Stop Loss Underwriting: A Deep Dive

This white paper explores the mechanics of stop loss underwriting, highlighting how carriers determine premium rates by blending actuarial manual rates with a group's historical claims experience. It explains how the credibility of experience—based on group size and data history—affects the weight of this blend, and how different carriers apply their own philosophies, ranging from manual-heavy to experience-heavy approaches.

The paper also examines underwriting guardrails like minimum percent-to-manual thresholds and the impact of leveraged trend, which causes stop loss liabilities to rise faster than general medical inflation. In today's environment of escalating high-cost claims and specialty drug pressures, understanding these dynamics is critical for brokers and employers seeking competitive pricing and sustainable renewals.

Through detailed examples and insights, readers will gain a clear understanding of how underwriting decisions vary across carriers and underwriters, and how these factors influence pricing, renewals, and strategic carrier selection.

Introduction

Stop loss insurance is a cornerstone of self-funded health plans, offering financial protection against catastrophic claims that exceed a predetermined threshold. While the concept is simple—reimbursing employers for claims above a specific deductible—the process by which carriers determine the premium rates is highly nuanced.

Stop loss underwriting blends actuarial modeling with real-world claims experience, and understanding this process is essential for brokers, consultants, and employers who want to make informed decisions.

At its core, stop loss underwriting is driven by two primary components:

1. Manual rates, which reflect population-level expectations
2. Experience-based rates, which incorporate the group's historical claims performance

These two elements are blended to produce the final quoted premium, and the weight of each component depends on factors such as group size, data stability (or credibility), the carrier's underwriting philosophy, and even individual underwriter discretion.

Beyond this foundational blend, additional forces shape pricing: leveraged trend, which amplifies cost increases above the deductible; guardrails like minimum percent-to-manual thresholds; and emerging market pressures such as specialty drugs, gene therapies, and predictive analytics.

Together, these dynamics explain why quotes for the same group can vary significantly across carriers—and why understanding the mechanics behind underwriting is essential for negotiating competitive rates and sustainable renewals.

Why Stop Loss Matters Now

Self-funding continues to dominate among large employers and is gaining traction with smaller firms. In 2024, 63% of covered workers were enrolled in self-funded plans, including nearly 79% at large firms and about 20% at small firms (KFF Employer Health Benefits Survey, 2024). This shift reflects employers' desire for greater cost control and flexibility—but it also introduces exposure to catastrophic claims.

Rising healthcare costs amplify this risk. Premiums for employer-sponsored coverage increased 6–7% year-over-year (KFF, 2024), and the frequency and severity of million-dollar claims are climbing, driven by high-cost conditions such as cancer, NICU stays, and specialty drugs. Gene therapies and advanced biologics add further volatility, with single treatments exceeding $2 million.

Against this backdrop, stop loss insurance is not just a financial safeguard—it's a strategic necessity. Understanding how carriers price this protection is critical for brokers and employers seeking competitive rates and sustainable renewals in an increasingly complex market.

Manual Rates: The Actuarial Baseline

Manual rates form the foundation of stop loss underwriting. These rates are developed using actuarial tables and statistical modeling, representing what a group *should* cost based on population-level expectations rather than its individual claims history. Carriers construct these manuals using large, multi-year datasets—often purchased from third-party actuarial firms—and apply predictive models to estimate expected losses for different risk profiles.

Key Factors in Manual Rate Development

• Demographics: Age, gender, and geographic location of the covered population
• Plan Design: Deductibles, copays, coinsurance, and out-of-pocket maximums
• Industry Type: Certain industries carry higher or lower risk profiles
• Trend Assumptions: Expected increases in healthcare costs over time, including both medical trend and leveraged trend
• Stop Loss Contract Type: Paid vs. incurred, contract periods (e.g., 12/15, 24/12)

Carriers typically update their manuals annually to reflect changes in medical inflation, leveraged trend, and observed claim patterns. For example, if medical trend is projected at 7% and leveraged trend at 20% for certain deductible levels, manual rates will incorporate these adjustments to maintain actuarial soundness.

Illustrative Example

A carrier might determine that a group with:

• 200 employees
• Average age 42
• $100,000 individual specific deductible
• Standard $2,000 deductible PPO plan design

...should be priced at $100 PEPM (Per Employee Per Month) based on its manual.

Practical Note

Manual rates often serve as the starting point for underwriting. Carriers then adjust for experience, lasers, contract features, and market loads (administrative fees, taxes, commissions, and margin) to achieve portfolio-level targets—commonly aiming for a loss ratio of 65–70% (industry standard; see Segal Health Plan Cost Trend Survey).

