How can my company offer better life insurance to everyone before it's too late?

A benefits consultant who hears "we want to offer better life insurance to everyone" is really being asked to solve two problems at once: widen eligibility so more of the workforce can get meaningful coverage, and do it without the cost and friction that historically priced lower-risk groups out of richer benefits. For years those two goals pulled in opposite directions. The lever that is starting to reconcile them is group life health data drawn from fast, non-invasive scans at the moment of enrollment, rather than from blood draws, paramed visits, or long evidence-of-insurability questionnaires that employees abandon. The "before it's too late" framing matters because the demographics are moving. An aging workforce, the spread of GLP-1 medications, and shifting mortality patterns are all repricing group life right now, and employers who modernize their data inputs early will be negotiating from a stronger position than those who wait for a bad renewal.

A GlobalData survey published in August 2025 found that more than half of US consumers are now willing to share wearable and biometric health data in exchange for a more tailored life insurance policy, signaling that the consent barrier consultants long assumed was fixed has shifted.

What group life health data actually changes

The traditional group life model runs on census data in and rate tables out. Employers submit ages, salaries, and headcount; the carrier applies manual rates; and anyone wanting coverage above the guaranteed issue (GI) limit completes evidence of insurability (EOI). That EOI step is where good intentions go to die. Gen Re's 2025 U.S. Group Medical Evidence of Insurability Underwriting Survey reported that participating carriers handled more than 2.5 million EOI applications in 2024, with an average processing time of roughly 11 business days. Every one of those days is a window for an employee to lose interest, leave a gap in coverage, or simply never finish. The result is the familiar paradox: a benefit designed to protect families ends up protecting mostly the people organized enough to push through the paperwork.

Group life health data from a non-invasive scan attacks that friction directly. Instead of asking an employee to schedule a clinic visit, a 60-second capture at enrollment can surface biometric signals associated with cardiovascular and metabolic risk. Those signals let carriers raise GI limits with confidence, offer simplified-issue tiers to people who would otherwise face full EOI, and segment risk on something more current than self-reported height and weight. The same Gen Re data showed high-volume carriers already pushing 82% of EOI cases through straight-through processing, which tells you the appetite for automated, data-driven decisions is well established. Non-invasive scans extend that automation to the front door of enrollment.

For a consultant, the practical translation is coverage that reaches more of the population. When the data layer improves, the carrier can say yes to more people at higher amounts without exposing the pool to adverse selection.

How the underwriting inputs compare

The choice facing employers is rarely "data or no data." It is which data collection model produces the widest eligibility at acceptable cost and participation. The table below frames the main options a consultant evaluates when redesigning a group life program.

Underwriting input model	Employee friction	Typical timeline	Data freshness	Effect on eligibility breadth
Census-only guaranteed issue	Very low	Immediate	None (demographic only)	Wide but capped at low face amounts
Full evidence of insurability (paramed/blood)	High	~11 business days avg	High at point of exam	Narrow; high abandonment above GI
Self-reported health questionnaire	Moderate	Days	Low and unverified	Moderate; prone to misstatement
Non-invasive scan health data	Low	Seconds to minutes	High and standardized	Wide, with higher GI limits and simplified tiers

A few points consultants should carry into client conversations:

• The non-invasive model is the only row that combines low friction with high data freshness, which is why it expands eligibility instead of trading one constraint for another.
• Census-only GI feels generous but quietly underserves employees because the face amounts are too small to matter for most families.
• Full EOI produces excellent data on the minority who complete it and nothing on the majority who do not.
• Verified scan data reduces the misstatement risk that makes carriers nervous about simplified-issue questionnaires.

Industry applications for benefits consultants

Expanding voluntary and supplemental life take-up

Voluntary life is where the eligibility gap is widest, because employees pay and therefore opt in deliberately. A voluntary benefits health scan that delivers an instant decision at enrollment removes the EOI delay that kills take-up. Consultants can position this as a participation play: higher enrollment spreads fixed program costs and improves the risk pool, which in turn supports better rates at renewal.

