Hierarchical Gaussian Process Models For Loss Reserving

Loss reserving is one of the main activities of actuaries in the insurance industry and is done to ensure the financial health of companies as well as protecting consumers’ interest. Techniques applied by the practitioners are highly regulated, but researchers are still ongoing in the pursuit of...

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Main Author: Ang, Zi Qing
Format: Thesis
Language:English
Published: 2021
Subjects:
Online Access:http://eprints.usm.my/59138/
http://eprints.usm.my/59138/1/24%20Pages%20from%20ANG%20ZI%20QING%20-%20TESIS.pdf
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author Ang, Zi Qing
author_facet Ang, Zi Qing
author_sort Ang, Zi Qing
building USM Institutional Repository
collection Online Access
description Loss reserving is one of the main activities of actuaries in the insurance industry and is done to ensure the financial health of companies as well as protecting consumers’ interest. Techniques applied by the practitioners are highly regulated, but researchers are still ongoing in the pursuit of finding methods to improve predictive accuracy and to establish a measure of predictive uncertainties. Diverting from the link ratio methods, researchers have experimented with parametric models such as growth-curve models and models involving dynamical systems, as well as nonparametric models. Researchers in this field have increasingly shown interests in utilizing Bayesian methods to measure predictive uncertainties.
first_indexed 2025-11-15T19:01:16Z
format Thesis
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institution Universiti Sains Malaysia
institution_category Local University
language English
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publishDate 2021
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spelling usm-591382023-08-18T01:19:56Z http://eprints.usm.my/59138/ Hierarchical Gaussian Process Models For Loss Reserving Ang, Zi Qing QA1 Mathematics (General) Loss reserving is one of the main activities of actuaries in the insurance industry and is done to ensure the financial health of companies as well as protecting consumers’ interest. Techniques applied by the practitioners are highly regulated, but researchers are still ongoing in the pursuit of finding methods to improve predictive accuracy and to establish a measure of predictive uncertainties. Diverting from the link ratio methods, researchers have experimented with parametric models such as growth-curve models and models involving dynamical systems, as well as nonparametric models. Researchers in this field have increasingly shown interests in utilizing Bayesian methods to measure predictive uncertainties. 2021-12 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/59138/1/24%20Pages%20from%20ANG%20ZI%20QING%20-%20TESIS.pdf Ang, Zi Qing (2021) Hierarchical Gaussian Process Models For Loss Reserving. Masters thesis, Perpustakaan Hamzah Sendut.
spellingShingle QA1 Mathematics (General)
Ang, Zi Qing
Hierarchical Gaussian Process Models For Loss Reserving
title Hierarchical Gaussian Process Models For Loss Reserving
title_full Hierarchical Gaussian Process Models For Loss Reserving
title_fullStr Hierarchical Gaussian Process Models For Loss Reserving
title_full_unstemmed Hierarchical Gaussian Process Models For Loss Reserving
title_short Hierarchical Gaussian Process Models For Loss Reserving
title_sort hierarchical gaussian process models for loss reserving
topic QA1 Mathematics (General)
url http://eprints.usm.my/59138/
http://eprints.usm.my/59138/1/24%20Pages%20from%20ANG%20ZI%20QING%20-%20TESIS.pdf