Detect and prevent health care fraud, waste and abuse at every stage of the claims process, and stop improper payments before claims are paid.
Detect more fraud, reduce your losses and optimize payment integrity.
Spot more payment integrity breaches than ever before with a robust fraud analytics engine that processes all data (not just a sample) in real time or in batch. Running on the powerful SAS Viya, the solution uses advanced analytics with embedded artificial intelligence (AI) and machine learning algorithms, combined with other techniques – business rules, outlier analysis, text mining, database searches, exception reporting, network link analysis, etc. – to uncover more suspicious activity with greater accuracy.
Gain a consolidated view of fraud risk.
Identify linkages among seemingly unrelated claims with a unique visualization interface that lets you go beyond individual and account views to 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 threats, enabling you to prevent big losses early. And you can stay on top of changes in payment and cost containment trends by continually improving models and adapting the system.
Reduce false positives while boosting efficiency.
The solution applies risk- and value-based scoring models to accurately score and prioritize alerts before they go to analysts, clinicians or investigators. With the time saved, valuable personnel can work more cases with greater efficiency and focus on higher-value networks that generate a better ROI. More accurate scoring also means fewer false positives – and that translates to less customer inconvenience and greater customer satisfaction.
An end-to-end framework for ensuring payment integrity, with components for fraud detection, alert management and case handling.
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- SAS ViyaConquiste seus desafios analíticos, desde o experimental até a missão crítica, com decisões mais rápidas na nuvem. O SAS Viya permite que todos - cientistas de dados, analistas de negócios, desenvolvedores e executivos - colaborem, escalem e operacionalizem insights, em qualquer lugar.