- Satisfy regulator and rating agency pressures with enhanced fraud management processes.

Features

Fraud detection.

A comprehensive fraud scoring engine uses a combination of different analytical techniques (automated business rules, database searches, anomaly and exception reporting, predictive modeling, text mining and network link analysis) to determine the propensity for claims fraud.
The fraud scoring engine is designed to detect fraud for auto, home and workers compensation lines of business and can easily be extended to support other lines of business.

Alert management.

A reporting mechanism scores, dedupes, prioritizes and routes potentially fraudulent claims to appropriate team members. A traffic light system highlights potentially fraudulent claims with a full risk score and transparent reason codes.
Provides a database for maintaining alert information and recording the actions taken to resolve the alert.

Social network analysis.

Provides top-down and bottom-up analysis for uncovering previously hidden linkages and making them visible.
Detects risky networks and provides them to investigators as alerts.
Allows for the input of individuals to display the networks to which they belong.

Case management.

Once an alert has been triaged and requires further investigation, the case management functionality provides a systematic means for facilitating the investigation and capturing and displaying all information pertinent to that case.