Client · A Pharmacy Benefits Manager · There are about 4 billion prescriptions written is US alone every year. · FBI estimates, potentially, up to about 10% of the transactions can be classified as FWA Challenge:· FWA detection · Current process is manual, can only find known fraud signatures
Advanced machine vision is increasingly being used to investigate, diagnose, and identify potential remedies and their progressions for complex health issues. In this study, a behavioral neuroscientist at the University of Chicago and his colleagues have collaborated with Kavi Global to characterize 3D feeding behavior and its potential changes caused
Up to 10% of the pharmacy claims submitted to health plans and insurance companies are estimated to be fraudulent. A two-step process comprising of a combination of unsupervised and supervised learning techniques can be used to effectively identify the Fraud, Waste and Abuse in the Pharmacy industry. Claims submitted by
Saurabh is a Senior Analytics Consultant in the R&D Team at Kavi Global. He is currently involved in the development of big data and analytics platforms that leverage the data processing and machine learning capabilities of Spark. He has worked in several industry verticals like Healthcare, Manufacturing, Transportation, and Logistics.
Giridharan Gurumoorthy is a Business Analytics Senior Consultant at Kavi Global LLC. He has more than a decade of experience in the healthcare industry and advanced analytics technology. He also has published several papers in data analytics and its applications. PHARMACY CLAIMS FRAUD DETECTION USING APACHE SPARK SUMMIT 2018 Up
Despite the hype, the sad reality is that only a very small percentage of the companies embarked on the digital transformation journey have been able to successfully move their data analytics solutions into production, accelerate delivery and scale. Many are stuck and churning, finding it difficult to deliver the business
