Claims Development Analysis Process In Need Of A Refresh? Machine Learning Can Help

Machine learning techniques can turn the critical task of identifying changing patterns of claims development and make it a more rewarding activity for both those doing the searching and those who use the information to make decisions.

In my experience, some of the most important questions insurance company senior executives want to know are: ‘How much adverse development are we experiencing? And what is driving these results?’

Or roughly translated: ‘Are any parts of the business heading into trouble?’ Typically, the way carriers have gone about answering this type of question is to drill into the characteristics of claims data for patterns of development that are anomalous to results or expectations.

This process can be very time consuming as the volumes of data involved are often large. It also requires a good chunk of experience and general industry knowledge to yield insights of much value.

Even then, answers that come from this type of effort can be very anecdotal or inconclusive, not to mention holding greater risk of confirming existing bias.