Longevity risk and capital markets: The 2019-20 update

Blake, David; Cairns, Andrew J. G.

doi:10.1016/j.insmatheco.2021.04.001

Cited by 12 publications

(8 citation statements)

References 362 publications

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“…Q1.3: There is not a significant number of publications on machine-learning application models in the final selection, mainly because, despite initially being the category with the most significant number of searches, they presented studies related to treating or diagnosing diseases and not specifically related to life insurance pricing. Regarding the articles reviewed, multi-modal models of the GLM type or Bayesian networks are applied to the prediction of longevity risks [39][40][41][42].…”

Section: Results and Findingsmentioning

confidence: 99%

Potential Applications of Explainable Artificial Intelligence to Actuarial Problems

Lozano-Murcia,

Romero,

Serrano-Guerrero

et al. 2024

Mathematics

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Explainable artificial intelligence (XAI) is a group of techniques and evaluations that allows users to understand artificial intelligence knowledge and increase the reliability of the results produced using artificial intelligence. XAI can assist actuaries in achieving better estimations and decisions. This study reviews the current literature to summarize XAI in common actuarial problems. We proposed a research process based on understanding the type of AI used in actuarial practice in the financial industry and insurance pricing and then researched XAI implementation. This study systematically reviews the literature on the need for implementation options and the current use of explanatory artificial intelligence (XAI) techniques for actuarial problems. The study begins with a contextual introduction outlining the use of artificial intelligence techniques and their potential limitations, followed by the definition of the search equations used in the research process, the analysis of the results, and the identification of the main potential fields for exploitation in actuarial problems, as well as pointers for potential future work in this area.

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Section: Results and Findingsmentioning

confidence: 99%

Potential Applications of Explainable Artificial Intelligence to Actuarial Problems

Lozano-Murcia,

Romero,

Serrano-Guerrero

et al. 2024

Mathematics

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“…Milevsky (2020) analyzes, among many other topics, the mortality growth, under COVID-19, and its impact on utility valuations of annuities, and concludes that there is a need for stochastic mortality models. Blake and Cairns (2021) describe how longevity risk affects pension risk, and the impact of the COVID-19 pandemic. They describe different types of financial securities that exist to minimize longevity risk.…”

Section: Introductionmentioning

confidence: 99%

The shock of COVID‐19 and the shock of rapid vaccine development on the value of senior life settlement contracts

Ortiz,

Stone,

Zissu

2023

Risk Manage Insurance Review

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In this paper, we develop a model that can capture how COVID‐19 and the subsequent rapid vaccine development against COVID‐19 impacts the value of pools of senior life settlements. The pandemic unexpectedly boosted the mortality rates of senior citizens who had prior diagnoses of certain health conditions. Our model accounts for the existence and concentration of these COVID‐19 comorbidities in portfolios of senior life settlements. It is the concentration of assets linked to the mortality rates of a group who is at elevated risk to COVID‐19 and who is also the primary beneficiaries of the COVID‐19 vaccine that we examine. We illustrate how the shock of the pandemic increases the value of senior life settlements and how the accelerated development and distribution of COVID‐19 vaccines moderated this increase. Our model is general enough to simulate the impact on other financial contracts that are linked to individual mortality rates. These would include life insurance contracts, annuities, and health insurance policies.

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“…The “life market” where mortality-linked derivatives and securities are traded is constantly evolving. Readers are referred to Blake and Cairns ( 2021 ) for an overview of the current state of this market. There, the management of longevity risk via mortality-linked instruments inadvertently leads to the issue of basis risk.…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, due to different realized longevity experiences among different populations, the risk of imperfect hedging, called (longevity) basis risk, arises. To measure and manage this risk, multi-population mortality models that give a joint characterization of the mortality experience of different populations are important and remain an active field of investigation in actuarial science (see Blake and Cairns 2021 ; Enchev et al. 2016 for the summary).…”

Section: Introductionmentioning

confidence: 99%

Multi-population mortality modeling with Lévy processes

Jevtic

Qin²,

Zhou

2023

Decisions Econ Finan

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This paper constructs a theoretical framework for multi-population mortality modeling via generalized linear models and Lévy stochastic perturbations driven by a common Brownian motion and idiosyncratic factors to capture the mortality shocks. By having Lévy stochastic perturbations, our model admits various jump types, which is increasingly important for capturing mortality shocks such as pandemics, particularly when they affect various populations differently. At the same time, the proposed model allows a novel dependence structure of multiple populations, which is essential when it comes to the development of multi-population or joint-life products in the context of mortality shocks. In our empirical investigations, the mortality experiences of male and female lives in the UK and Japan are used. Compared with pure Poisson-generalized linear models, the proposed multi-population model shows superiority in predicting future mortality rates.

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Longevity risk and capital markets: The 2019-20 update

Cited by 12 publications

References 362 publications

Potential Applications of Explainable Artificial Intelligence to Actuarial Problems

Potential Applications of Explainable Artificial Intelligence to Actuarial Problems

The shock of COVID‐19 and the shock of rapid vaccine development on the value of senior life settlement contracts

Multi-population mortality modeling with Lévy processes

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