Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.8
2.0
Journals
Risks
Special Issues
Life Insurance and Pensions: Latest Advances and Prospects
share announcement

Life Insurance and Pensions: Latest Advances and Prospects

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: closed (31 October 2024) | Viewed by 7239

Special Issue Editors

Prof. Dr. Pierre Devolder

E-Mail Website
Guest Editor
Institute of Statistics, Biostatistics and Actuarial Sciences, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium
Interests: life insurance valuation; pension theory; public pension schemes; quantitative finance; solvency 2
Prof. Dr. Massimiliano Menzietti

E-Mail Website
Guest Editor
Department of Economics, Statistics and Finance, University of Calabria, 87036 Rende, Italy
Interests: longevity risk; disability risk; NDC pension systems; long term care insurance; health insurance

Special Issue Information

Dear Colleagues,

Life insurance and pension schemes have been recently exposed to new challenges and risk factors in a general environment characterized, from a financial point of view, by persistent low interest rates, volatile stock markets, and inflation shocks, and from a demographic perspective, by longevity improvement and aging. In many markets, the design of life insurance products and occupational pension schemes has changed with the development of new hybrid products based on alternative risk-sharing philosophies. These product evolutions require new valuation tools. New issues appear in the accumulation phase as well as in the decumulation phase (annuitization, tontines). New models are requested for mortality risk and its links with finance. Financial sustainability of public pension systems is also a major concern for our societies, necessitating new actuarial and financial analysis that mixes social and financial constraints such as the automatic balance mechanisms. From a more methodological perspective, new statistical methods such as machine learning, neural networks, etc., traditionally more oriented to non-life insurance, are more and more relevant for life insurance problems. Last but not least, as massive investors, life insurance and pension funds will have to integrate environmental constraints (ESG) into their strategies.

Authors are invited to submit papers that address these various design and valuation challenges for life insurance products and pension schemes (occupational and public pension schemes).

Prof. Dr. Pierre Devolder
Prof. Dr. Massimiliano Menzietti
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Risks is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • life insurance products
  • occupational pension schemes
  • public pension systems
  • valuation tools
  • mortality and demographic models
  • annuitization and tontines
  • inflation risk
  • machine learning applications
  • ESG for life insurers and pension funds

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

17 pages, 12461 KiB  
Article
A Contrast-Tree-Based Approach to Two-Population Models
by Matteo Lizzi
Risks 2024, 12(10), 152; https://doi.org/10.3390/risks12100152 - 25 Sep 2024
Viewed by 393
Abstract
Building small-population mortality tables has great practical importance in actuarial applications. In recent years, several works in the literature have explored different methodologies to quantify and assess longevity and mortality risk, especially within the context of small populations, and many models dealing with [...] Read more.
Building small-population mortality tables has great practical importance in actuarial applications. In recent years, several works in the literature have explored different methodologies to quantify and assess longevity and mortality risk, especially within the context of small populations, and many models dealing with this problem usually use a two-population approach, modeling a mortality spread between a larger reference population and the population of interest, via likelihood-based techniques. To broaden the tools at actuaries’ disposal to build small-population mortality tables, a general structure for a two-step two-population model is proposed, its main element of novelty residing in a machine-learning-based approach to mortality spread estimation. In order to obtain this, Contrast Trees and the related Estimation Contrast Boosting techniques have been applied. A quite general machine-learning-based model has then been adapted in order to generalize Italian actuarial practice in company tables estimation and implemented using data from the Human Mortality Database. Finally, results from the ML-based model have been compared to those obtained from the traditional model. Full article
(This article belongs to the Special Issue Life Insurance and Pensions: Latest Advances and Prospects)
►▼ Show Figures

Figure 1

11 pages, 1168 KiB  
Article
Sustaining Algeria’s Retirement System in the Population Aging Context: Could a Contribution Cap Strategy Work?
by Farid Flici and Inmaculada Dominguez-Fabian
Risks 2024, 12(6), 96; https://doi.org/10.3390/risks12060096 - 14 Jun 2024
Viewed by 1364
Abstract
Previous research predicts an increasing financial deficit in Algeria’s PAYG retirement system, mainly due to rapid population aging, and parametric adjustments will be insufficient to alleviate this imbalance. Mitigating the effects of population aging will necessitate further intervention. In this work, we analyze [...] Read more.
Previous research predicts an increasing financial deficit in Algeria’s PAYG retirement system, mainly due to rapid population aging, and parametric adjustments will be insufficient to alleviate this imbalance. Mitigating the effects of population aging will necessitate further intervention. In this work, we analyze how capping contributed salaries can help to mitigate the effects of population aging on the retirement system. Under generous Pay-As-You-Go schemes, promised pension payouts far exceed contributions. Thus, restricting contributions is expected to reduce the burden of future benefits by accepting lower contributions today, while directing public subsidies to low-income individuals. We simulate the future evolution of the financial balance of Algeria’s retirement system under various contributable salary caps versus various scenarios of environmental evolution and potential parametric reform actions. The results demonstrated that a 40% cap, along with major parametric reforms and an ideal environment, would help achieve a cumulatively balanced system in the long run. Full article
(This article belongs to the Special Issue Life Insurance and Pensions: Latest Advances and Prospects)
►▼ Show Figures

