Modeling non-life insurance price for risk without historical information

How should an insurer price a risk for which there is no history? This work intends to show, step by step, which main mechanisms are needed to capture the tariff model of another insurance company minimizing the risk involved. The document generally deals with the price-making mechanisms in non-life...

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Bibliographic Details
Main Author: Azevedo, Filipe Charters de (author)
Other Authors: Oliveira, Teresa A. (author), Oliveira, Amilcar (author)
Format: article
Language:eng
Published: 2021
Subjects:
Online Access:http://hdl.handle.net/10400.2/10718
Country:Portugal
Oai:oai:repositorioaberto.uab.pt:10400.2/10718
Description
Summary:How should an insurer price a risk for which there is no history? This work intends to show, step by step, which main mechanisms are needed to capture the tariff model of another insurance company minimizing the risk involved. The document generally deals with the price-making mechanisms in non-life insurance through the GLM regression models — Generalized Linear Model, more precisely the Poisson, Gamma and Tweedie models. Given the complexity of the application of these models in experimental design, it is studied a simpler way to characterize the rate, namely considering the Box–Cox transformation with SUR — Seemingly Unrelated Regression. An orthogonal experimental design to collect information is also presented as well as an application of these methods in the motor industry considering different companies.