The General Range, and Why It Is Wide
Commercial insurance agencies and books are generally reported to trade at 2x to 3.5x revenue, or 6x to 10x EBITDA, in 2026, a range synthesized across several M&A advisory sources rather than pinned to one single, precise study. Treat that range as directionally corroborated, several sources converge on similar numbers, rather than as a single verified figure to plug into a specific deal without further diligence.
The top of that range is reported to go to books with 90% or higher client retention, diversified carrier representation, and a modern digital workflow system already in place. A thin, single-carrier, paper-heavy book sits at the bottom of the same range, even before buyer type or line of business enter the picture.
Why Buyer Type Moves the Multiple So Much
The same reported data breaks the multiple down by who is actually buying. An individual owner-operator buyer is reported to typically pay 3x to 5x EBITDA, a small regional strategic buyer 5x to 7x, a private-equity-backed consolidator 8x to 12x, and a public brokerage 10x to 14x. Each step up reflects a buyer with a lower cost of capital, a larger integration platform to absorb the acquisition into, and a roll-up strategy that can justify paying more for the same book than an individual buyer financing the purchase personally ever could.
A seller comparing offers across buyer types is not comparing apples to apples on multiple alone, the buyer’s own capital structure is doing a large part of the work behind the number.
Why Line of Business Also Moves the Number
Line of business adds another layer to the same reported range: personal-lines P&C books are reported to trade at 5x to 7x, commercial lines at 7x to 10x, and specialty or employee-benefits books at the top, 9x to 12x. The pattern makes sense on its own terms, specialty and benefits books tend to be stickier and harder for a buyer to replicate organically than a personal-lines book, which commands a premium accordingly.
A buyer evaluating two books of similar revenue but different line composition should expect a meaningfully different price, not the same number adjusted only for size.
The One Named, Real Data Point Inside the Range
Most of the figures above come from a synthesized range across several advisory sources. Sica|Fletcher, a named M&A advisory firm, is reported to have tracked agencies with $1 million or more in EBITDA averaging 11.8 times adjusted EBITDA in H1 2025, across a dataset of more than 450 sell-side deals, alongside a reported count of 714 total brokerage transactions in 2025. Treat this specific figure, like the broader range above, as reported rather than independently re-confirmed, though it is the closest thing in this data set to a single, named, dated benchmark rather than a blended estimate.
For a buyer sizing up what a specific, larger book might actually cost, that named figure is a useful anchor, closer to real transaction data than the wider synthesized range on its own.
The Retention Number That Sets the Price
Underneath all of the tiers above sits one mechanic reported to move the multiple more than almost anything else: 90% or higher client retention is reported to earn premium pricing and a high cash-at-close percentage, while retention below 80% is reported to trigger heavy earn-out structures and compress the multiple by two or more full turns.
That is the practical reason two books with identical trailing revenue can carry very different price tags. A buyer evaluating a specific book should treat the seller’s retention history, not just the revenue line, as the number that actually determines what a fair offer looks like.
What This Means for Someone Evaluating a Book to Buy
Put together, a buyer walking into a real conversation about purchasing a book should expect the multiple to move on at least three variables at once, who is buying, what line of business the book writes, and how well the seller has actually retained clients, not a single flat number that applies regardless of any of those factors.
None of this replaces a real, deal-specific valuation, but it is enough to walk into a first conversation with realistic expectations instead of anchoring on whichever single multiple happened to come up first in a search.
Sources
The external data in this article draws on the sources below. Figures described in the text as estimates or industry triangulations are directional and are not attributed to a single dataset.
- CT Acquisitions, Insurance Agency Valuation (2026): Book Multiples
- Ada Astra Equity, Insurance Agency Valuation and EBITDA Multiples (2026)