Life and annuity reinsurers are wrestling with the possibility that technological advances could help large numbers of U.S. residents live to 120.
But actuaries and other longevity experts say they are already seeing another interesting change: groups of people who once died young now seem to be catching up with the groups who were already living to a ripe old age.
U.S. mortality rates “are not improving evenly,” says Robert Friedland, founding director of the Center On An Aging Society at Georgetown University in Washington.
Technology may be increasing the maximum possible life span for a few 90-year-old women to 110, but the fact that more young men can expect to live into their 90s is probably more important for society, Friedland says.
“Is life span changing, or just life expectancy?” Friedland asks. “My view is that life span has not increased at all.”
Market researchers have made an art of slicing and dicing the U.S. population into easy-to-understand demographic groups, such as “Volvo-owning term life buyers.”
Actuaries are more comfortable with variables taken from more traditional information sources.
Stacy Gill, a vice president at the MIB Group Inc., Westwood, Mass., a life insurance industry data collection and analysis consortium, says life insurers typically look at four major variables when assessing mortality rates, or the risk that a member of a particular group might die in a particular period of time: sex, smoking, age and life insurance policy characteristics, such as the number of years a policy has been in effect.
Some researchers have tried looking at more offbeat variables, such as the correlation between pet ownership and mortality among the elderly, but finding reliable, published data even on meat-and-potatoes variables such as the insureds occupation or state of residence can be difficult, Gill says.
“There arent standard industry statistics for geographical differences,” Gill says.
When life insurers, life reinsurers and actuarial firms do use life claims databases to break down mortality rates in unusual ways, they may be more likely to use the results to gauge whether applicants are insurable than to try to use the results to set rates, experts report.
One popular method of dividing the population is to compare the insured with the uninsured population, and policyholders who own large amounts of coverage with those owning small amounts.
“The insured population does not have the same characteristics” as the general population, says Rick Bergstrom, a consulting actuary in the Seattle office of Milliman USA.