A stitch in time
Predicting life expectancy is never easy. In addition to the more obvious factors that need to be considered, Swiss Re’s Daniel Ryan points out some less obvious but potentially beneficial ones
Ask almost any actuary and they will tell you how old Jeanne Calment was when she died. The Frenchwoman lived to a record 122 years and 164 days, dying in 1997 - a record that, surprisingly, still stands.
In recent years life expectancy has been rising faster than expected in many developed countries, and this has had a direct impact on the future liabilities. And longer lives means longer retirements, which have to be funded.
So what factors should be considered when assessing a pension fund’s longevity risk?
Aside from the more obvious influences, such as gender, health, wealth and smoking history, one factor that is often overlooked is month of birth. It may be a surprise that the month in which a person is born actually provides valuable information on how long they are expected to live - and date of birth is readily available information.
To illustrate this, Swiss Re recently investigated 220,000 insured individuals from Germany who died between 2004 and 2008 to establish the strength of the association between month of birth and age at death. The information was collected from a number of German insurers, and this Swiss Re database has been used widely for benchmarking and detailed analysis of mortality experience.
The graph demonstrates how people born in the autumn and winter months tend to live longer than those born in the spring and the summer months. Those born between April and June have the lowest life expectancy and the greatest difference - between someone born in June and someone born in September - is just over one-and-a-half years. To put this into perspective, the current difference in life expectancy between a German man and a German woman is about five years, so month of birth is not an unimportant factor.
Similar population studies in different countries have supported our findings. For example, in the southern hemisphere, where seasons are reversed, those born in the autumn and winter also have longer life expectancy. Furthermore, life expectancy of people emigrating between hemispheres appears to reflect the prevailing seasons in their country of origin rather than their new home - this is a risk factor that reflects where and when you were born.
What reasons are behind this phenomenon? Children born in the spring and summer in the mid twentieth century tended to weigh significantly less than those born in winter and autumn. Low birth weights have been associated with increased susceptibility to disease in later life and deeper analysis indicates higher rates of mortality from heart disease, stroke and stomach cancer for those born in spring.
Refrigeration and international transport of food have dramatically improved the potential quality of people’s diet, along with better availability of fruit and vegetables. Studies have suggested narrowing differences in life expectancy by month of birth for those born more recently. But clear differences remain and month of birth will continue to be an important factor in life expectancy.
Better health data is very important in understanding life expectancy and the subsequent management of a pension fund’s finances. Analysis of historical trends of death provides a limited insight into the future, but it is only through a strong comprehension of what is coming next that we can start to generate predictions closer to reality.
To what extent will vaccines under development, or disease treatments soon to finish their clinical trials, reduce future mortality rates? On the negative side, will the global rise in obesity and diabetes, or a future influenza pandemic, limit further improvements in life expectancy?
Access to better sources of individual medical data needs to be coupled with an enhanced understanding and interpretation of this data.
Pension funds could benefit to an extent from an improved understanding of future longevity risk through better access to research and data on their members. However, this would involve considerable resources and even large schemes could not be confident of protecting themselves against significant changes. The uncertainty over future possibilities means that many have decided to remove any unexpected liabilities from their balance sheet.
The de-risking trend
Recently, there has been a shift from defined benefit (DB) to defined contribution schemes, which passes the risk for pension income from the employer to the individual - although this has not been the case for all funds and DB are still a key attraction for employees. Even where DB schemes have closed to existing members, accrued benefits remain.
Many funds have turned to the insurance industry - via products such as bulk annuities and longevity insurance - to take on this risk. Bulk annuities are now well-established, but perhaps less well known is longevity insurance.
In many ways, longevity insurance is a carbon copy of a bulk annuity in that, in return for a pre-agreed premium, all future pensions will be paid until the last member dies. But one key difference is the fact that premiums are spread over time, rather than a single, up-front payment. This leaves control of asset risk - and the associated opportunity - with the pension fund.
The vast majority of recent transactions referred to as longevity swaps have followed the longevity insurance format. The risk has mainly ended up on the books of reinsurers - who provide additional capacity to everyday insurers - even when a banking group has been involved. This is because reinsurers are often seen as the ‘natural home’ for longevity risk.
Reinsurers are actively seeking exposure to longevity for a number of reasons. First, longevity is typically uncorrelated to the other business they underwrite, such as hurricanes or motor risks. Second, reinsurers are generally the largest holders of mortality risk through wholesale life insurance protection provided to household-name insurers. Mortality risk, the risk that people die earlier than expected, is the opposite peril to longevity and can be used to offset any significant changes in life expectancy. Furthermore, economies of scale are achieved through providing longevity reinsurance products, covering vast numbers of people, in many countries.
To date, longevity transactions have mainly taken place in the UK. However, similar transactions are expected to develop in other countries, such as in the Netherlands and Switzerland, where there are significant pension assets and an increasing awareness of the financial risk associated with improvements in longevity.
Pension funds have two stark choices. They can retain their longevity risk and fund it themselves - this involves attempting to improve the data collected on members and their understanding of potential improvements in life expectancy. Or they can seek ways to permanently remove this risk and pass it to organisations with access to more economies of scale and diversification.
In either case it is vital that the stakeholders - pension funds, the insurance industry, governments and research organisations - work together to design better models to understand future life expectancy.
Knowledge of influences such as month of birth is key to this process, but there are many influences that are as yet unknown. Predicting the future will never be an exact science. For example, it is estimated that people born in February will have a relatively low life expectancy and yet Jeanne Calment was born on 21 February 1875.
Daniel Ryan is head of research and development at Swiss Re