A Data Driven Binning Strategy for the Construction of Insurance Tariff Classes

30 Pages Posted: 13 Oct 2017

See all articles by Roel Henckaerts

Roel Henckaerts

KU Leuven - Faculty of Business and Economics (FEB)

Katrien Antonio

KU Leuven; University of Amsterdam

Maxime Clijsters

KU Leuven - Faculty of Business and Economics (FEB)

Verbelen Roel

KU Leuven

Date Written: May 12, 2017

Abstract

We present a fully data driven strategy to incorporate continuous risk factors and geographical information in an insurance tariff. A framework is developed that aligns exibility with the practical requirements of an insurance company, its policyholders and the regulator. Our strategy is illustrated with an example from property and casualty (P&C) insurance, namely a motor insurance case study. We start by fitting generalized additive models (GAMs) to the number of reported claims and their corresponding severity. These models allow for flexible statistical modeling in the presence of different types of risk factors: categorical, continuous and spatial risk factors. The goal is to bin the continuous and spatial risk factors such that categorical risk factors result which capture the effect of the covariate on the response in an accurate way, while being easy to use in a generalized linear model (GLM). This is in line with the requirement of an insurance company to construct a practical and interpretable tariff that can be explained easily to stakeholders. We propose to bin the spatial risk factor using Fisher's natural breaks algorithm and the continuous risk factors using evolutionary trees. GLMs are fitted to the claims data with the resulting categorical risk factors. We find that the resulting GLMs approximate the original GAMs closely, and lead to a very similar premium structure.

Keywords: P&C insurance pricing, frequency, severity, continuous risk factors, spatial risk

Suggested Citation

Henckaerts, Roel and Antonio, Katrien and Clijsters, Maxime and Roel, Verbelen, A Data Driven Binning Strategy for the Construction of Insurance Tariff Classes (May 12, 2017). Available at SSRN: https://ssrn.com/abstract=3052174 or http://dx.doi.org/10.2139/ssrn.3052174

Roel Henckaerts (Contact Author)

KU Leuven - Faculty of Business and Economics (FEB) ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

Katrien Antonio

KU Leuven ( email )

Leuven, Vlaams-Brabant

HOME PAGE: http://www.econ.kuleuven.be/katrien.antonio

University of Amsterdam ( email )

Roetersstraat 11
Amsterdam, 1018 WB
Netherlands

Maxime Clijsters

KU Leuven - Faculty of Business and Economics (FEB) ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

Verbelen Roel

KU Leuven ( email )

Naamsestraat 69
B-3000 Leuven, Vlaams-Brabant 3000
Belgium

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