You don't have to accept claims fraud as a cost of doing business. SAS® Detection and Investigation for Insurance provides an end-to-end solution for detecting, preventing and managing both opportunistic and organized claims fraud across multiple lines of business, with components for fraud detection, alert management and case handling.
Detect more fraudulent activity.
Identify suspicious activity, uncover hidden relationships and detect subtle patterns of behavior at every stage of the claims process. Our insurance fraud analytics engine uses multiple techniques (automated business rules, embedded AI and machine learning methods, text mining, anomaly detection and network link analysis) to automatically score millions of claims records in real time or in batch. Customized anomaly detection methods reveal previously unknown schemes, linked entities and hidden crime rings, which can help stem larger losses.
Get a consolidated view of fraud risk.
Identify linkages among seemingly unrelated claims, and identify cross-product fraud. A unique visualization interface lets you see customer claims and policies for all lines of business, and analyze all related activities and relationships at a network dimension. Social network diagrams and sophisticated data mining capabilities give you a better understanding of new fraud threats, enabling you to prevent substantial losses early. And you can stay on top of changing claims fraud trends by continually improving models and adapting the system.
Lower loss-adjustment expenses, and gain a greater competitive advantage.
A sophisticated fraud scoring engine enables you to identify claims fraud with greater speed and accuracy. By quickly determining which claims require further scrutiny and which ones don't, you can significantly reduce false positives – which means a better customer experience. Automatic scoring lets you prioritize higher-value claims, entities and networks, while advanced case handling tools enable more efficient, effective investigations – and a higher ROI per investigator. In addition, all claims settlement amounts are captured within the system for reuse with similar claims in the future.
- Data management. Includes an insurance-specific data model that consolidates data from internal and external sources – claims systems, watch lists, third parties, unstructured text, etc. – and seamlessly integrates existing solutions.
- Advanced analytics with embedded AI. Provides a broad set of advanced analytic and AI techniques, including modern statistical, machine learning, deep learning and text analytics algorithms – accessible from a single environment.
- Rule and analytic model management. Includes prepackaged heuristic rules, anomaly detection and predictive models, and lets you create and logically manage business rules, analytic models, alerts and watch lists.
- Detection and alert generation. Calculates the propensity for claims fraud at first submission with a scoring engine that combines business rules, anomaly detection and advanced analytics; then rescores claims at each processing stage as new claims data is captured.
- Alert management. Combines alerts from multiple monitoring systems and associates them with common individuals for a more complete view of risk for individuals or groups.
- Social network analysis. Provides a unique visualization interface that lets you go beyond transaction and detailed claims views to analyze all related activities and relationships at a network dimension.
- Search and discovery. Lets you perform free-text, field-based or geospatial searches across all internal and external data, and refine searches using interactive filters.
- Case handling. Streamlines operations with a configurable workflow that provides a systematic means of conducting investigations, and captures and displays all information pertinent to a case.