Figure 1

31 pages, 1109 KiB  
Article
Relationship between Occupational Pension, Corporate Social Responsibility (CSR), and Organizational Resilience: A Study on Listed Chinese Companies
by Hao Wang, Tao Zhang, Xi Wang and Jiansong Zheng
Risks 2024, 12(4), 65; https://doi.org/10.3390/risks12040065 - 9 Apr 2024
Viewed by 1644
Abstract
Numerous researchers acknowledge that the occupational pension protects employees. However, in China, the total cost of occupational pensions is shared between employees and employers, representing a significant financial commitment. This study aimed to explore the effect of the occupational pension on corporate social [...] Read more.
Numerous researchers acknowledge that the occupational pension protects employees. However, in China, the total cost of occupational pensions is shared between employees and employers, representing a significant financial commitment. This study aimed to explore the effect of the occupational pension on corporate social responsibility (CSR) and organizational resilience. Drawing on insights from cost-stickiness and resource-based theories, we developed a model that elucidated the influence of occupational pensions on firms’ approaches to CSR within the context of COVID-19 and how this, in turn, impacted organizational resilience. This study categorized CSR into strategic and responsive activities, employing the concept of cost stickiness as a framework. We analyzed a sample of 34,145 observations from Chinese A-share listed companies spanning the period 2010–2023 to examine the influence of occupational pension adjustments on CSR strategies. The findings of this study revealed that the cost pressure associated with contributions to occupational pensions prompted firms to decrease their engagement in responsive CSR activities while enhancing their strategic CSR initiatives. Furthermore, it was observed that strategic CSR contributed to improved organizational resilience, whereas responsive CSR did not exhibit the same effect. The relationship between occupational pension contributions and CSR was found to be significantly and negatively moderated by factors such as the minimum wage and population aging. Conversely, the relationship between CSR and organizational resilience was significantly and positively moderated by digital transformation and marketing capabilities. Full article
(This article belongs to the Special Issue Life Insurance and Pensions: Latest Advances and Prospects)
►▼ Show Figures

Figure 1

14 pages, 1665 KiB  
Article
Dynamic Liability-Driven Investment under Sponsor’s Loss Aversion
by Dong-Hwa Lee and Joo-Ho Sung
Risks 2024, 12(2), 38; https://doi.org/10.3390/risks12020038 - 13 Feb 2024
Viewed by 1503
Abstract
This paper investigates a dynamic liability-driven investment policy for defined-benefit (DB) plans by incorporating the loss aversion of a sponsor, who is assumed to be more sensitive to underfunding than overfunding. Through the lens of prospect theory, we first set up a loss-aversion [...] Read more.
This paper investigates a dynamic liability-driven investment policy for defined-benefit (DB) plans by incorporating the loss aversion of a sponsor, who is assumed to be more sensitive to underfunding than overfunding. Through the lens of prospect theory, we first set up a loss-aversion utility function for a sponsor whose utility depends on the funding ratio in each period, obtained from stochastic processes of pension assets and liabilities. We then construct a multi-horizon dynamic control optimization problem to find the optimal investment strategy that maximizes the expected utility of the plan sponsor. A genetic algorithm is employed to provide a numerical solution for our nonlinear dynamic optimization problem. Our results suggest that the overall paths of the optimal equity allocation decline as the age of a plan participant reaches retirement. We also find that the equity portion of the portfolio increases when a sponsor is less loss-averse or the contribution rate is lower. Full article
(This article belongs to the Special Issue Life Insurance and Pensions: Latest Advances and Prospects)
►▼ Show Figures

Figure 1

33 pages, 1869 KiB  
Article
Pricing Life Contingencies Linked to Impaired Life Expectancies Using Intuitionistic Fuzzy Parameters
by Jorge de Andrés-Sánchez
Risks 2024, 12(2), 29; https://doi.org/10.3390/risks12020029 - 2 Feb 2024
Cited by 2 | Viewed by 1577
Abstract
Several life contingency agreements are based on the assumption that policyholders have impaired life expectancy attributable to factors, such as lifestyle, social class, or preexisting health issues. Quantifying two crucial variables, augmented death probabilities and the discount rate of projected cash flows, is [...] Read more.
Several life contingency agreements are based on the assumption that policyholders have impaired life expectancy attributable to factors, such as lifestyle, social class, or preexisting health issues. Quantifying two crucial variables, augmented death probabilities and the discount rate of projected cash flows, is essential for pricing such agreements. Information regarding the correct values of these parameters is subject to vagueness and imprecision, which further intensifies if impairments must be considered. This study proposes modelling mortality and interest rates using a generalization of fuzzy numbers (FNs), known as intuitionistic fuzzy numbers (IFNs). Consequently, this paper extends the literature on life contingency pricing with fuzzy parameters, where uncertainty in variables, such as interest rates and death probabilities, is modelled using FNs. While FNs introduce epistemic uncertainty, the use of IFNs adds bipolarity to the analysis by incorporating both positive and negative information regarding actuarial variables. Our analysis focuses on two agreements involving policyholders with impaired life expectancies: determining the annuity payment in a substandard annuity and pricing a life settlement over a whole life insurance policy. In particular, we emphasize modelling interest rates and survival probabilities using triangular intuitionistic fuzzy numbers (TIFNs) owing to their ease of interpretation and implementation. Full article
(This article belongs to the Special Issue Life Insurance and Pensions: Latest Advances and Prospects)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop