Longevity Risk Transfer Research Articles

Two-Population Mortality Forecasting: An Approach Based on Model Averaging

The analysis of residual life expectancy evolution at retirement age holds great importance for life insurers and pension schemes. Over the last 30 years, numerous models for forecasting mortality have been introduced, and those that allow us to predict the mortality of two or more related populations simultaneously are particularly important. Indeed, these models, in addition to improving the forecasting accuracy overall, enable evaluation of the basis risk in index-based longevity risk transfer deals. This paper implements and compares several model-averaging approaches in a two-population context. These approaches generate predictions for life expectancy and the Gini index by averaging the forecasts obtained using a set of two-population models. In order to evaluate the eventual gain of model-averaging approaches for mortality forecasting, we quantitatively compare their performance to that of the individual two-population models using a large sample of different countries and periods. The results show that, overall, model-averaging approaches are superior both in terms of mean absolute forecasting error and interval forecast accuracy.

Resilience in a time of crisis: how COVID-19 pandemic insights are supporting a vibrant longevity risk transfer market

AbstractPension risk transfer and longevity risk transfer are now growing secular trends. From North America to Europe, companies are de-risking pension plans in near-record volumes and have continued to boldly do so throughout the pandemic—at or near the most favorable pricing experienced in years. The arrival of funded reinsurance on both sides of the Atlantic is bringing reinsurer capital and private assets to support the steady growth in the pension risk transfer market. Additionally, we have observed that the enduring low-rate environment and quest for uncorrelated risk has the world's largest investors directing billions into life reinsurance sidecars. How have these markets thrived during the worst global outbreak in a century? Key research on the pandemic's impact on pensioner life expectancy allowed prices to be set and transactions to proceed through a time of significant uncertainty.

On the economics of the longevity risk transfer market

AbstractWe present a model of a longevity risk transfer market with different market players (primary insurers, reinsurers, and capital market investors) and investigate how market dynamics and the market players' roles evolve with progressing market saturation. We find that reinsurers' appetite for longevity risk is the key driver in the early stage of market development. Since diversification benefits with other businesses decrease with every transaction, the reinsurance market is intrinsically antimonopolistic. With the increasing saturation of the reinsurance sector as a whole, its competitiveness shrinks leading to rising expected risk‐adjusted returns for capital market investors. We show that in a saturated market, reinsurers should assume the entire longevity risk from primary insurers, diversify it within their business mix, and subsequently pass on only specific (nondiversifiable) components of the longevity risk to the capital markets. Our findings provide valuable suggestions on how to make the best use of the market's limited risk absorption capacity.

Optimal longevity risk transfer under asymmetric information

Optimal longevity risk transfer under asymmetric information

Collective longevity swap: A novel longevity risk transfer solution and its economic pricing

To mitigate the hedger’s longevity risk exposure, this paper proposes a collective longevity swap between a reinsurer (hedge provider) and a group of hedgers (pension plans and annuity providers), and an economic framework to price longevity risk and longevity swaps. Combining the appealing features of two widely discussed longevity swaps, i.e., the indemnity swap and index-based swap, the collective longevity swap requires that reinsurer’s payments are based on the longevity risk of the aggregate portfolio of all hedgers, whereas each hedger could receive indemnity payments on their own portfolio. In a general principal-agent pricing model under the incomplete market setting, we determine the optimal risk premiums and hedge rates that maximize the reinsurer’s expected profit under a set of the hedgers’ participation constraints. We find that, in a competitive market, the proposed collective swap could lead to a higher expected profit for the reinsurer than the indemnity and the index-based swap, and simultaneously improve the benefits of the majority of hedgers without worsening the benefits of the rest. Finally, using a stochastic multi-population mortality model and real-world mortality data, a series of numerical analyses are performed to verify the theoretical findings.

TARGET VOLATILITY STRATEGIES FOR GROUP SELF-ANNUITY PORTFOLIOS

AbstractWhile the current pandemic is causing mortality shocks globally, the management of longevity risk remains a major challenge for both individuals and institutions. It is high time there be private market solutions designed for efficient longevity risk transfer among various stakeholders such as individuals, pension funds and annuity providers. From individuals’ point of view, appealing features of post-retirement solutions include stable and satisfactory benefit levels, flexibility, meeting bequest preferences and low fees. This paper proposes a dynamic target volatility strategy for group self-annuitization (GSA) schemes aimed at enhancing living benefits for pool participants. More specifically, we suggest investing GSA funds in a portfolio consisting of equity and cash, continuously rebalanced to maintain a target volatility level. The performance of a dynamic target volatility strategy is assessed against the static case which does not involve portfolio rebalancing. Benefit profiles are assessed by analysing quantiles and alternative strategies involving varying equity compositions. The case of death benefits is included, and the fund dynamics analysed by assessing resulting investment returns and the mortality credits. Overall, higher living benefit profiles are obtained under a dynamic target volatility strategy. From the analysis performed, a trade-off between the equity proportion and the impact on the lower quantile of the living benefit amount emerges, suggesting an optimal proportion of equity composition.

