Retirement Industry Eyes QDIA Personalization–With Caution[i]
On June 3, 2026, PlanSponsor published an article summarizing the “QDIA Evolution” session at the 2026 PLANSPONSOR National Conference in Nashville, Tennessee. Panelists Brian Miller (Vanguard), John Doyle (Capital Group), and Phil Senderowitz (Strategic Retirement Partners) agreed that the future of default investing will likely be more personalized. The speakers cautioned plan sponsors to resist change for its own sake and to remain focused on the participant outcomes they want their plans to achieve.
According to the panel, simplicity remains one of the strongest arguments for TDFs, which are estimated to comprise between 40%-50% of defined contribution assets in America. Over time, there will be a lot more personalization as technology makes it more practical and affordable. The TDF future will likely incorporate private assets, guaranteed lifetime income, and even AI tools. This will likely be an evolutionary and refinement process.
Although the panelists agreed that personalization is the future, they repeatedly emphasized that personalization is not automatically superior. According to Doyle, “[t]he right personalization is probably going to be better. But how much data are you using, where are you getting that data, and what aren’t you getting that you might be missing?”
Before we begin our discussion, we should define “personalization” and when the trend began.
(1) Personalization is the practice of using data to tailor products, services, messages, and experiences specifically to each person. Instead of a one-size-fits-all approach, it adapts to individual needs, making the experience more relevant, familiar, intuitive, and targeted.
(2) Modern personalization began in the early 1990s as a strategic shift in relationship marketing and exploded with the birth of the World Wide Web. It transformed into data-driven, one-to-one consumer experiences powered by the Internet. Today, personalization has evolved into hyper-personalization. Companies use generative AI and real-time contextual data to curate entirely unique, one-to-one experiences.
Even after 30 years of progressively more sophisticated personalization that infiltrated the entire consumer ecosystem, the retirement plan industry has shown very little personalization advancement. In December 2001, the Department of Labor (DOL) issued Advisory Opinion 2001-09A[ii] to SunAmerica, which clarified the legality of offering customized participant portfolios to employer-sponsored defined contribution plans (DC Plans). Twenty-five years later, the Managed Account remains the go-to personalized investment solution.
Managed Account
A Managed Account is a personalized, professional investment service (“MA Service”) offered under a DC Plan. It is an automated computer model that continuously manages and adjusts a participant’s portfolio based on the participant’s specific age, salary, account value, deferral contributions, and employer contributions (the “Default Data Set”). If and when a participant engages with the MA Service through a service portal, additional personal information can enrich the Default Data Set. That voluntarily provided data can include outside qualified and non-qualified assets, additional sources of income, expected retirement location, expected retirement age, defined benefit income at retirement, a risk tolerance questionnaire, and overall financial goals (the “Additional Data Set”). Bear in mind that, to have the Additional Data Set at all, an enrolled participant must engage the MA Service. Therefore, as life, and thus the Additional Data Set changes, it is incumbent on the participant to update the data to keep it current.
As reported in the February 2026 NAPA online magazine[iii], citing T. Rowe Price’s 2026 Reference Point annual 401(k) benchmarking report, only 13.8% of participants currently use “financial advice, education, or tools available through their workplace retirement site.” The 2025 NEPC DC Plan Trends & Fees Survey shows that 48% of plans offer a managed account option, with only a 10% utilization rate, representing 9% of plan assets invested. The adoption level has been insignificant. According to Kiplinger’s Magazine[iv], retirement savers pay annual fees of between 40bp and 60bp of the account balance, on average, for a managed account service, on top of the underlying fund expenses, which can quickly bring the all-in cost to 100bp or more. A number of class action lawsuits[v] have been filed making the case that using MA Services as a QDIA is imprudent, since most participants are inactive (i.e., unengaged) and never receive the full value of the personalization for which they are paying.
As the industry pioneer and creator of the first personalized target date solution (PTD), the Individualized Glide Path Solution (iGPS), I challenge two of the panel’s conclusions.
