Part 1: The impact of automatic enrollment - J.P. Morgan Asset Management

Part 1: The impact of automatic enrollment

Contributors Anne Lester, Daniel Oldroyd
Ready! Fire! Aim? 2018

Our ongoing study of how real-life participant saving patterns interact with target date design continues to show that suboptimal participant behaviors and the consequent increase in cash flow volatility remain much more prevalent than many plan sponsors might expect. In a series of four articles, we discuss our findings and the steps plan sponsors can take to place participants on a path to a more secure retirement.

View the Ready Fire Aim overview >  

The good news: Automatic enrollment continues to expand engagement

This year’s research continued to highlight that effective plan design can have a powerful impact on participant behaviors. Nowhere is this clearer than with automatic enrollment programs.

Past Ready! Fire! Aim? findings have consistently shown that contribution rates, on average, started too low for younger participants and increased much too slowly throughout their working careers to ensure adequate retirement funding—and these trends have gotten steadily worse over the years. With this current update, we were able to take a deeper dive into contribution patterns to evaluate how behaviors differed among three participant segments:

  1. passive participants, who were automatically enrolled in their plans and never made contribution changes beyond their initial default rates
  2. subsequent shifters, who were automatically enrolled but had a later rate change (either through automatic contribution escalation or by making a change on their own)
  3. active engagers, who both enrolled in their plans and set their contribution rates on their own

Approximately 62% of the plans in our study, which covered roughly 80% of the participants, utilized automatic enrollment as a way to increase participant engagement.1 Given this broad adoption, it was unsurprising to see that more than 51% of 25-year-old participants investing in a plan were initially enrolled through an automatic enrollment default, potentially engaging participants who might not have invested in the plan otherwise. This percentage drifted lower to 36% for 45-year-old participants and to 27% for 65-year-old participants, since the bulk of many companies’ new hires (i.e., the employees most likely to have been automatically enrolled) tend to be in their earlier working years.

This large percentage of younger defaulted participants suggests that plan sponsors can have an extremely positive influence by setting employees on a constructive retirement savings path while also getting them to start investing for retirement early in their careers. These participants are also typically automatically invested in qualified default investment alternatives (QDIAs), usually professionally managed target date funds, which research has shown often deliver stronger investment results for the average investor than if that investor had selected his or her own asset allocation.

The bad news: Automatic enrollment is also weighing on lower contribution rate trends

Unfortunately, the average contribution rate for passive participants fell significantly below those of subsequent shifters and active engagers. On average, contribution rates for:

  • passive participants started at a 3.3% average contribution rate at age 25 and stayed at that level across all working years
  • subsequent shifters started at a 5.7% average contribution rate at age 25 and increased slowly, reaching 6.9% at age 45 and 8.2% at age 65
  • active engagers started at a 5.5% average contribution rate and increased even more slowly, reaching 6.3% of salary at age 45 and 7.7% at age 65

This means that a sizable segment of participants is starting average contributions at a minimal 3.3% rate and failing to take any action other than what the plan sponsor makes on their behalf in terms of subsequent increases. Moreover, these contributions are anchored at a level notably below the savings rate of at least 10% recommended by many industry experts.

On the plus side, subsequent shifters changed their contribution rates, on average, at the highest percentage amounts across all three groups, a trend that continued as the segment grew older. There also seemed to be a strong correlation between participant salary increases and positive contribution rate changes, particularly in the earlier career years.

Key finding: Automatic enrollment weighing on contribution rates

Source: J.P. Morgan retirement research, 2015–17.

Digging deeper into these averages reveals a wide range of contribution behaviors. Disappointedly, even at the higher end of the spectrum many participants are simply contributing far too little. This also illustrates how retirement planning averages alone may be misleading. (Please see our related research No one is average.) The median numbers below show the midpoint in each segment where 50% of participants are contributing more and 50% are contributing less. There can be extremes on both sides. The strongest retirement plans need to be built to address this broad array of potential behaviors to help ensure as many participants as possible are best positioned for retirement funding success.

Key finding: The least engaged participants contribute less
Contribution enrollment Lower end Median Higher end
Passive participants 3.3% 3.3% 3.4%
Subsequent shifters 5.7% 6.9% 8.2%
Active engagers 5.5% 6.3% 7.7%

Note: All contribution rates are representative of contribution rates made by individuals age 25-65. The lower end represents the bottom contributions across ages, while the higher end represents the top contribution rates across ages.
Source: J.P. Morgan retirement research, 2015–17.


We again found that a large number of participants were taking sizable account loans. On average:

  • 14% of passive participants borrowed 22% of their account balances
  • 19% of subsequent shifters borrowed 18% of their account balances
  • 21% of active engagers borrowed 18% of their account balances

It makes intuitive sense that the more engaged participants were more likely to tap into their plans for cash needs. However, across all three segments a sizable portion of assets were not invested in any given year. Our earlier papers presented how this cash flow volatility may negatively interact with market volatility.


Pre- and post-retirement withdrawal trends were fairly consistent across all three segments. A range of 7% to 12% of participants over the age of 59½ withdrew, on average, 55% of assets. The majority of participants, regardless of how they enrolled in the plan, left the plan within three years of retirement. More insights into these withdrawal patterns can be found in the third section of this year’s research, Withdrawal trends .

Implications for plan sponsors

The main takeaway from these numbers is that getting employees into the plan is a good first step. However, plans interested in positioning as many participants as possible for retirement funding success also need to lobby more aggressively for higher contribution rates, either passively through targeted communications or more explicitly by broadly implementing automatic contribution escalation programs at much higher rate increase levels than typically used today. Ultimately, the only way to be certain of safe retirement funding is to save enough. Our 2018 DC Plan Participant Survey Findings showed that participants tend to appreciate these efforts as well, indicating high satisfaction rates with automatic enrollment and automatic contribution escalation programs, and that 80% of participants with both features expect their savings to last throughout their lifetime vs. 47% of those who were only automatically enrolled.2

Further, cash flow volatility remains higher and more prevalent than many general industry expectations. This can significantly shape the most suitable target date design in two critical ways. First, plan sponsors and their advisors/consultants should carefully weigh appropriate levels of overall market exposures across the glide path. Second, they should prudently assess potential drawdown risk at the times when participants are most apt to withdraw assets, typically when entering retirement or soon after.

1 Stats may vary depending on plan size, population base, calculation method, etc.

2 J.P. Morgan Plan Participant Research 2018.

Part 2: The salary effect
Part 2 of our Ready! Fire! Aim? research series examines participant behavior by salary level.
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