Experience-Based Rates: Real-World Claims History

The second component of stop loss underwriting is the group's actual claims experience. While manual rates provide a population-level baseline, experience-based rates reflect how the group has performed historically. Carriers analyze detailed claims data to assess risk and project future costs.

Key Elements Carriers Review

• Large Claims: Identification of high-cost individuals and their diagnoses, such as cancer, transplants, or NICU stays
• Monthly Paid Claims: Total claims paid over time, often broken down by medical and pharmacy
• Utilization Patterns: Frequency of doctor visits, prescriptions, and hospitalizations
• High-Cost Drugs or Treatments: Use of specialty medications, biologics, and emerging therapies like gene treatments

Once analyzed, this experience is trended forward to the rating period to account for expected cost increases. Carriers often apply different trend assumptions for medical and pharmacy claims, and in some cases, leveraged trend adjustments for stop loss layers. Specialty pharmacy trends—such as GLP-1 drugs for diabetes/weight management, oncology agents, and gene therapies—are a persistent headwind and receive specific modeling attention in many underwriting manuals.

Illustrative Example

If a group has run well historically, its experience might suggest a lower rate—say, $60 PEPM compared to a manual rate of $100 PEPM. However, the credibility of this experience depends on several factors:

• Group Size: Larger groups provide more reliable data
• Data Duration: Multiple years of claims history improve predictability
• Consistency: Stable patterns are more credible than volatile swings

Smaller groups or those with limited history are considered less credible, meaning carriers will lean more heavily on manual rates when blending the final premium.

Blending Manual and Experience

Neither manual rates nor experience alone can fully predict future risk, so carriers blend the two to arrive at a final quoted premium. This blending process is guided by credibility theory, which determines how much weight to assign to the group's historical experience versus the manual baseline.

How Credibility Works in Practice

• Larger groups with multiple years of stable claims data receive higher credibility, meaning more weight on experience
• Smaller groups or those with limited or volatile history lean more heavily on manual rates

The Actuarial Formula Behind the Blend

A simplified credibility formula often used in underwriting is:

R = ZX + (1−Z)M

Where:

• R = Credibility-weighted rate
• X = Group's average loss (experience)
• M = Manual rate
• Z = Credibility factor (0–1), based on group size and data stability

This formula underscores why even large groups rarely receive a 100% credibility rating using just their experience—manual rates remain a stabilizing anchor.

Practical Insight

Credibility weighting is standard across insurance lines and documented in actuarial literature (e.g., Bühlmann and Limited Fluctuation methods; SOA Credibility Theory Practices). While carriers rarely disclose their exact formula, the principle is consistent: more credible experience = more weight on actual claims.

Carrier Philosophies and Variability

Each carrier has its own underwriting philosophy, which influences how heavily they rely on manual rates versus experience-based rates. This variation can lead to dramatically different quotes for the same group—even when both carriers have access to identical data.

• Manual-heavy carriers tend to be more favorable for groups with poor claims history because they rely less on actual performance and more on population-level assumptions
• Experience-heavy carriers are more competitive for groups that have run well, as they reward strong historical performance

Why Philosophies Differ

• Portfolio Strategy: Some carriers pursue growth and will stretch to the floor (minimum percent-to-manual). Others tighten during periods of adverse portfolio results or inflation, reducing flexibility or increasing second-year rate caps (Milliman Medical Index, 2023)
• Risk Appetite: Some carriers prioritize predictability and loss ratio targets, while others accept more variability for competitive positioning
• Market Conditions: Competitive pressure, renewal persistency goals, and internal profitability targets can all influence how aggressively a carrier applies experience credibility

Key Takeaway

Carrier philosophy matters. Brokers who understand these differences can strategically market groups to carriers whose approach aligns with the group's risk profile—maximizing competitiveness and minimizing surprises at renewal.

Guardrails: Minimum Percent-to-Manual

Even experience-heavy carriers have limits. Most carriers have a minimum percent to manual—a floor below which they cannot quote, regardless of how favorable the group's experience is. This guardrail ensures pricing stability and prevents carriers from undercutting their actuarial assumptions.

Most carriers set this floor between 50% and 70% of their manual rates (Law Insider - Tiered Underwriting). So, if a carrier's manual rate is $100 PEPM and their minimum percent to manual is 60%, the lowest they can quote is $60 PEPM—even if the experience suggests a lower rate.

This limitation often becomes apparent on renewals, especially for groups that have run well for multiple years. If the group is already at the carrier's floor, the renewal rate may still increase—not because of poor claims, but because the manual rate itself is rising due to medical and leveraged trend.

