Is Your Company Ready for Self-Funding? A Feasibility Guide

Most employers who ask “should we self-fund?” skip the one step that actually answers the question: a self funded plan feasibility study. Instead of running a structured financial analysis, they go straight to talking to vendors, collecting stop-loss quotes, or asking their broker for an opinion. That approach separates a defensible decision from an expensive guess, and not in a good way.

Self-funding can save a mid-sized employer real money. We’re talking about eliminating insurer profit margins, premium taxes, and carrier-controlled reserve padding. But moving without evidence can expose an employer to serious claims volatility, cash flow gaps, and vendor misalignment that costs more than the original problem. The math has to support the move before the move happens.

This guide walks through every component of a self funded plan feasibility study: the data you need, how to model stop-loss scenarios, how to run the breakeven equation, and how to read the results honestly. By the end, you’ll know where your company stands, not where your broker hopes you’ll land.

What a Self Funded Plan Feasibility Study Actually Covers

A self-insured feasibility study is a structured financial and risk analysis built to answer one question: can this employer fund its own claims without blowing up its budget? It’s not a gut check. It’s not a sales pitch. It’s evidence-based analysis with numbers that either support a transition or tell you to wait.

The study has four core components that work together to build a complete picture of financial readiness. Historical claims data analysis examines what the group has actually spent on medical, pharmacy, and behavioral health claims over the past several years. Stop-loss threshold modeling tests different attachment point structures to determine what risk the employer should retain versus transfer. Workforce risk profiling evaluates age distribution, dependent enrollment, chronic condition prevalence, and industry-specific utilization patterns. Financial cost projection then compares projected self-funded total costs against the current fully insured premium to locate the breakeven point.

Many employers who’ve stayed on a fully insured plan for years have never seen this analysis. Some brokers may not proactively run feasibility studies, particularly when the results might reveal the employer should change plan structures. Employers often don’t know to ask because they assume their broker would have raised it already. That assumption costs money every year.

Group Size and Workforce Risk: The Thresholds That Actually Matter

The first qualifying question is straightforward: how big does the group need to be? The standard minimum for a traditional self-funded plan is 100 employees. Below that threshold, stop-loss pricing tends to become unfavorable enough to erase the financial advantage. Companies with 25 to 99 employees can access self-funding through a group captive structure, but traditional self-funding at that size typically doesn’t pencil out.

Group size alone doesn’t tell the full story. Claims credibility matters just as much as headcount. A group of 150 employees with stable demographics and low utilization is a fundamentally different risk profile than a group of 150 employees with three catastrophic claimants in the last two years. The self-funding readiness assessment needs to account for both dimensions.

Workforce risk profiling goes beyond counting heads. Consultants evaluate age distribution, dependent enrollment rates, chronic condition prevalence, and geographic concentration to build a predictive picture of future claims. For manufacturers, construction firms, and transportation companies, industry-specific factors like physical labor, injury exposure, and workforce age skew also get factored in. A claims risk score built from this data tells you how predictable the group’s cost trajectory will be, which directly affects whether stop-loss pricing is workable.

A group that passes the headcount test but fails the risk profile test is not ready. Both screens have to come back clean before a self-funding transition makes financial sense.

Self Funded Plan Feasibility Study: Claims Data and What to Look For

How far back to go

A reliable self-funded health plan analysis requires a minimum of 36 months of claims data, and five years is the generally recommended standard. A longer window lets you spot multi-year trends, isolate outliers, and distinguish between a one-time shock event and a structural cost problem. Actuaries consistently recommend the five-year window because shorter periods increase modeling uncertainty and can produce projections that don’t survive contact with reality. Building a feasibility model on 12 months of data is building it on assumptions.

What to pull

Claims data in this context means paid versus incurred claims, enrollment and disenrollment continuity, line-of-business breakdowns covering medical, pharmacy, and behavioral health, and large claimant identification. Employers are entitled to their own data. If your carrier or broker hasn’t provided it, request it directly. ERISA’s plan sponsor provisions give employers the right to this information, and any hesitation from a vendor to hand it over is itself a red flag worth noting.

Outlier handling

Outlier handling is one of the most important parts of the analysis. A single high-cost claimant, a transplant, a cancer diagnosis, a NICU stay, can distort a feasibility model if left unaddressed. Consultants typically laser out catastrophic claims or restate them when projecting forward-looking cost expectations. The goal is to model what a “normal” claims year looks like for the group, with stop-loss coverage providing the backstop for abnormal events.

Claims volatility analysis also surfaces red flags that can disqualify a group entirely. High monthly claim swings, recurring large claims rather than isolated ones, unmanaged specialty pharmacy exposure, and concentrated chronic conditions in the workforce are all signals that self-funding may introduce more financial risk than it resolves. These patterns don’t always mean “no,” but they often mean “not yet” until the underlying drivers are addressed.

Running a Self Funded Plan Feasibility Study: Stop-Loss Modeling and the Breakeven Equation

Stop-loss insurance is what makes self-funding manageable for mid-sized employers. Specific stop-loss caps the employer’s liability on any individual claimant. Aggregate stop-loss caps total annual claims exposure across the entire group. For most employers under 500 lives, both layers are essential, the exact structure and necessity depends on actuarial analysis and the employer’s risk tolerance, but relying on just one layer typically leaves significant exposure on the table.

