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Cancer insurance pricing under different scenarios associated with diagnosis and treatment

Cancer insurance pricing under different scenarios associated with diagnosis and treatment
Cancer insurance pricing under different scenarios associated with diagnosis and treatment
We consider pricing of a specialised critical illness and life insurance contract for
breast cancer risk. We compare: (a) an industry-based Markov model with (b) a recently developed semi-Markov model, which accounts for unobserved breast cancer cases and progression through clinical stages of breast cancer, and (c) an alternative Markov model derived from (b). All models are calibrated using population data in England and data from the medical literature. We show that the semi-Markov model aligns best with empirical evidence. We then consider net premiums of specialised life insurance products under various scenarios of cancer diagnosis and treatment. The results show strong dependence on the time spent with diagnosed or undiagnosed pre-metastatic breast cancer. This proves to be significant for refining cancer survival estimates and accurately estimating related age-dependence by cancer stage. In contrast, the industry-based model, by overlooking this critical factor, is more sensitive to the model assumptions, underscoring its limitations in cancer estimates
semi-Markov model, model risk, multiple state models, Breast cancer, pricing
1748-4995
1-32
Arik, Ayse
32d5081b-55a4-44a0-938f-fba68e0ef296
Cairns, Andrew
27945b1c-4bb5-4b9c-9e4e-84ff6d590237
Dodd, Erengul
b3faed76-f22b-4928-a922-7f0b8439030d
Macdonald, Angus
c66b0677-4c66-4c1f-952c-aa05fea0cae9
Shao, Adam
9333291d-fb79-44af-b8cd-473886266db3
Streftaris, George
2cf1fc9b-9b00-4cf3-958e-0ccb4212a68d
Arik, Ayse
32d5081b-55a4-44a0-938f-fba68e0ef296
Cairns, Andrew
27945b1c-4bb5-4b9c-9e4e-84ff6d590237
Dodd, Erengul
b3faed76-f22b-4928-a922-7f0b8439030d
Macdonald, Angus
c66b0677-4c66-4c1f-952c-aa05fea0cae9
Shao, Adam
9333291d-fb79-44af-b8cd-473886266db3
Streftaris, George
2cf1fc9b-9b00-4cf3-958e-0ccb4212a68d

Arik, Ayse, Cairns, Andrew, Dodd, Erengul, Macdonald, Angus, Shao, Adam and Streftaris, George (2025) Cancer insurance pricing under different scenarios associated with diagnosis and treatment. Annals of Actuarial Science, 1-32. (doi:10.1017/S1748499524000332).

Record type: Article

Abstract

We consider pricing of a specialised critical illness and life insurance contract for
breast cancer risk. We compare: (a) an industry-based Markov model with (b) a recently developed semi-Markov model, which accounts for unobserved breast cancer cases and progression through clinical stages of breast cancer, and (c) an alternative Markov model derived from (b). All models are calibrated using population data in England and data from the medical literature. We show that the semi-Markov model aligns best with empirical evidence. We then consider net premiums of specialised life insurance products under various scenarios of cancer diagnosis and treatment. The results show strong dependence on the time spent with diagnosed or undiagnosed pre-metastatic breast cancer. This proves to be significant for refining cancer survival estimates and accurately estimating related age-dependence by cancer stage. In contrast, the industry-based model, by overlooking this critical factor, is more sensitive to the model assumptions, underscoring its limitations in cancer estimates

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More information

Accepted/In Press date: 22 December 2024
e-pub ahead of print date: 18 February 2025
Keywords: semi-Markov model, model risk, multiple state models, Breast cancer, pricing

Identifiers

Local EPrints ID: 498430
URI: http://eprints.soton.ac.uk/id/eprint/498430
ISSN: 1748-4995
PURE UUID: a33257dc-313c-4876-b934-75845fc7a480
ORCID for Erengul Dodd: ORCID iD orcid.org/0000-0001-6658-0990

Catalogue record

Date deposited: 18 Feb 2025 17:39
Last modified: 22 Aug 2025 02:10

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Contributors

Author: Ayse Arik
Author: Andrew Cairns
Author: Erengul Dodd ORCID iD
Author: Angus Macdonald
Author: Adam Shao
Author: George Streftaris

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