Longevity Risk in Life Insurance

2017 ◽  
pp. 87-104
Author(s):  
Elif Ceylan ◽  
Seher A. Tezergil
Keyword(s):  
Life Insurance ◽  
Longevity Risk

scholarly journals Measurement of Longevity Risk of Life Annuity Based on C-ROSS Framework

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Ming Zhao ◽  
Ziwen Li ◽  
Yinge Cai ◽  
Weiting Li
Keyword(s):  
Mortality Rate ◽  
Life Table ◽  
Life Insurance ◽  
Insurance Companies ◽  
Longevity Risk ◽  
Risk Capital ◽  
Risk Margin ◽  
Life Annuity ◽  
Mortality Improvement ◽  
Carter Model

This paper constructs a model to measure longevity risk and explains the reasons for restricting the supply of annuity products in life insurance companies. According to the Lee–Carter Model and the VaR-based stochastic simulation, it can be found that the risk margin of the first type of longevity risk for ignoring the improvement of mortality rate is about 7%, and the risk margin of the second type of longevity risk for underestimating mortality improvement is about 7%. Therefore, the insurer needs to use cohort life table pricing premium and gradually prepares longevity risk capital during the insurance period.

An Optimal Product Mix for Hedging Longevity Risk in Life Insurance Companies: The Immunization Theory Approach

2009 ◽  
Vol 77 (2) ◽  
pp. 473-497 ◽  
Author(s):  
Jennifer L. Wang ◽  
H.C. Huang ◽  
Sharon S. Yang ◽  
Jeffrey T. Tsai
Keyword(s):  
Life Insurance ◽  
Insurance Companies ◽  
Longevity Risk ◽  
Theory Approach ◽  
Product Mix

scholarly journals On the Market-Consistent Valuation of Participating Life Insurance Heterogeneous Contracts under Longevity Risk

Risks ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 20
Author(s):  
Anna Rita Bacinello ◽  
An Chen ◽  
Thorsten Sehner ◽  
Pietro Millossovich
Keyword(s):  
Interest Rate ◽  
Life Insurance ◽  
Financial Risk ◽  
Numerical Analyses ◽  
Longevity Risk ◽  
Participation Rates ◽  
Expected Return ◽  
Market Consistent Valuation ◽  
Valuation Of Life

The purpose of this paper is to conduct a market-consistent valuation of life insurance participating liabilities sold to a population of partially heterogeneous customers under the joint impact of biometric and financial risk. In particular, the heterogeneity between groups of policyholders stems from their offered minimum interest rate guarantees and contract maturities. We analyse the effects of these features on the company’s insolvency while embracing the insurer’s goal to achieve the same expected return for different cohorts of policyholders. Within our extensive numerical analyses, we determine the fair participation rates and other key figures, and discuss the implications for the stakeholders, taking account of various degrees of conservativeness of the insurer when pricing the contracts.

Longevity swaps for longevity risk management in life insurance products

2020 ◽  
Vol 21 (3) ◽  
pp. 253-269 ◽  
Author(s):  
Canicio Dzingirai ◽  
Nixon S. Chekenya
Keyword(s):  
South Africa ◽  
South African ◽  
Life Insurance ◽  
Regime Switching ◽  
Longevity Risk ◽  
The South ◽  
Conditional Heteroscedasticity ◽  
Content Type ◽  
Vector Autoregressive ◽  
Long Run