Regulatory Backdrop

Some states and the NAIC Stop-Loss Insurance Model Act (#92) govern aspects of stop loss coverage standards, including minimum attachment points and filing requirements. The model establishes minimum attachment points (specific ≥ $20,000; aggregate ≥ 110% of expected claims for groups of 51+), but enforcement varies by state, and not all states adopt the model in full. Brokers should confirm state-specific rules early in the quoting process.

Leveraged Trend vs. Medical Trend

To understand why manual rates increase annually, it's important to distinguish between medical trend and leveraged trend.

Medical trend refers to the general increase in healthcare costs year-over-year. This includes inflation, provider rate increases, new technologies, and increased utilization. Medical trend typically ranges from 7–9% annually (Segal 2024 Health Plan Cost Trend Survey; Milliman).

Leveraged trend, on the other hand, applies specifically to stop loss coverage. It reflects how higher deductibles amplify cost increases. Because stop loss only covers claims above a certain threshold (e.g., $100,000), even small increases in large claims can have a disproportionate impact on the carrier's liability.

Key Insight

Leveraged trend is not uniform—it's higher for claims just above the deductible and lower for very large claims. Carriers use an average leveraged trend, based on their book of business or actuarial models, to adjust manual rates each year.

Additionally, ISL deductible size also affects leveraged trend: higher deductibles reduce exposure to smaller claims, which tend to have higher leveraged trend. As a result, carriers may apply different leveraged trend assumptions depending on the deductible level being quoted.

Additional Tools: Lasers and Aggregating Specific Deductibles

Beyond manual and experience-based pricing, carriers use additional underwriting tools to manage risk exposure—two of the most common being lasers and aggregating specific deductibles (ASDs).

Lasers

A laser is an underwriting technique where the carrier assigns a higher individual specific deductible to one or more high-risk members identified during the underwriting process. These individuals often have known conditions or ongoing treatments that could result in catastrophic claims, such as:

• Organ transplants
• Advanced cancer therapies
• Gene therapy candidates

By applying a laser, the carrier limits its exposure on these members while still providing coverage for the rest of the group at standard deductibles. While lasers can reduce overall premium, they shift more risk back to the employer and can create budgeting challenges if the lasered member incurs a large claim.

Aggregating Specific Deductible (ASD)

An aggregating specific deductible is an additional layer of risk assumed by the employer before stop loss reimbursements begin.

ASDs are often used to lower premiums without increasing volatility as much as raising the ISL deductible for every member. They can be particularly effective for groups with stable claims but wanting to reduce fixed costs.

Specialty Drugs & Gene Therapies: Market Pressure on Stop Loss

Specialty drug costs continue to outpace overall medical trend, creating significant challenges for stop loss underwriting. Therapies for oncology, autoimmune conditions, and metabolic disorders—such as GLP-1 drugs—are driving sustained cost growth. Milliman's 2024 pharmacy trend analysis highlights rising unit costs and the introduction of novel therapies as core drivers of this pressure.

Gene therapies amplify the challenge. These treatments often involve a single administration with multi-million-dollar price tags. For example:

• Zolgensma (for spinal muscular atrophy): >$2.125 million (FDA-approved 2019)
• Lenmeldy (for metachromatic leukodystrophy): ≈$4.25 million WAC (FDA-approved March 2024)

And the pipeline is growing rapidly—over 4,000 new therapies are in development (Emerging Therapy Solutions). This creates enormous pressure on future stop loss premiums.

Carrier Strategies to Mitigate Risk

Carriers are responding with innovative solutions to spread risk and stabilize pricing:

Embedded Programs:

• Companion Life includes its CompanionCARE Gene Therapy Program in all new and renewal stop loss policies at no additional cost.
• Sun Life provides its No New Laser Gene Therapy Enhancement.
• Crum & Forster offers similar integrated protection within its stop loss rates.

Standalone Enhancements:

• Anthem/Wellpoint offers a standalone solution priced at approximately $3.50 PEPM to offset catastrophic drug costs.

AI Underwriting When Claims Experience Is Unavailable

Stop loss underwriting traditionally relies on two pillars: actuarial manual rates and historical claims experience. But what happens when one of those pillars—namely, the claims experience—is missing?

This scenario is common for small groups transitioning from fully insured coverage, and start-ups entering the market. Today, artificial intelligence (AI) is changing that equation.