For employers with 100 to 300 employees in 2026, specific stop-loss attachment points typically range from $50,000 to $100,000 per claimant. A group of 100 employees might set their specific deductible at $50,000 to $75,000. A group of 250 employees might carry a $75,000 to $100,000 attachment point.

Aggregate attachments are usually set at 110 to 125 percent of expected claims, creating a defined worst-case scenario the employer budgets against. Consultants test multiple configurations to find the structure that balances premium cost against risk exposure. A lower attachment point means less retained claims risk but a higher stop-loss premium, and that trade-off directly affects the breakeven outcome. This is also where TPA and stop-loss feasibility modeling overlap: the right TPA relationship can often unlock better stop-loss market access than going it alone.

The breakeven equation is straightforward. Add projected claims, TPA and administrative fees, and stop-loss premiums together. Compare that total against the current fully insured premium. If the self-funded total is lower, you have a financial case to move. If it’s higher, or within a margin that doesn’t justify the added operational complexity, you don’t. The formula: (Projected Claims + Admin Fees + Stop-Loss Premium) vs. Fully Insured Premium. Everything else in the feasibility process feeds into those four numbers.

A practical example: a 200-employee manufacturer paying $2.4 million in fully insured premiums might project $1.6 million in claims, $180,000 in TPA fees, and $320,000 in stop-loss premiums. That totals $2.1 million, $300,000 in annual savings. That’s a case worth pursuing. If the stop-loss came back at $520,000 due to adverse risk profile findings, the case weakens considerably. The self-funded plan cost projection has to be honest, not optimistic.

TPA Fees, Admin Costs, and the Cash Reserve Question

Once the breakeven model takes shape, the next place employers routinely underestimate costs is on the administrative side. A clear-eyed view of TPA fees is essential before any transition decision gets made. TPA fees range from $5 to $60 per employee per month depending on group size and scope of services. Large national carriers operating on an ASO basis often bill around $225 per enrollee annually. Independent TPAs frequently beat that number, which is one reason employer-driven vendor evaluation matters so much in this process.

Reserve requirements are the other cost that doesn’t always make it into the initial conversation. Unlike a fully insured plan where the carrier absorbs claims risk, a self-funded employer needs a cash reserve or a dedicated line of credit to cover claims that run higher than projected in any given month. Industry practice among plan consultants holds that two months of reserves covers basic run-out purposes, while six to seven months covers catastrophic exposure depending on stop-loss structure. IBNR reserves, covering claims incurred but not yet reported, typically run 20 to 25 percent of total annual claims and need to be budgeted before day one.

Smaller groups pay a higher percentage of assets in total admin costs. Plans under $10 million often exceed 1.00 percent of assets in administrative fees. Mid-sized plans average 0.60 to 0.90 percent. That scale effect is real, and it’s part of why the feasibility model needs to include every cost layer, not just stop-loss premiums. The numbers only tell the full story when all costs are on the table.

How to Read Your Results and What a Smart Next Step Looks Like

A completed feasibility study produces one of three outcomes. The data supports moving to a self-funded structure now. The data suggests piloting through a level-funded or captive arrangement first, which lets the employer begin capturing savings with less immediate risk exposure while building claims data credibility. Or the group isn’t ready, and the right call is to stay fully insured for 12 to 24 months while addressing specific identified risk factors like pharmacy spend, chronic condition prevalence, or workforce demographics.

Interpreting the results requires context, not just arithmetic. A group with one catastrophic claimant in the last three years looks different from a group with three recurring high-cost members. A manufacturer with a concentrated workforce in a single location carries different geographic risk than a logistics company spread across twelve states. The numbers don’t make the decision alone. Someone with experience reading these models needs to sit with the data and make a defensible recommendation, not a convenient one.

Internal HR teams can gather claims data and request loss runs. But modeling stop-loss scenarios, profiling workforce risk, and building a credible self-funded plan cost projection requires actuarial expertise and vendor market knowledge that takes years to develop. At BeneSmart, our engagements begin with a systematic feasibility study that anchors the entire multi-year benefits strategy, giving employers a data-driven starting point before a single vendor is changed or a plan document is rewritten. That disciplined first step is what separates a successful self-funding transition from an expensive one.

The Decision Starts With the Data, Not the Instinct

A self funded plan feasibility study isn’t complicated, but it requires the right data, an honest financial model, and someone who reads the results without a conflict of interest. The employers who move to self-funding successfully don’t do it because it sounds like a good idea. They do it because the numbers said so, and they had the analysis to prove it.

If you haven’t seen a breakeven analysis comparing your current fully insured premium against projected self-funded costs, you don’t actually know whether you’re overpaying. You’re guessing. That analysis is where the decision starts. And it’s often where employers realize that no one in the room had been running the numbers on their behalf.

Run the study. Read the results honestly. Then decide. If you want a second set of eyes on your claims data or a clear picture of what self-funding would actually cost your company, BeneSmart can start that conversation without the sales pitch.