Purpose The life insurance industry has been exposed to high levels of longevity risk born from the mismatch between realized mortality trends and anticipated forecast. Annuity providers are exposed to extended periods of annuity payments. There are no immediate instruments in the market to counter the risk directly. This paper aims to develop appropriate instruments for hedging longevity risk and providing an insight on how existing products can be tailor-made to effectively immunize portfolios consisting of life insurance using a cointegration vector error correction model with regime-switching (RS-VECM), which enables both short-term fluctuations, through the autoregressive structure [AR(1)] and long-run equilibria using a cointegration relationship. The authors also develop synthetic products that can be used to effectively hedge longevity risk faced by life insurance and annuity providers who actively hold portfolios of life insurance products. Models are derived using South African data. The authors also derive closed-form expressions for hedge ratios associated with synthetic products written on life insurance contracts as this will provide a natural way of immunizing the associated portfolios. The authors further show how to address the current liquidity challenges in the longevity market by devising longevity swaps and develop pricing and hedging algorithms for longevity-linked securities. The use of a cointergrating relationship improves the model fitting process, as all the VECMs and RS-VECMs yield greater criteria values than their vector autoregressive model (VAR) and regime-switching vector autoregressive model (RS-VAR) counterpart’s, even though there are accruing parameters involved. Design/methodology/approach The market model adopted from Ngai and Sherris (2011) is a cointegration RS-VECM for this enables both short-term fluctuations, through the AR(1) and long-run equilibria using a cointegration relationship (Johansen, 1988, 1995a, 1995b), with a heteroskedasticity through the use of regime-switching. The RS-VECM is seen to have the best fit for Australian data under various model selection criteria by Sherris and Zhang (2009). Harris (1997) (Sajjad et al., 2008) also fits a regime-switching VAR model using Australian (UK and US) data to four key macroeconomic variables (market stock indices), showing that regime-switching is a significant improvement over autoregressive conditional heteroscedasticity (ARCH) and generalised autoregressive conditional heteroscedasticity (GARCH) processes in the account for volatility, evidence similar to that of Sherris and Zhang (2009) in the case of Exponential Regressive Conditional Heteroscedasticity (ERCH). Ngai and Sherris (2011) and Sherris and Zhang (2009) also fit a VAR model to Australian data with simultaneous regime-switching across many economic and financial series. Findings The authors develop a longevity swap using nighttime data instead of usual income measures as it yields statistically accurate results. The authors also develop longevity derivatives and annuities including variable annuities with guaranteed lifetime withdrawal benefit (GLWB) and inflation-indexed annuities. Improved market and mortality models are developed and estimated using South African data to model the underlying risks. Macroeconomic variables dependence is modeled using a cointegrating VECM as used in Ngai and Sherris (2011), which enables both short-run dependence and long-run equilibrium. Longevity swaps provide protection against longevity risk and benefit the most from hedging longevity risk. Longevity bonds are also effective as a hedging instrument in life annuities. The cost of hedging, as reflected in the price of longevity risk, has a statistically significant effect on the effectiveness of hedging options. Research limitations/implications This study relied on secondary data partly reported by independent institutions and the government, which may be biased because of smoothening, interpolation or extrapolation processes. Practical implications An examination of South Africa’s mortality based on industry experience in comparison to population mortality would demand confirmation of the analysis in this paper based on Belgian data as well as other less developed economies. This study shows that to provide inflation-indexed life annuities, there is a need for an active market for hedging inflation in South Africa. This would demand the South African Government through the help of Actuarial Society of South Africa (ASSA) to issue inflation-indexed securities which will help annuities and insurance providers immunize their portfolios from longevity risk. Social implications In South Africa, there is an infant market for inflation hedging and no market for longevity swaps. The effect of not being able to hedge inflation is guaranteed, and longevity swaps in annuity products is revealed to be useful and significant, particularly using developing or emerging economies as a laboratory. This study has shown that government issuance or allowing issuance, of longevity swaps, can enable insurers to manage longevity risk. If the South African Government, through ASSA, is to develop a projected mortality reference index for South Africa, this would allow the development of mortality-linked securities and longevity swaps which ultimately maximize the social welfare of life assurance policy holders. Originality/value The paper proposes longevity swaps and static hedging because they are simple, less costly and practical with feasible applications to the South African market, an economy of over 50 million people. As the market for MLS develops further, dynamic hedging should become possible.

The pricing of hedging longevity risk with the help of annuity securitizations

2014 ◽  
Vol 15 (4) ◽  
pp. 385-416 ◽  
Author(s):  
Jonas Lorson ◽  
Joël Wagner
Keyword(s):  
Life Insurance ◽  
Longevity Risk ◽  
Insurance Company ◽  
Pricing Model ◽  
German Market ◽  
Content Type ◽  
Life Insurer ◽  
Market Situation ◽  
Specific Country ◽  
Theoretical Side

Purpose – The purpose of this paper is to develop a model to hedge annuity portfolios against increases in life expectancy. Across the globe, and in the industrial nations in particular, people have seen an unprecedented increase in their life expectancy over the past decades. The benefits of this apply to the individual, but the dangers apply to annuity providers. Insurance companies often possess no effective tools to address the longevity risk inherent in their annuity portfolio. Securitization can serve as a substitute for classic reinsurance, as it also transfers risk to third parties. Design/methodology/approach – This paper extends on methods insurer's can use to hedge their annuity portfolio against longevity risk with the help of annuity securitization. Future mortality rates with the Lee-Carter-model and use the Wang-transformation to incorporate insurance risk are forecasted. Based on the percentile tranching method, where individual tranches are aligned to Standard & Poor's ratings, we price an inverse survivor bond. This bond offers fix coupon payments to investors, while the principal payments are at risk and depend on the survival rate within the underlying portfolio. Findings – The contribution to the academic literature is threefold. On the theoretical side, building on the work of Kim and Choi (2011), we adapt their pricing model to the current market situation. Putting the principal at risk instead of the coupon payments, the insurer is supplied with sufficient capital to cover additional costs due to longevity. On the empirical side, the method for the German market is specified. Inserting specific country data into the model, price sensitivities of the presented securitization model are analyzed. Finally, in a case study, the procedure to the annuity portfolio of a large German life insurer is applied and the price of hedging longevity risk is calculated. Practical implications – To illustrate the implication of this bond structure, several sensitivity tests were conducted before applying the pricing model to the retail sample annuity portfolio from a leading German life insurer. The securitization structure was applied to calculate the securitization prices for a sample portfolio from a large life insurance company. Social implications – The findings contribute to the current discussion about how insurers can face longevity risk within their annuity portfolios. The fact that the rating structure has such a severe impact on the overall hedging costs for the insurer implies that companies that are willing to undergo an annuity securitization should consider their deal structure very carefully. In addition, we have pointed out that in imperfect markets, the retention of the equity tranche by the originator might be advantageous. Nevertheless, one has to bear in mind that by this behavior, the insurer is able to reduce the overall default risk in his balance sheet by securitizing a life insurance portfolio; however, the fraction of first loss pieces from defaults increases more than proportionally. The insurer has to take care to not be left with large, unwanted remaining risk positions in his books. Originality/value – In this paper, we extend on methods insurer's can use to hedge their annuity portfolio against longevity risk with the help of annuity securitization. To do so, we take the perspective of the issuing insurance company and calculate the costs of hedging in a four-step process. On the theoretical side, building on the work of Kim and Choi (2011), we adapt their pricing model to the current market situation. On the empirical side, we specify the method for the German market. Inserting specific country data into the model, price sensitivities of the presented securitization model are analyzed.

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