May 2017 - Machine learning is a powerful tool for insurers looking to improve their capabilities with predictive analytics and data processing, and carriers are beginning to see benefits from pilot programs in rating and claims. But implementing machine learning successfully isn’t as simple as turning a business process over to AI; it requires a combination of data science expertise, an understanding of how machine learning can improve the process and the resources that execute it, and a willingness to think through business questions in new ways.

This report examines machine learning applications to identify general best practices for implementing machine learning in business functions.