Pricing of Automobile Insurance Policies using Generalized Linear Models and Lasso Regularization

The goal of this thesis is to create a predictive model for the expected claim cost of automobile insurance policies in Iceland. The proposed model is based on the characteristics of the policyholder and the insured vehicle, and reflects the risk associated with each policy. Most insurers base their...

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Bibliographic Details
Main Author: Sunna Víðisdóttir 1994-
Other Authors: Háskóli Íslands
Format: Thesis
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/1946/31860
id ftskemman:oai:skemman.is:1946/31860
record_format openpolar
spelling ftskemman:oai:skemman.is:1946/31860 2023-05-15T16:52:30+02:00 Pricing of Automobile Insurance Policies using Generalized Linear Models and Lasso Regularization Sunna Víðisdóttir 1994- Háskóli Íslands 2018-09 application/pdf http://hdl.handle.net/1946/31860 en eng http://hdl.handle.net/1946/31860 Tölfræði Tryggingar Farartæki Spálíkön Reiknilíkön Eignatjón Kostnaður Thesis Master's 2018 ftskemman 2022-12-11T06:58:36Z The goal of this thesis is to create a predictive model for the expected claim cost of automobile insurance policies in Iceland. The proposed model is based on the characteristics of the policyholder and the insured vehicle, and reflects the risk associated with each policy. Most insurers base their premium structure on the expected cost of claims, making a model with good future prediction capabilities a valuable resource for the insurer. The data used in this thesis is provided by the Icelandic insurance company TM, and contains policy and claims data from 2009-2017. Automobile insurance policies at TM are considered to consist of five product components, but since the components vary significantly in what they cover, each product component is modelled separately in this thesis. The predicted claim cost of each product component is determined by three parts; a frequency model of standard claims, a claim severity model of standard claims, and a large loss model. The main focus is on the frequency and severity models of standard claims which are modelled using a Poisson regression model and a gamma regression model respectively. This results in a compound Poisson distribution for the total cost of standard claims. The parameters of the two models are selected using lasso regularization. Finally, the predictive ability of the models is assessed using cross-validation. The results show that the optimal predictive model for each of the five product components is quite different with regards to the choice of variables, demonstrating the importance of modelling each product component separately. The selected parameters for the frequency and the severity models of standard claims also differ, and by analyzing the two separately, a better understanding of the underlying risk is obtained. It is our believe that the modelling framework presented in this thesis can easily improve the current tariff structure at TM, and improve the competitiveness of the company. Markmið þessarar ritgerðar er að búa til spálíkan fyrir ... Thesis Iceland Skemman (Iceland)
institution Open Polar
collection Skemman (Iceland)
op_collection_id ftskemman
language English
topic Tölfræði
Tryggingar
Farartæki
Spálíkön
Reiknilíkön
Eignatjón
Kostnaður
spellingShingle Tölfræði
Tryggingar
Farartæki
Spálíkön
Reiknilíkön
Eignatjón
Kostnaður
Sunna Víðisdóttir 1994-
Pricing of Automobile Insurance Policies using Generalized Linear Models and Lasso Regularization
topic_facet Tölfræði
Tryggingar
Farartæki
Spálíkön
Reiknilíkön
Eignatjón
Kostnaður
description The goal of this thesis is to create a predictive model for the expected claim cost of automobile insurance policies in Iceland. The proposed model is based on the characteristics of the policyholder and the insured vehicle, and reflects the risk associated with each policy. Most insurers base their premium structure on the expected cost of claims, making a model with good future prediction capabilities a valuable resource for the insurer. The data used in this thesis is provided by the Icelandic insurance company TM, and contains policy and claims data from 2009-2017. Automobile insurance policies at TM are considered to consist of five product components, but since the components vary significantly in what they cover, each product component is modelled separately in this thesis. The predicted claim cost of each product component is determined by three parts; a frequency model of standard claims, a claim severity model of standard claims, and a large loss model. The main focus is on the frequency and severity models of standard claims which are modelled using a Poisson regression model and a gamma regression model respectively. This results in a compound Poisson distribution for the total cost of standard claims. The parameters of the two models are selected using lasso regularization. Finally, the predictive ability of the models is assessed using cross-validation. The results show that the optimal predictive model for each of the five product components is quite different with regards to the choice of variables, demonstrating the importance of modelling each product component separately. The selected parameters for the frequency and the severity models of standard claims also differ, and by analyzing the two separately, a better understanding of the underlying risk is obtained. It is our believe that the modelling framework presented in this thesis can easily improve the current tariff structure at TM, and improve the competitiveness of the company. Markmið þessarar ritgerðar er að búa til spálíkan fyrir ...
author2 Háskóli Íslands
format Thesis
author Sunna Víðisdóttir 1994-
author_facet Sunna Víðisdóttir 1994-
author_sort Sunna Víðisdóttir 1994-
title Pricing of Automobile Insurance Policies using Generalized Linear Models and Lasso Regularization
title_short Pricing of Automobile Insurance Policies using Generalized Linear Models and Lasso Regularization
title_full Pricing of Automobile Insurance Policies using Generalized Linear Models and Lasso Regularization
title_fullStr Pricing of Automobile Insurance Policies using Generalized Linear Models and Lasso Regularization
title_full_unstemmed Pricing of Automobile Insurance Policies using Generalized Linear Models and Lasso Regularization
title_sort pricing of automobile insurance policies using generalized linear models and lasso regularization
publishDate 2018
url http://hdl.handle.net/1946/31860
genre Iceland
genre_facet Iceland
op_relation http://hdl.handle.net/1946/31860
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