Using Mathematica in the Modeling of Insurance Claims

Four "Real World" Examples

Mark Coleman and Darrel Barbato

Liberty Mutual Group

Abstract

Mathematica provides a unique analytical environment for visualizing, exploring, and modeling insurance claims data. We present four specific examples of how Liberty Mutual uses Mathematica to both enhance our understanding of observed insurance claiming behavior and to develop operational predictive modeling tools to improve how we handle key aspects of some common property and automobile claims. The first two of these examples focus on predicting outcomes around "total loss" auto claims, i.e., auto accidents that result in sufficient damage that the insured's vehicle needs to be replaced. The second pair of examples involve homeowner claims. In the first we explore how one might predict the need for mitigation services due to water damage; the second integrates spatial analysis with linear statistical modeling techniques to estimate a storm-dependent count of property claims due to hail storms.