Modeling the Risk in Mortality Projections

Capturing the Uncertainty in Long-Term Mortality Forecasts The uncertainty in future longevity presents a substantial risk factor for insurance companies, pension funds, and retirement systems. In “Modeling the Risk in Mortality Projections,” Zhu and Bauer present novel stochastic models for analyzing this longevity risk that focus on the uncertainty associated with long-term mortality projections and capture the evolution of mortality forecasts over the past decades. They arrive at their models by analyzing time series of mortality forecasts in a forward modeling framework, which contrasts with conventional stochastic mortality models that are built on age-specific realized mortality rates. The authors showcase their models in exemplifying financial applications in both traditional life insurance markets and the emerging longevity risk transfer market. A key takeaway is that uncertainty in positions that depend on the long-term evolution of mortality is substantially greater under their models than suggested by conventional models.

Asymmetric Information and Longevity Risk Transfer

Asymmetric Information and Longevity Risk Transfer

Collective Longevity Swap: a Novel Longevity Risk Transfer Solution and Its Economic Pricing

Collective Longevity Swap: a Novel Longevity Risk Transfer Solution and Its Economic Pricing

Optimal Longevity Risk Transfer and Investment Strategies

Given the rising cost of maintaining defined benefit pensions, there has been a surge of activities in recent years by defined benefit plan sponsors to transfer their pension risk through strategies such as buy-ins and buy-outs. As buy-in and buy-out transaction pipelines grow, insurers actively participating in the buy-in and buy-out markets are exposed to significant longevity risk embedded in pension schemes. In this article, we investigate how to maximize a bulk annuity insurer’s value with reinsurance and/or longevity securities, subject to constraints that control longevity and investment risks as well as an overall risk. We apply duality and the martingale approach to derive an optimal longevity risk transfer strategy. Our results show that longevity risk transfer interacts with an insurer’s investment decision for value maximization. Our analysis also highlights the interdependence of different longevity risk management tools to achieve an overall risk target.

Reinsurance Sidecars: The Next Stage in the Development of the Longevity Risk Transfer Market

The longevity risk transfer market in Europe and North America remains in its infancy despite rapid growth in recent years, and further qualitative progress is needed to develop a commoditized market. Reinsurance sidecars, which are commonly used in the property and casualty market in the United States, have enormous potential to play an important role in such development. Transaction structures involving reinsurance sidecars can be adapted to benefit cedants and sponsoring reinsurers and also to attract a broader spectrum of investors and participants by reducing the long-tail risk inherent in longevity risk transfer. While several transaction structures are possible, each would fundamentally provide additional capital to support transactions in a form that is not subject to a requirement to hold a regulatory solvency capital buffer, thereby enabling sponsoring reinsurers to offer keener pricing to cedants. As a result, a European Union-based cedant could gain considerable capital benefits by reinsuring longevity risk, market risk or both to a reinsurance sidecar.

Hedging Longevity Risk: Does the Structure of the Financial Instrument Matter?

Longevity-linked securities can be constructed either as cash flow hedging instruments or as value hedging instruments. This article studies the interaction between the structure of longevity-linked securities and shareholder value. Relying on a strand of literature that investigates corporate risk management decisions made in the interests of shareholders, we present a framework that compares cash flow hedges with value hedges. Both our theoretical model and numerical experiments show that value hedging dominates cash flow hedging in the context of management decisions being made to maximize shareholder value. This finding provides an explanation for the failure of some attempted issues of longevity risk transfer instruments and suggests efficient alternate structures.

New Solutions to an Age-Old Problem: Innovative Strategies for Managing Pension and Longevity Risk

The recent wave of innovation in the pension and longevity risk transfer market is barely a decade old, but more than U.S. $470 billion in global transaction activity has taken place, mainly in the United Kingdom, the United States, Canada, and the Netherlands. The main deals have been buy-outs, buy-ins, and longevity swaps for pension schemes. Similar derisking solutions have spread to the market for insured annuities. But transactions must be simplified, standardized, and made available to all pension schemes, regardless of size. They must also cover younger deferred scheme participants, as well as those in collective schemes where intergenerational risks are important. New investors must be brought in, and one way of doing this is via sidecars. Capital relief is important in reducing the costs of insurance-based solutions, such as those involving tail-risk protection; regulators need to become more comfortable with such deals.

