Daly, Linda
ORCID: 0009-0002-2982-6407
(2025)
Mortality Modelling for Actuarial applications: Challenges and Implications for Pension Sustainability and Insurance Pricing.
PhD thesis, Dublin City University.
Abstract
Mortality forecasting and longevity risk are critical concerns for insurers, employers offering occupational pension schemes, and governments providing state pensions and social welfare benefits. Moreover, as many countries, including Ireland, experience
an ageing population, increased longevity raises pension costs, potentially undermining the sustainability of funding models used by both Companies and the state. However, accurately estimating mortality rates and forecasting future trends remains a significant challenge. For instance, the SARS-CoV-2 pandemic had a profound
impact on mortality rates from 2020-2022 with potential long-term effects. While the death toll of a country often serves as the ultimate indicator of pandemic impact, the calculation of excess deaths (deaths beyond expected levels) is complex and subjective. Seasonal mortality variations also pose risks, with factors such as
climate change, medical advances, and improvements in living standards disrupting established patterns, adding uncertainty for insurers and policymakers. Accurate mortality estimation for those retiring due to ill health is another complex issue.Ill-health retirement rates increase with age and are higher for females. As pension
schemes raise retirement ages in line with increasing life expectancy and more females join the workforce, the mortality of ill-health retirees will become increasingly important. This is an especially important consideration for employers providing
occupational pensions and insurers providing insurance for these benefits and/or selling impaired life annuities. Modelling these mortality challenges is particularly difficult for smaller populations, where mortality rates can be highly volatile. In Ireland and Northern Ireland, current national life tables have shown inconsistent
patterns, lack regional coherence, and exhibit volatile mortality trends. By jointly modelling mortality across different populations, the accuracy and coherence of forecasts can be improved. Joint modelling, or multi-population modelling, enhances the robustness of final graduated rates by allowing populations to borrow strength
from each other. This thesis provides insights into these evolving mortality challenges, contributing to more informed decision-making and ultimately improving the long-term sustainability of pension schemes (both private and public) and increasing the offering of accurately priced pension products.
Metadata
| Item Type: | Thesis (PhD) |
|---|---|
| Date of Award: | 27 August 2025 |
| Refereed: | No |
| Supervisor(s): | Hall, Mary |
| Subjects: | Mathematics Mathematics > Mathematical analysis |
| DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Science and Health DCU Faculties and Schools > Faculty of Science and Health > School of Mathematical Sciences |
| Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 License. View License |
| ID Code: | 31483 |
| Deposited On: | 27 Nov 2025 10:42 by Mary Hall . Last Modified 27 Nov 2025 10:42 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Creative Commons: Attribution-Noncommercial-No Derivative Works 4.0 13MB |
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record