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Risks
Special Issues
Innovations in Annuities and Longevity Risk Management
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Innovations in Annuities and Longevity Risk Management

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

Deadline for manuscript submissions: 15 June 2026 | Viewed by 663

Special Issue Editors

Dr. Nan Zhu

E-Mail Website
Guest Editor
Department of Risk Management, Smeal College of Business, Pennsylvania State University, University Park, PA 16802, USA
Interests: stochastic mortality modeling; secondary life market; longevity risk management; insurance contract theory
Prof. Dr. Richard MacMinn

E-Mail Website
Guest Editor
1. Department of Information, Risk, and Operations Management, McCombs School of Business, The University of Texas at Austin, Austin, TX, USA
2. Risk and Insurance Center, College of Commerce, National Chengchi University, Taipei, Taiwan
Interests: corporate risk management; financial market theory; CAT risk; longevity risk; risk management and insurance

Special Issue Information

Dear Colleagues,

We invite researchers, practitioners, and policymakers to submit their original research for the upcoming Special Issue of Risks on longevity risk and innovations in annuities.

The COVID-19 pandemic has underscored the importance of longevity risk management, as it has accelerated demographic changes and highlighted potential vulnerabilities in retirement planning. With the population aging globally and life expectancies fluctuating in response to health crises, there is an urgent need for innovative solutions to address the financial challenges associated with longevity risk.

This Special Issue will explore dimensions of longevity risk, including its impact on individuals, corporations, government, pension systems, and financial markets. We are particularly interested in contributions investigating innovations in retirement products and markets, risk management strategies and financial instruments necessary to implement the strategies, and relevant policy implications. Topics may include but are not limited to the following: the development of flexible and adaptive annuity products, the analysis of alternative retirement products such as modernized tontines or decentralized annuities, the integration of longevity risk into retirement financial planning, and the role of modern technology and data analytics in shaping products and markets.

For further submission information, please visit the Risks website or contact the Special Issue editors. We look forward to receiving insightful contributions. 

Dr. Nan Zhu
Prof. Dr. Richard MacMinn
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

  • longevity risk
  • mortality risk
  • annuities
  • tontines
  • decentralized annuities
  • retirement planning
  • pensions
  • blockchain, innovative technology, and machine learning

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Published Papers (1 paper)

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Research

28 pages, 1343 KB  
Article
Understanding Reverse Mortgage Acceptance in Spain with Explainable Machine Learning and Importance–Performance Map Analysis
by Jorge de Andrés-Sánchez and Laura González-Vila Puchades
Risks 2025, 13(11), 212; https://doi.org/10.3390/risks13110212 (registering DOI) - 2 Nov 2025
Abstract
In developed countries such as Spain, where the population is increasingly aging, retirement planning and longevity risk represent major societal challenges. In Spain, in particular, a significant proportion of household wealth is concentrated in real estate, primarily in the form of owner-occupied housing. [...] Read more.
In developed countries such as Spain, where the population is increasingly aging, retirement planning and longevity risk represent major societal challenges. In Spain, in particular, a significant proportion of household wealth is concentrated in real estate, primarily in the form of owner-occupied housing. For this reason, one emerging financial product in the retirement savings space is the reverse mortgage (RM). This study examines the determinants of acceptance of this financial product using survey data collected from Spanish individuals. The intention to take out an RM is explained through performance expectancy (PE), effort expectancy (EE), social influence (SI), bequest motive (BM), financial literacy (FL), and risk (RK). The analysis applies machine learning techniques: decision tree regression is used to visualize variable interactions that lead to acceptance; random forest to improve predictive capability; and Shapley Additive Explanations (SHAP) to estimate the relative importance of predictors. Finally, Importance–Performance Map Analysis (IPMA) is employed to identify the variables that merit greater attention in the acceptance of RMs. SHAP values indicate that PE and SI are the most influential predictors of intention to use RMs, followed by BM and EE with moderate importance, whereas the positive influence of RK and FL is more reduced. The IPMA highlights PE and SI as the most strategic drivers, and RK and BM act as relevant barriers to the widespread adoption of RMs. Full article
(This article belongs to the Special Issue Innovations in Annuities and Longevity Risk Management)
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