with Background check business · 25-year number one background search provider
LenderHawk analysis. Not affiliated with or endorsed by Acquisitions Anonymous.
A $7 million ask on $1.1 million of EBITDA implies a 6.4x multiple, which only makes sense if growth and defensibility are both real.
A business can look like software on the surface while still depending on manual public-record retrieval and offshore document processing.
Customer integrations may be the real moat in background-check businesses, not the data itself.
No-SBA, all-cash-only marketing narrows the buyer pool and usually signals either confidence in price or a seller targeting strategic buyers.
API-native competitors can compress value if the incumbent’s workflow is still tied to legacy county-record processes.
A business serving Fortune 500 customers can still be vulnerable if its service is easier to modernize than the seller admits.
A high-volume, low-ticket model can produce attractive cash flow, but diligence has to prove the volume is durable and not easily displaced.
The hosts distinguish between businesses that have recurring revenue and integrations and businesses with actual product defensibility, automation, and modern APIs. The framework asks whether technology is the moat or merely the interface.
When to use: Use it when a service business is priced like software but may still depend on manual processes.
The listing asked $7 million for a business with $1.1 million of cash flow and $3.8 million of gross revenue.
Michael and Heather read the BizBuySell teaser and immediately anchor on valuation.
The implied multiple was about 6.4x EBITDA/cash flow.
Computed from the stated ask and cash flow in the listing.
The seller claimed the business had been operating for 25 years and was the number one background search provider in California.
The teaser framed the business as a long-tenured category leader.
The listing claimed coverage across all California counties, while most competitors only covered several counties.
The hosts used this as the main suggested moat.
The teaser referenced a 15-year wholly owned offshore document-processing facility.
This was presented as part of the cost structure and margin story.
The listing said potential buyers had to show proof of funds for the full purchase price and that no SBA loans would be accepted.
Michael highlighted this as an unusually restrictive sales filter.
Heather noted that background checks often cost around $25 each in practice, while Michael referenced a typical around-$50 to-$55 price point from Checker.
They used this to estimate plausible transaction volume and compare the market.
Diligence whether a county-record business still depends on paper retrieval in any meaningful geography.
Why: If the workflow is still manual, a newer API-based competitor may replace the incumbent more easily than the listing suggests.
Treat system integrations as a moat only if they are hard to unwind and deeply embedded in customer hiring workflows.
Why: A simple plug-in to an applicant-tracking system is not the same as true switching cost.
Ask whether the business is feeding third-party platforms or whether it is itself the system of record.
Why: If it is only a data supplier, its pricing power may be weaker than a platform’s.
Push hard on growth-rate evidence before paying a software-like multiple for a services business.
Why: A 6x-plus EBITDA price is only attractive if the business is growing and resistant to disruption.
Be skeptical of all-cash-only listing language unless the seller has a clear strategic-buyer rationale.
Why: It can shrink the buyer pool without proving the price is justified.
Michael contrasted fully digital county records in places like San Antonio with West Texas counties where records may still require a person named Jim to hand over paper. He used that contrast to explain why some legacy-record businesses can still have a real moat in large geographies.
Lesson: A manual public-record workflow can remain defensible where digitization is uneven.
Michael pointed to Checker as an API-first background-check platform that packages many underlying databases into one product. The example was used to show how legacy data wholesalers can get squeezed if they are only a source feeding newer software layers.
Lesson: When a workflow can be abstracted into an API, legacy operators need a sharper moat than “we have the records.”