Leveraging big data to gain insights, defined contribution service providers are adding and refining tools to help plan executives and consultants access and analyze participant data to improve savings behavior in their plans.
"The really macro trends that have been going on over the last few years around (the) growth and maturity of our technology, the rise of consumerism and really the whole disruption in the financial services space with robo-advisers ... have all really escalated over the last four to five years," said Lynda Abend, Boston-based chief data officer at record keeper John Hancock Retirement Plan Services. "That's where we said ... we really need to dedicate energy to understanding and utilizing the information that's now available to us to help participants save and plan for retirement."
Since Ms. Abend was appointed the firm's first chief data officer nearly four years ago, her priorities have been "making sure that we are leveraging all of the information the firm has about a participant, a client, a plan, to drive better outcomes" and ensuring the data are maintained in a secure environment and used only in the best interest of participants, she said.
For several years, John Hancock has provided record-keeping clients and their consultants information on participant activities through an online "analytics dashboard." However, recently the firm has been leveraging machine-learning algorithms and third-party data from the Bureau of Labor Statistics and data aggregators such as KBM Group to help enhance its understanding of participants and the challenges they face, Ms. Abend said.
Benefited from deeper dive
One client, Farm Credit Foundations, an agriculture-focused financial services company with more than $1 billion in employee 401(k) assets, has benefited from this deeper dive. Officials at the company, which does an auto-enrollment sweep every other year, wanted to know why the same employees kept opting out after they were auto enrolled, Ms. Abend said.
After an initial analysis of the basic employee data available to John Hancock did not reveal anything striking about these employees, the firm used machine-learning algorithms and data from KBM on Americans' personal debt, household activities and spending habits to provide broader insight into these employees and identify employees who might change their contribution behavior.
John Hancock learned that employees who kept opting out were single mothers or midcareer people who faced similar financial stress returning to the workforce, Ms. Abend said.
To help encourage these employees to participate in the 401(k) plan, Farm Credit Foundations, St. Paul, Minn., lowered the auto-enrollment default rate to 1% from 6%, which it coupled with auto escalation.
Nearly 85% of the non-contributors who were auto enrolled at the lower default rate stayed in the plan, and many increased their contribution rates, Ms. Abend said.
Other data projects John Hancock has been working on include leveraging Bureau of Labor Statistics information on consumer spending habits to help near-retirees understand what their spending needs could look like in retirement if they move to Florida from New York, for instance.
The firm also is looking at what activities lead up to someone taking a retirement plan loan so it can deliver educational content to participants who might be at risk of taking a loan.
Rollovers, too, are becoming more of a focus for plan sponsors, said Alison Borland, San Francisco-based executive vice president, defined contribution, at record keeper Alight Solutions.
"Even though the fiduciary rule is dead, it definitely raised awareness and curiosity about rollovers," Ms. Borland said. More plan executives are focused on rollover behaviors and are wondering whether IRA rollovers from their plans are really "the result of unbiased guidance and education for folks who really want the individual retirement account solution" or if participants are being steered into IRA products.
Ms. Borland said Alight released a white paper last year with some high-level benchmarking information on rollovers that has "led to some really interesting and rich conversations with plan sponsors when their rollover behavior is outside of what we consider typical or normal."
In general, each year, Alight officials do a "deep dive" with plan executives on participant behaviors in their own plans and benchmark those behaviors against other plan sponsors in their industry and the rest of Alight's record-keeping clients.
Among the behaviors analyzed: participants' savings rates, asset allocations, investment returns and assets being withdrawn from plans.
More going online
Historically, these insights were provided to plan executives on paper; only raw participant data and limited charts and reports were available online. However, the firm is in the process of making these insights available to plan executives online so they can access it whenever they like.
An "emerging area" that Alight officials are thinking more about is how participants are (or aren't) saving in their health savings accounts vs. their DC accounts, Ms. Borland said. (Alight provides health and welfare benefits administration in addition to DC and defined benefit administration.)
Leveraging information about participants' interactions online to deliver personalized digital experiences is an area Ms. Borland sees as an opportunity for the retirement industry.
In some ways, Alight already has worked to personalize the participant experience — by providing individual retirement readiness scores, for example. Moving forward, Ms. Borland said she sees an opportunity to do things likes serve up targeted messages, prompts to take action, or information and resources based on what Alight knows about the participant and how he or she has interacted with the website before.
One focus at Empower Retirement this year and next is improving the way participant data are interpreted and presented to plan sponsors and consultants, said Edmund F. Murphy III, Empower's Denver-based president.
Participant data "really has to be offered in a way that's consumable and in a way that can help (a plan sponsor) either mitigate risk or improve outcomes or work in conjunction with us, the provider, on targeting strategies at specific employee populations," Mr. Murphy said.
A current project aims to expand the benchmarking data available to plan sponsors through their Empower sponsor portals, he added.
Soon, plan sponsors will be able to see how their participants' income replacement levels compare to participants at other companies and demographics at those companies.
Additionally, at the end of last year, Empower released an online tool to help sponsors and consultants (clients and non-clients) estimate the impact of potential plan design changes — such as implementing or changing employer match formulas, auto-enrollment default rates and auto-escalation rates — on employees' retirement readiness and contribution expenses.
At Fidelity, officials hope to put an internal financial wellness assessment tool in hands of plan sponsors within the next year. The intent is for plan sponsors with participants using Fidelity's financial wellness tools to be able to readily see where their participants are expressing concerns, whether it be college debt, budget planning, having an emergency fund or medical expenses, said Phil Chisholm, Smithfield, R.I.-based vice president of product management at Fidelity.
Results are aggregated to protect individual privacy.
Currently, only Fidelity officials have ready access to this tool, although they have been sharing insights with plan sponsors for approximately nine months.
In December, Vanguard officials launched a new version of the Vanguard Plan Comparison Tool, which aggregates data from the firm's annual "How America Saves" report to help plan sponsors and consultants compare their plans to 2,000 other plans for which Vanguard is a record keeper. Users can now build and analyze custom reports, selecting characteristics like plan size, industry, and participants' gender and tenure, a spokeswoman said. Users do not have to be Vanguard clients. (Under the old tool, plan sponsors could only splice data by industry type.)