JSM 2005 - Toronto

Abstract #303858

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Activity Number: 139
Type: Contributed
Date/Time: Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor: Business and Economics Statistics Section
Abstract - #303858
Title: Predictive Modeling in Property and Casualty Insurance: Case Study for Identifying the Worst Insurance Risks among Small Businesses
Author(s): Vladimir Ladyzhets*+ and Martin Couture
Companies: Babson Capital Management LLC and St. Paul Travelers Insurance Company
Address: 38 Kinne Rd, Glastonbury, CT, 06033, United States
Keywords: decision trees ; neural network ; variable selection ; explanatory analysis
Abstract:

Small businesses comprise one of the most profitable and, at the same time, risky market segments for the property and casualty insurance companies. The industry's actuaries and underwriters face the challenge of identifying the business entities with highest propensity to make large claims. The case study of building a neural network model that identifies the worst insurance risks among small restaurants is presented. It has been demonstrated that different types of decision trees, chi-square, entropy, and Gini, can be used effectively to provide the best variable selection and carry on the explanatory analysis of the scores yielded by the neural network model.

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