1) Stay the Course (Defaulting to the Present) and Personalization Is the Future
To advise “stay the course” is to advise sticking with the single-factor TDF, pioneered by Wells Fargo Investment Advisors in 1994. The “position of stasis”[vi] feels safe and is well understood. Incumbent inertia and a “change is the enemy of the good” mentality have kept innovation away from the single-factor TDF for three decades — even as it grew to over $5 trillion and more than 40% of total plan assets[vii]. The first commercially available smartphone, the IBM Simon Personal Communicator, reached the market that same year, 1994. In 2026, Apple will introduce its 18th iteration, the iPhone 18. The TDF has not had its second version. And the “single factor” is barely a factor. A TDF series is built from 10 to 12 five-year vintages, so a 41-year-old and a 45-year-old are dropped into the identical glidepath. That is not personalization on age; it is coarse age-bucketing.
In 2024, Nexus338 launched iGPS, the first “intelligent” TDF and the founding example of a new category – the Personalized Target Date (PTD). Critically, iGPS is not a new model. It runs the same well-known, in-market PIMCO glidepath methodology used across PIMCO’s RealPath Blend series, and all vintages are the portfolio building blocks that pair actively managed PIMCO fixed income with index-tracking Vanguard equity. Each building block carries an established track record. The only change: the five population-average assumptions that produce a standard glidepath (age, salary, account value, deferral, employer contribution) are replaced with each participant’s actual Default Data Set. The engine is proven; we simply stopped feeding it averages.
Because the overwhelming evidence is that most participants never engage with their plan investments, iGPS deliberately requires no engagement and no Additional Data Set. It personalizes from the Default Data Set the recordkeeper already holds. In that respect, a participant in iGPS is no worse off than a non-engaged participant in a managed account who never logs in and incurs dramatically lower fees.
Personalization is today. With PTD, it is the present. Stay the course is inferior.
2) Personalization Is Not Automatically Superior…Unless You Are Replacing Averages With Facts
The panel’s caution rests on a buried assumption: that personalization runs on rich-but-questionable data — Doyle’s “how much data, where from, and what are you missing?” Eliminate that assumption and the disagreement dissolves. For PTDs, the data in question is not exotic. It is the same five Default Data Set fields a TDF already implies – only true instead of averaged.
Consider the managed account, still the industry’s go-to “personalized” solution 25 years after DOL Advisory Opinion 2001-09A. Its theoretical advantage is the Additional Data Set: outside assets, spousal income, risk tolerance, retirement timing. But that advantage exists only for the participant who engages and keeps the data current. For the roughly 90% who never engage, the managed account is personalizing on exactly the Default Data Set — the same inputs iGPS uses — while charging 40bp to 60bp on top of fund expenses, 100bp or more all-in. I do not believe tomorrow’s participant will suddenly become a diligent, perpetual data-updater. The Additional Data Set’s value is real only for the exception, not the rule.
iGPS delivers the same realistic personalization for the disengaged majority at 29bp all-in — inclusive of PIMCO’s active management. That figure is less than the managed account’s service fee alone before that account has paid for a single fund. Twenty of those basis points are PIMCO’s asset management; the remaining nine cover fiduciary oversight, the personalization technology, and recordkeeping. In other words, personalization itself adds roughly 9bp over the underlying management — versus the 40bp to 60bp a managed account charges for a personalization the disengaged majority never switches on. This is not the cheapest option on the shelf, and it does not pretend to be; it is the best personalization per dollar that a real-world participant population will ever actually receive.
There may be many ways professionals build personalization. For iGPS, we construct each participant’s portfolio from their unique Default Data Set. The asset allocation — across stocks, bonds, cash, and the sub-asset classes and styles within them — is driven by how much “risk” that participant should take to build an efficient portfolio that optimizes future returns. “Risk” here is the portfolio’s beta[viii] dominated by the size of the equity allocation, and the goal is to optimize the return earned for every unit of risk the portfolio takes over time. So for iGPS, personalizing means identifying the right portfolio risk for each participant — from each participant’s own Default Data Set — with the end objective of income replacement at retirement. Moreover, the personalized portfolio is updated quarterly based on the changing Default Data Set. This process happens in the background automatically.
Now comes the part the panel’s framing left out entirely and the reason for iGPS’s name. Think of the GPS in your car/phone. You enter a destination, and it plots the most efficient route given current conditions. If you veer off, by choice or by accident, it senses the change and reroutes you back to the best path to that same destination. iGPS does exactly this with a retirement portfolio. The destination is fixed: the income replacement each participant needs at retirement. The route is the efficient allocation that gets them there, given their Default Data Set. And every quarter, iGPS checks whether any of the five factors has moved. Age advances. A raise lifts salary, which lifts the deferral, which lifts the employer match, which lifts the balance, and the amount of risk required to stay on course shifts with it. When the change is durable enough to matter, iGPS re-routes. It rebalances the portfolio automatically to reflect who the participant has become this quarter rather than who they were the day they enrolled.
