Healthcare expenses related to the federal government make up close to one trillion dollars, a substantial portion of which is lost to fraud and abuse. Machine Analytics carried out studies to detect fraud using registration and claim data, a solution that can be automated and added to a business process to substantially save both time and money. The outliers representing candidate fraudulent behavior have been detected with over 98% accuracy applying in-house powerful machine learning algorithms for classification. Relevant data have been extracted and cleaned using our proprietary algorithms for data dimension and noise reduction techniques.
Machine Analytics solution for fraud detection in the healthcare domain can be easily customized for similar problems in other business verticals such as to detect fraudulent credit card transactions and insurance claims.