Raising guaranteed issue ceilings

The most direct use of group life health data is renegotiating GI limits. When a carrier has a standardized biometric snapshot of the eligible population, it can extend automatic coverage to higher amounts because the tail risk is better understood. For a mid-size employer, moving the GI ceiling up by even one salary multiple can be the difference between a benefit that looks competitive and one that does not.

Differentiating the consultant's own offering

As carrier products converge on similar terms, the advisory differentiator becomes program design. A consultant who can bring a scalable screening approach to a client conversation is selling a capability, not a commodity. This connects directly to wellness and population health goals, because the same scan that informs life underwriting can feed the employer's broader health strategy.

Current research and evidence

The evidence base for using non-invasive and digital health signals in life underwriting has moved from speculation to validation. In February 2025, Munich Re Life US, working with Klarity, published a study showing that physical activity data such as step count meaningfully refines mortality risk segmentation, demonstrating that non-clinical signals carry real actuarial value. Reinsurers including RGA have similarly documented how emerging health technologies can widen insurance reach by lowering the cost and intrusiveness of data collection.

The consumer side is moving in parallel. Beyond the GlobalData finding that a majority of US consumers will share data for a tailored policy, industry surveys indicate that more than 60% of life insurers are investing in accelerated underwriting systems that can ingest these new inputs. CoherentMI valued the global group life market at roughly $164.71 billion in 2025 and projected double-digit annual growth, which means the carriers building data-driven capability now are doing so inside a market large enough to reward the investment. The mortality pressures Securian Financial flagged for 2025 pricing, an aging workforce, GLP-1 adoption, and changing overdose patterns, are exactly the variables that current, granular health data helps carriers price accurately rather than conservatively.

The future of group life health data

The trajectory points toward enrollment becoming the primary data event in group life, displacing the separate medical exam entirely for most coverage tiers. Expect three developments over the next few years. First, GI and simplified-issue limits will keep rising as carriers gain confidence in standardized scan inputs, narrowing the gap between what guaranteed issue and fully underwritten coverage can offer. Second, the data captured for life underwriting will increasingly do double duty in wellness and population health programs, so employers stop paying for redundant screening. Third, governance will mature: as adoption grows, the controls around consent, fairness, and data segregation between the employer and the carrier will become a standard part of vendor evaluation rather than an afterthought. Consultants who build privacy and consent literacy now will lead those conversations instead of reacting to them.

The "before it's too late" instinct is sound for a structural reason. Risk pools reprice, and the employers who modernize their data inputs while their workforce is comparatively healthy lock in better terms than those who wait until a deteriorating loss experience forces the issue.

Frequently asked questions

Does using non-invasive scan data require employees to give up privacy to their employer? No. In well-designed programs the biometric data flows to the carrier or its administrator for underwriting, not to the employer in identifiable form. The employer typically receives only aggregate or de-identified reporting, and consent is captured at the point of the scan.

Can health data from a scan really replace a blood test for group life? For most coverage tiers, yes. Non-invasive scans surface biometric signals that let carriers make simplified and guaranteed issue decisions automatically. Very high face amounts may still trigger additional evidence, but the threshold for requiring it keeps rising.

How does this help employees who would normally be declined? Higher guaranteed issue limits and simplified-issue tiers mean more employees get meaningful coverage without full medical underwriting. The standardized data lets carriers say yes to a broader population while still managing pool risk.

What should a consultant look for in a screening vendor? Scalability across sites and remote workers, clear consent and data-segregation practices, instant or near-instant decisioning at enrollment, and the ability to feed both underwriting and wellness use cases from one capture.

Circadify is building scalable, non-invasive biometric screening designed for exactly this group enrollment and underwriting challenge, helping carriers and the consultants who advise them widen life insurance eligibility without the friction of traditional exams. Benefits consultants who want to evaluate the approach with a client population can explore the enterprise pilot program to see how group life health data can reshape what coverage their clients are able to offer.