How AI Underwriting Bridges the Gap

AI-driven underwriting platforms offer an alternative by predicting risk using non-traditional data sources and advanced modeling techniques. Instead of relying solely on historical claims, these tools analyze:

• Medical and Pharmacy Data: From eligibility feeds, Rx histories, and lab results
• Behavioral and Lifestyle Indicators: Social determinants of health (SDoH), engagement patterns, and demographic attributes
• Population Health Signals: Predictive markers for chronic conditions, high-cost therapies, and hospitalization risk

Leading AI Solutions in Stop Loss

Two platforms dominate this space:

[Gradient AI](https://www.gradientai.com/) (SAIL): Specializes in medical, Rx, and lab data to forecast large-claim risk. Its models refresh monthly and achieve high match rates, making it ideal for MGUs and carriers quoting small groups.

[Verikai](https://www.verikai.com/) (CaptureHealth & Capture360): Expands beyond clinical data to include behavioral and lifestyle factors. By modeling social determinants and engagement patterns, Verikai predicts utilization trends that claims history alone cannot reveal.

Both platforms integrate with underwriting workflows, reducing reliance on IHQs and accelerating quote turnaround times.

Best Practices for Brokers & Employers

Successful stop loss marketing begins with preparation. Brokers who anticipate underwriting needs and present a complete, strategic picture of the group can dramatically improve quote competitiveness and renewal stability.

Start with Data Readiness

Underwriters price risk based on credibility, and credibility depends on data quality. Whenever possible, provide three to four years of monthly paid claims, not just 12–24 months. Include large claimant details with diagnosis, monthly claims with enrollments, and plan designs.

Plan Ahead for Leveraged Trend

Stop loss liabilities rise faster than medical inflation, especially for claims near the deductible threshold. Brokers should advise employers to consider annual increases to individual specific deductibles or implement aggregating specific deductibles (ASDs) to lower fixed costs without introducing excessive volatility.

Address Gene Therapy Exposure Early

Multi-million-dollar therapies are no longer hypothetical—they're here. Evaluate whether carriers offer embedded gene therapy programs or standalone riders, and understand coverage limits and exclusions.

Match Carrier Philosophy to Group Profile

Manual-heavy carriers tend to be more competitive for groups with adverse or volatile experience, while experience-heavy carriers reward strong historical performance. Understanding these philosophies—and aligning them with the group's risk story—is critical for maximizing competitiveness.

Conclusion

Stop loss underwriting is both an art and a science. While actuarial models and manual rates provide the foundation, the blending of experience, carrier philosophy, and market dynamics creates significant variability in pricing. Brokers and employers who understand these mechanics are better positioned to navigate the market, secure competitive rates, and build sustainable self-funded programs.

In an environment of rising healthcare costs, specialty drug pressures, and evolving AI tools, staying informed about underwriting practices is more important than ever. By partnering with knowledgeable advisors and leveraging strategic insights, employers can turn the complexity of stop loss into a competitive advantage.

References

1. Kaiser Family Foundation (KFF). *2024 Employer Health Benefits Survey*. https://www.kff.org/health-costs/report/2024-employer-health-benefits-survey/
2. Milliman. *2024 Milliman Medical Index*. https://www.milliman.com/en/insight/2024-milliman-medical-index
3. Milliman. *2023 Milliman Medical Index*. https://www.milliman.com/en/insight/2023-milliman-medical-index
4. Segal. *2024 Health Plan Cost Trend Survey*. https://www.segalco.com/consulting-insights/2024-health-plan-cost-trend-survey
5. NAIC. *Stop Loss Insurance Model Act (#92)*. https://content.naic.org/sites/default/files/inline-files/SLI_SF.pdf
6. Society of Actuaries. *Credibility Theory and Practice*. https://www.soa.org/resources/tables-calcs-tools/credibility/
7. Tokio Marine HCC. *2025 Stop Loss Market Trends*. https://www.tmhcc.com/en-us/news-and-articles/thought-leadership/jay-ritchie-current-stop-loss-market-trends
8. FDA. *Gene Therapy Approvals - Zolgensma*. https://www.fda.gov/news-events/press-announcements/fda-approves-innovative-gene-therapy-treat-pediatric-patients-spinal-muscular-atrophy
9. FDA. *Gene Therapy Approvals - Lenmeldy*. https://www.fda.gov/news-events/press-announcements/fda-approves-first-gene-therapy-children-metachromatic-leukodystrophy
10. Gradient AI. https://www.gradientai.com/
11. Verikai. https://www.verikai.com/
12. Law Insider. *Tiered Underwriting Clauses*. https://www.lawinsider.com/clause/tiered-underwriting