Combined loss reserving and premium rating by GLM

Bibliographic Details
Main Author: Mensah, Joel Agbo
Publication Date: 2023
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.5/27586
Summary: Mestrado Bolonha em Actuarial Science
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spelling Combined loss reserving and premium rating by GLMChain ladderBornhuetter-FergusonGLMRisk groupMestrado Bolonha em Actuarial ScienceGeneralised linear models(GLM) are routinely used in two different areas of actuarial work: Loss Reserving and Premium rating. There is little overlap between the two areas: Loss Reserving models attempt to model the development of claims but pays little attention to effect of risk variables. Premium Rating model attempt to model the effect of risk variables on claim patterns (frequency and/or severity), but usually assumes that the claims analysed are fully developed. In this dissertation, we aim to bridge the gap between these two areas of actuarial work by developing a Premium Rating model that incorporates risk variables. Specifically, we will consider demographic characteristics such as gender on claim patterns. By doing so, we hope to provide a more comprehensive understanding of the factors that contribute to insurance claims and improve insurers' ability to accurately price their policies, something which can be done in GLM but not in the original Chain Ladder or Bornheutter-Ferguson methods. The GLM approach is applied to real-life statistics of a professional health insurance that is sold to two risk groups, females and males. The results show that with the inclusion of the risk_group variable in the GLM model framework, females have higher claim cost per insured than males, plus that the number of females is increasing while the number of males is falling. The increase of the proportion of females is partly explained by the fact that more females are entering the profession. In a competitive market, the insurance company could risk adverse selection, if at the same time as more women enter, the lower risk group (males) starts falling because premiums are becoming too high. EU regulation does not allow insurers to differentiate premiums by sex. Therefore, the insurance will have to find other ways than premium differentiation, to prevent or reduce adverse selection. It is not my purpose to suggest what the company could do. The purpose of this dissertation is to demonstrate that the use of a GLM in loss reserving may show up facts that would remain concealed if one only used a simple chain ladder method on the aggregate statistics. The theoretical base of the work is standard; its challenges lies in applying GLM to realistic datasets and studying the results.Instituto Superior de Economia e GestãoNeuhaus, WaltherRepositório da Universidade de LisboaMensah, Joel Agbo2023-04-04T17:34:15Z2023-022023-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.5/27586engMensah, Joel Agbo (2023). “Combined loss reserving and premium rating by GLM ". Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T15:30:00Zoai:repositorio.ulisboa.pt:10400.5/27586Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T03:45:13.889050Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Combined loss reserving and premium rating by GLM
title Combined loss reserving and premium rating by GLM
spellingShingle Combined loss reserving and premium rating by GLM
Mensah, Joel Agbo
Chain ladder
Bornhuetter-Ferguson
GLM
Risk group
title_short Combined loss reserving and premium rating by GLM
title_full Combined loss reserving and premium rating by GLM
title_fullStr Combined loss reserving and premium rating by GLM
title_full_unstemmed Combined loss reserving and premium rating by GLM
title_sort Combined loss reserving and premium rating by GLM
author Mensah, Joel Agbo
author_facet Mensah, Joel Agbo
author_role author
dc.contributor.none.fl_str_mv Neuhaus, Walther
Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Mensah, Joel Agbo
dc.subject.por.fl_str_mv Chain ladder
Bornhuetter-Ferguson
GLM
Risk group
topic Chain ladder
Bornhuetter-Ferguson
GLM
Risk group
description Mestrado Bolonha em Actuarial Science
publishDate 2023
dc.date.none.fl_str_mv 2023-04-04T17:34:15Z
2023-02
2023-02-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/27586
url http://hdl.handle.net/10400.5/27586
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Mensah, Joel Agbo (2023). “Combined loss reserving and premium rating by GLM ". Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão.
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833601821059317760

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