Changes of Relation in Multi-Population Mortality Dependence: An Application of Threshold VECM

Standardized longevity risk transfers often involve modeling mortality rates of multiple populations. Some researchers have found that mortality indexes of selected countries are cointegrated, meaning that a linear relationship exists between the indexes. Vector error correction model (VECM) was used to incorporate this relation, thereby forcing the mortality rates of multiple populations to revert to a long-run equilibrium. However, the long-run equilibrium may change over time. It is crucial to incorporate these changes such that mortality dependence is adequately modeled. In this paper, we develop a framework to examine the presence of equilibrium changes and to incorporate these changes into the mortality model. In particular, we focus on equilibrium changes caused by threshold effect, the phenomenon that mortality indexes alternate between different VECMs depending on the value of a threshold variable. Our framework comprises two steps. In the first step, a statistical test is performed to examine the presence of threshold effect in the VECM for multiple mortality indexes. In the second step, threshold vector error correction model (TVECM) is fitted to the mortality indexes and model adequacy is evaluated. We illustrate this framework with the mortality data of England and Wales (EW) and Canadian populations. We further apply the TVECM to forecast future mortalities and price an illustrative longevity bond with multivariate Wang transform. Our numerical results show that TVECM predicted much faster mortality improvement for EW and Canada than single-regime VECM and thus the incorporation of threshold effect significant increases longevity bond price.

Still living with mortality: the longevity risk transfer market after one decade

Abstract This paper updates Living with Mortality published in 2006. It describes how the longevity risk transfer market has developed over the intervening period, and, in particular, how insurance-based solutions – buy-outs, buy-ins and longevity insurance – have triumphed over capital markets solutions that were expected to dominate at the time. Some capital markets solutions – longevity-spread bonds, longevity swaps, q-forwards and tail-risk protection – have come to market, but the volume of business has been disappointingly low. The reason for this is that when market participants compare the index-based solutions of the capital markets with the customised solutions of insurance companies in terms of basis risk, credit risk, regulatory capital, collateral and liquidity, the former perform on balance less favourably despite a lower potential cost. We discuss the importance of stochastic mortality models for forecasting future longevity and examine some applications of these models, e.g. determining the longevity risk premium and estimating regulatory capital relief. The longevity risk transfer market is now beginning to recognise that there is insufficient capacity in the insurance and reinsurance industries to deal fully with demand and new solutions for attracting capital markets investors are now being examined – such as longevity-linked securities and reinsurance sidecars.

Still living with mortality: the longevity risk transfer market after one decade

This abstract relates to the following paper: Blake D. , Cairns A. J. G. , Dowd K. and Kessler A. R. Still living with mortality: the longevity risk transfer market after one decade.British Actuarial Journal, 23. doi: 10.1017/S1357321718000314.

Still Living with Mortality: The Longevity Risk Transfer Market After One Decade

This paper updates Living with Mortality published in 2006. It describes how the longevity risk transfer market has developed over the intervening period, and, in particular, how insurance-based solutions – buy-outs, buy-ins and longevity insurance – have triumphed over capital markets solutions that were expected to dominate at the time. Some capital markets solutions – longevity-spread bonds, longevity swaps, q-forwards, and tail-risk protection – have come to market, but the volume of business has been disappointingly low. The reason for this is that when market participants compare the index-based solutions of the capital markets with the customized solutions of insurance companies in terms of basis risk, credit risk, regulatory capital, collateral, and liquidity, the former perform on balance less favourably despite a lower potential cost. We discuss the importance of stochastic mortality models for forecasting future longevity and examine some applications of these models, e.g., determining the longevity risk premium and estimating regulatory capital relief. The longevity risk transfer market is now beginning to recognize that there is insufficient capacity in the insurance and reinsurance industries to deal fully with demand and new solutions for attracting capital markets investors are now being examined – such as longevity-linked securities and reinsurance sidecars.

Still Living with Mortality: The Longevity Risk Transfer Market after One Decade

Still Living with Mortality: The Longevity Risk Transfer Market after One Decade

Still Living With Mortality: The Longevity Risk Transfer Market After One Decade

Still Living With Mortality: The Longevity Risk Transfer Market After One Decade

Optimal Longevity Risk Transfer and Investment Strategies

Given the rising cost of maintaining defined benefit (DB) pensions, there has been a surge of activities in recent years by DB plan sponsors to transfer their pension risk through strategies such as buy-ins and buy-outs. As buy-in and buy-out transaction pipelines grow, insurers actively participating in the buy-in and buy-out markets are exposed to significant longevity risk embedded in pension schemes. In this paper, we investigate how to maximize a bulk annuity insurer’s value with reinsurance and/or longevity securities, subject to constraints that control longevity and investment risks as well as an overall risk. We apply duality and the martingale approach to derive an optimal longevity risk transfer strategy. Our results show that longevity risk transfer interacts with an insurer’s investment decision for value maximization. Our analysis also highlights the interdependence of different longevity risk management tools to achieve an overall risk target.