From pharmaceutical, healthcare and financial claims, to insurance and product warranty claims, identifying and monitoring Fraud is a priority for many organizations. Not only is a monetary loss at stake, but there is also potential damage to a company's brand, reputation, and trust. However, it can be a challenge for companies to understand and stay ahead of ever-evolving fraud risks and proactively identify and investigate active threats—let alone to navigate the new world of data analytics to assist in the process.
This post first appeared on Elder Research Data Science & Machine Learning Blog, please read the originial post: here