A single-factor TDF cannot do this. It knows the calendar and nothing else, and it slides every participant in a five-year vintage down the identical glidepath on a fixed schedule. It is blind to the raise, the deferral change, the balance jump. It never reroutes for you because it never knew where you were. And because all of this happens inside a tax-deferred plan, the rerouting carries no tax cost — only the benefit of staying on the efficient path.
So the panel’s own question: “what are we solving for?” has a simple answer. We are solving for precisely what a single-factor TDF solves for: income replacement at retirement, through the same trusted methodology, with materially higher precision. A standard TDF is simply run on the assumption that every participant is average. iGPS runs the same model on who each participant actually is — and keeps running it, quarter after quarter. If the choice is between real data or a population average, the answer is obvious.
Personalization, done this way, is automatically superior.
Conclusion
Change is uncomfortable, and the preference for stability is deeply human. Behavioral researchers call it status quo bias – the tendency to prefer current arrangements and to justify them even when they are not optimal. A fiduciary can feel that pull as strongly as anyone, and prudence is typically the justification, at first glance, to counsel caution toward anything new. But the fiduciary standard is not a license to default to the familiar. Fiduciaries owe the twin duties of loyalty and prudence (or due care) and must act solely in the interest of plan participants. That sole-interest standard is precisely what should free a fiduciary to set personal comfort aside and judge a solution on its merits.
On the merits, the case is straightforward. The panel calls personalization the future. With a proven methodology, established building blocks, transparent all-in pricing, and a portfolio that course corrects every quarter, iGPS is already the present. The single-factor TDF asks every participant to be average and to stay on a calendar forced on them. This is forcing the same size shoe on all participants in the same 5-year vintage to wear. A superior default exists today. Rather than keep defaulting participants into a one-size-fits-all world, plan fiduciaries owe it to their participants to investigate and, if deemed prudent, implement a competitively priced (to a TDF), high-value personalized solution today…no need for stasis or waiting for the future.
ENDNOTES
[i] https://www.plansponsor.com/retirement-industry-eyes-qdia-personalization-with-caution/
[ii] https://www.dol.gov/agencies/ebsa/about-ebsa/our-activities/resource-center/advisory-opinions/2001-09a
[iii] https://www.napa-net.org/news/2026/2/advice-and-education-usage-correlates-with-higher-savings-study-finds/
[iv] June 23, 2025 issue, https://www.kiplinger.com/retirement/401ks/are-managed-401-k-accounts-worth-the-extra-cost
[v] Plaintiffs claimed that fiduciaries breached ERISA’s duty of prudence by defaulting disengaged participants into an expensive managed-account QDIA when prudent fiduciaries would not automatically enroll plan participants, who tend to be disengaged and do not provide additional personalized information to the recordkeeper, in an expensive managed account program when much less expensive target-date funds are readily available. The core theory was that without participant engagement, the managed account did not produce results worth the additional fees, particularly when target-date funds could have produced similar results at a lower cost – meaning the managed account amounted to little more than an overpriced TDF that “significantly and imprudently” increased the administrative fees paid to the recordkeeper.
Hanigan v. Bechtel Global Corp. (E.D. Va., No. 1:24-cv-00875) — original complaint filed May 24, 2024.
Dionicio v. U.S. Bancorp (D. Minn., No. 0:23-cv-00026) — filed January 6, 2023.
Gosse v. Dover Corporation (N.D. Ill., No. 1:22-cv-04254) — filed August 11, 2022.
Guyes v. Nestlé USA, Inc. (E.D. Wis., No. 1:20-cv-01560) — filed October 9, 2020.
Pizarro v. The Home Depot, Inc. (N.D. Ga., No. 1:18-cv-01566) — filed April 12, 2018.
[vi] maintaining a state of inactivity, motionlessness, or balance where no development or forward progress is occurring. It represents a standstill where equal and opposing forces neutralize each other, halting any change.
[vii] https://www.swayresearch.com/targetdate
[viii] Portfolio beta measures a collection of investments’ sensitivity and volatility compared to the broader market (such as the S&P 500). It indicates how much the portfolio’s value is expected to change relative to a benchmark index, highlighting its overall market or systematic risk.