Healthcare Provider Fraud Detection

Use case in BFSI Data Intelligence

The goal of this usecase is to illustrate how Data Science & AI can be applied to address a healthcare provider fraud prevention challenge by creating a solution that is more effective, efficient, scalable, and adaptable.

This analysis using a sample data set was done to test the possibility of identifying fraudulent claims using past claim data. Having such a dataset would allow us to design, train and test Machine Learning models that enable us to extract intelligence embedded in large amounts of data that is overlooked otherwise. However, without an efficient way to integrate this model with your data, this only solves the problem partially. This is where Qualetics opens new possibilities.

To know how Qualetics gives an effective solution, download the full usecase.

    Get the Full Use case

    About Qualetics Data Machines

    Data Analytics and Artificial Intelligence are growing to be a ubiquitous need in the modern enterprise ecosystem. The need for Analytics is ranging from basic Descriptive and Diagnostic Analytics to advanced Predictive, Prescriptive, and Cognitive Analytics.  However, the barrier of entry is high due to expensive infrastructure and highly skilled resource requirements.

    Qualetics Data Machines Inc. aims to eliminate this barrier by introducing a product that makes it easy for businesses to embrace AI and gain data intelligence.