In order to determine if the claims process is changing, actuaries may rely on discussion with claims personnel and tests performed on the data to look for abnormalities. However, this may not help quantify the impact of any changes and will not necessarily tell you what has changed in the underlying claims process. Through the use of predictive modeling on detailed claim data, actuaries can better estimate not just if there is a change in the underlying claims process, but what is driving this overall change. Are payments on back claims accelerating? Are the claim adjuster estimates of incurred losses more inaccurate on certain types of claims? Has the distribution of claims changed significantly?

While claims predictive modeling transforms how the industry and claim systems settle claims on the back-end, there are other forms of analytics (i.e. underwriting predictive modeling, fraud analytics, etc.) that transform the risks insurance companies write on the front-end, and which actuaries also need to consider. This presentation will discuss the key concepts and drivers behind changes in the underlying claims process, and how the role of the actuary will need to change to adapt to the expanded use of more detailed claims data, claims predictive modeling capabilities and other forms of analytics, and how they are all impacting loss development triangles and other loss reserving methodologies.