Applied machine learning for health insurance fraud detection
Research and develop a machine learning application to detect fraud in health insurance claims. The project will seek to understand how machine learning can contribute significantly to health insurance fraud detection, and develop a methodology to yield the best results using available data and current machine learning best practices. The output of the project will be a unique machine learning framework to enable health insurance fraud detection, an engine that can be integrated with existing insurance claim software and a front-end dashboard for analysts. The contribution of this research will be to provide a new, automated approach to insurance fraud detection, saving significant time and money to the public and private sector alike.
View Full Project DescriptionVladimir Makarenkov
Solutions Ségic Inc
Computer science
Information and cultural industries
Université du Québec à Montréal
Accelerate