Retirement Savings Models Simplify a Complex Picture

Consider this: A young woman enters the workforce at age 25 and is automatically enrolled in a defined contribution (DC) plan at 3% of pay. The plan automatically escalates her deferral by 1% until the woman is deferring 10% of pay annually. When you add to this a safe harbor match and give the participant 7% per year returns, she theoretically retires by age 60 a wealthy woman.

Sounds great, right? However, as John Lowell, partner and retirement actuary with October Three, who is based in Atlanta, notes, this is rarely reality. What if the woman gets married and has children and stops work to take care of the children? Or, what if the woman has a period of time where paying for child care costs, a mortgage or health care urges her to reduce her deferrals or to take a loan from her DC plan? What if she involuntarily loses her job? In addition, Lowell says DC plan participants should understand that 7% per year returns is not a reality.

This is the problem with retirement savings models, says Drew Carrington, head of Franklin Templeton Investments’ U.S. large market institutional defined contribution (DC) business, who is based in San Mateo, California. “It is also partly a more generalized problem in the [retirement] industry to oversimplify the retirement challenge,” he tells PLANSPONSOR.

Almost all of these assumptions are wrong, he says. People change jobs every five or so years; many new hires will not be fresh out of college and have probably saved somewhere else. Models simplify decisions about retirement, including when a person will retire and when they will claim Social Security. “These are usually household decisions, but models are for individuals,” he notes.

Lowell adds that every time you throw market volatility in the mix, even if it has a mathematical average equal to the assumption, it will bring the outcome down. As a simple example, Lowell says, if the woman in the example has a zero return in year one, then a 14% return in year two, the cumulative return is not 7% compounded, it’s less.

Lowell points out that when actuaries do forecasting for defined benefit (DB) plans, they do not look at one set of assumptions; they model multiple scenarios. If the DB plan sponsor is risk-averse, it would look at the poorer outcomes and hedge against them.

Lowell says the same can be done with DC planning models. “The model I would like to see is one in which people are able to input their own individual best estimate of what they think they will do, and the model will perform various scenarios,” he says.

“I’m suggesting a model that doesn’t just show a scenario based on a participant’s input and say ‘Yeah you’re good,’ or ‘No you’re not,’ but one that starts with reasonable expectations, and shows a participant all realistic outcomes,” Lowell adds. “The model will tell a participant what percentage of time they will be in good shape and how often they won’t, as well as what they can do to minimize the percentage of times they are not in good shape, such as change asset allocations. It is OK for a model to use questions like, ‘Do you anticipate work stoppages or periods of time where you will have to stop or lower deferrals?’”

Lowell concedes this is not an easy model to build, but it is “doable.” He says, “If it can be done for DB plans, it can be done for DC plans.”

Until such a model exists, Carrington says it is a great challenge in the industry to help people piece together the complex retirement puzzle. “We have to start talking to participants about the challenge,” he says. “Rather than simply discussing only their DC assets, or only their resources and not their household’s, we need to discuss the more complex picture. This takes a combination of models, advice and communication to make participants aware of the reality.”

Carrington adds that financial wellness is important as well, because it helps people look at budgeting at the household level and issues such as addressing debt. It helps participants address challenges when their savings behaviors do not fit a model’s assumptions.

Lowell says if a DC plan sponsor adopts a model for participants to use, it should roll out an educational program to help participants use the model in a way that is prudent and informed. Plan sponsors should explain the parameters of the model and what participants might think about when running those parameters. “Obviously plan sponsors have to limit how much to say to participants, but they can say participants may consider work stoppages they may have for personal reasons or changes in lifestyle that may cause them to change deferrals,” he says.

Carrington suggests other things plan sponsors can do to better position participants for success. They can target new hires—especially mid- and late-career hires—with communication that invites them to save at a rate similar to what they did at their prior job, not just at the new employer’s auto deferral percent. “They know they can save at a higher level because they did at their previous job,” he says.

Plan sponsors can also change their plans to accommodate regular withdrawals, not just lump-sums.

They can also choose models that help with Social Security claiming decisions, Carrington suggests, and provide education or access to advice that will help them fund retirement if they retire at age 65 but claim Social Security later.

Carrington believes the retirement readiness picture is more positive than what the data shows or what gets reported. “We look at general things, like average DC plan balance, and that’s very distorted. We don’t take into consideration things like savings from a participant’s whole job tenure or their household situation. Certainly there are things we can do to improve participants’ retirement readiness, but we don’t have to start from scratch. Incremental improvements will enhance retirement for many participants,” he concludes.