Businessolver®, a leader in Saas-based benefits technology and services, today released a comprehensive report showing the broad effects of financial literacy and risk tolerance on employees’ benefits decision-making—specifically, a lack of understanding how their lifestyle and financial preparedness affect their benefit elections.
Now in its fourth year, the MyChoice® Recommendation Engine Benefits Insights Report annually examines employees’ understanding, confidence, financial preparedness, and risk tolerance when making benefits enrollment decisions. Comprised of proprietary data from the MyChoice Recommendation Engine, Businessolver’s decision guidance tool integrated into its Benefitsolver® platform, the 2022 report takes a multiyear lens (from fall of 2019 to fall of 2021) to analyze and compare employees’ state of mind around benefits choices.
“Our data shows year-over-year that significant knowledge gaps are preventing employees from understanding how to elect the right benefits or utilize what’s already available to them,” said Sherri Bockhorst, Businessolver Senior Vice President of Innovation and Strategy. “Employees are making benefit elections independent of their lifestyle, finances, and health needs, indicating a clear need for personalized benefits information and just-in-time communication aligned to lifestyle milestones. Year-round benefits engagement strategies can close these knowledge gaps and reshape benefits from a one-time annual event to a personalized benefits experience aligned to employees’ unique situations driving better outcomes across the board.”
Benefits confusion remains universal; lack of financial preparedness and lifestyle management plays a role.
Businessolver’s 2022 data shows employees continue to remain confused about their benefits, holding steady over the four-year history of the Benefits Insights Report. A correlation between lifestyle and financial preparedness shows benefits literacy is closely tied to how employees understand their health and finances. According to the 2022 data:
- One third (31%) of employees are confused by their benefits, consistent with data from prior years.
- More than one half (60%) of employees describe themselves as healthy, and more than a third (35%) say they are in “average health.” Yet 60% say they take two or more prescription drugs.
- Nearly half (44%) would feel “panicked” about a $6,000 emergency room expense.
- Slightly more than half (55%) say they only “sometimes” save for emergency expenses; 12% “never” save.
Financial preparedness remains poor, though the data is starting to trend upwards.
There’s a disconnect for employees when it comes to how financial preparedness plays in to making benefits decisions. Businessolver data shows a slight increase in financial preparedness, though the majority of employees remain unprepared or unwilling to incur large health care expenses.
- When asked if a rainy-day fund would cover a large ER bill, 34% say they are unprepared; 33% have savings but not enough to cover the whole bill.
- Over half (55%) say they “sometimes” spend more than they earn.
- Nearly half (45%) could cover a $6,000 emergency room bill, but would prefer not to.
- Preparedness for unexpected bills (12%) is trending up two points from 2020, but these users are still the minority.
Leveraging year-round engagement strategies is key to engaging employees and improving literacy.
Businessolver’s data shows a clear lack of preparedness and understanding across employees when it comes to their benefits. Employers should consider year-round benefits strategies that highlight underutilized benefits and resources that often help offset financial stress and improve overall wellness.
Aligning year-round engagement strategies to counter employee knowledge gaps by steering them to available benefits can help improve literacy and positively affect outcomes in their moment of need.
Visit businessolver.com to find the full 2022 MyChoice Recommendation Engine Benefits Insights Report, along with related special content and an interactive dashboard that filters data by various demographic metrics.
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