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Bayesian modelling of the time delay between diagnosis and settlement for Critical Illness Insurance using a Burr generalised-linear-type model

Bayesian modelling of the time delay between diagnosis and settlement for Critical Illness Insurance using a Burr generalised-linear-type model
Bayesian modelling of the time delay between diagnosis and settlement for Critical Illness Insurance using a Burr generalised-linear-type model
We discuss Bayesian modelling of the delay between dates of diagnosis and settlement of claims in Critical Illness Insurance using a Burr distribution. The data are supplied by the UK Continuous Mortality Investigation and relate to claims settled in the years 1999–2005. There are non-recorded dates of diagnosis and settlement and these are included in the analysis as missing values using their posterior predictive distribution and MCMC methodology. The possible factors affecting the delay (age, sex, smoker status, policy type, benefit amount, etc.) are investigated under a Bayesian approach. A 3-parameter Burr generalised-linear-type model is fitted, where the covariates are linked to the mean of the distribution. Variable selection using Bayesian methodology to obtain the best model with different prior distribution setups for the parameters is also applied. In particular, Gibbs variable selection methods are considered, and results are confirmed using exact marginal likelihood findings and related Laplace approximations. For comparison purposes, a lognormal model is also considered
0167-6687
266-279
Ozkok, Erengul
b3faed76-f22b-4928-a922-7f0b8439030d
Streftaris, George
c183b8ea-cf3f-4f5c-8266-b4486b458792
Waters, Howard R.
4e0e6216-6ea1-4034-91b3-0224f00c0ad8
Wilkie, A. David
17e3f2b6-25cd-4b8e-8d38-a92c5261dfe7
Ozkok, Erengul
b3faed76-f22b-4928-a922-7f0b8439030d
Streftaris, George
c183b8ea-cf3f-4f5c-8266-b4486b458792
Waters, Howard R.
4e0e6216-6ea1-4034-91b3-0224f00c0ad8
Wilkie, A. David
17e3f2b6-25cd-4b8e-8d38-a92c5261dfe7

Ozkok, Erengul, Streftaris, George, Waters, Howard R. and Wilkie, A. David (2012) Bayesian modelling of the time delay between diagnosis and settlement for Critical Illness Insurance using a Burr generalised-linear-type model. Insurance: Mathematics and Economics, 50 (2), 266-279. (doi:10.1016/j.insmatheco.2011.12.001).

Record type: Article

Abstract

We discuss Bayesian modelling of the delay between dates of diagnosis and settlement of claims in Critical Illness Insurance using a Burr distribution. The data are supplied by the UK Continuous Mortality Investigation and relate to claims settled in the years 1999–2005. There are non-recorded dates of diagnosis and settlement and these are included in the analysis as missing values using their posterior predictive distribution and MCMC methodology. The possible factors affecting the delay (age, sex, smoker status, policy type, benefit amount, etc.) are investigated under a Bayesian approach. A 3-parameter Burr generalised-linear-type model is fitted, where the covariates are linked to the mean of the distribution. Variable selection using Bayesian methodology to obtain the best model with different prior distribution setups for the parameters is also applied. In particular, Gibbs variable selection methods are considered, and results are confirmed using exact marginal likelihood findings and related Laplace approximations. For comparison purposes, a lognormal model is also considered

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Published date: March 2012
Organisations: Statistics

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Local EPrints ID: 358092
URI: http://eprints.soton.ac.uk/id/eprint/358092
ISSN: 0167-6687
PURE UUID: 2e554421-c3eb-43de-b0f8-b17365aaa5b1
ORCID for Erengul Ozkok: ORCID iD orcid.org/0000-0001-6658-0990

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Date deposited: 04 Oct 2013 08:41
Last modified: 15 Mar 2024 03:49

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Contributors

Author: Erengul Ozkok ORCID iD
Author: George Streftaris
Author: Howard R. Waters
Author: A. David Wilkie

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