A commercial lender's archive is unusual because every decision has an outcome attached. A credit memo argues for a loan, a committee approves it with conditions, and the file then records whether the borrower paid, stretched, or defaulted. Factoring companies add a second loop: verifying invoices, monitoring account debtors, chasing slow payers. Specialty lenders in equipment, asset-based or merchant finance each have their own checklists for what to look at and when to say no.
That pairing of written reasoning with a result is what buyers say they want. Mercor names finance and insurance and gives underwriting files as an example. micro1 names financial services and lists SOPs, playbooks and task histories. Loan officers and credit analysts score 100 out of 100 on O*NET's email scale.
The borrower is the complication. Credit files hold financial statements, tax returns, guarantor details and bank data that borrowers shared for one purpose. So the material least tied to any one borrower leads: credit policy, memo templates, underwriting and verification checklists, covenant-monitoring routines and collections playbooks. Raise every borrower record and every broker or funding-partner agreement with the licensing company before anything is exported.
Worth
What a lender's data may be worth
Pre-set for a typical lender: 30 staff and 12 years of records. No buyer publishes pricing by industry, so industry does not move the band. Our estimate, not a buyer quote.
Buyers
Which buyers want this data
Each reason is the buyer's own published statement about the tools, data or industries it takes, matched to how commercial and specialty lenders and factoring companies work.
Featured partners
micro1
Names financial services and lists SOPs, playbooks and task histories, which is how a credit policy and a covenant-monitoring routine read.10,11
- $100K to $2M+, micro1 says7
Watch out for: Says it removes personal details only "when relevant", so ask exactly how.12
Polyshares
Names financial services and buys CRM, email and spreadsheets, with a third-party partner scrubbing PII before licensing.13,14,15
- $100K to $2M+, Polyshares says8
- None, Polyshares says16
- An offer in 1 to 2 weeks, then paid in 30 to 60 days17
Watch out for: Exclusive by default, and every deal it lists is exclusive with no end date.18,19
Everyone else we reviewed
By score, with full reviews. We have no referral agreement with these companies, so we do not link out to them.
Mercor
Names finance and insurance with underwriting files and statements among its examples, and pays by wire 2-4 weeks after signing.1,20
Watch out for: It confirmed a cyberattack in 2026, and class actions followed.23,24
Nyne AI
Buys from Salesforce, HubSpot and NetSuite, where many lenders keep their broker pipeline and portfolio servicing records.25
- $100K or more, Nyne says26
Watch out for: Pays only after the dataset is accepted, and publishes no timeline.27
Buyer demand
How buyers' own tools rate commercial and specialty lenders and factoring companies
No buyer publishes a price list by industry. These are settings inside buyers' and brokers' own estimators and intake forms, read from their public pages on 2026-10-14. They show how each company sorts industries, not what any lender was paid. The category shown is the one a lender would most likely pick; that match is ours.
| Company | Its category | How it rates the industry |
|---|---|---|
| Troveo | Financial services, banking or fintech | Tier 1 of 4: "Buyers pay a premium for data from your industry." Price factor 1.3 in its estimator.28 |
| Polyshares | Financial services and fintech | Marked premium in its intake list29 |
| VMS | Finance | Higher weight in its estimator (factor 1.30)30 |
| Ventra | Legal, healthcare, financial services or accounting | Says it cannot take these industries right now31 |
Size rules buyers publish
Checked against 30 staff, the typical lender size this page's calculator is set to. Ask each buyer whether contractors and part-time staff count.
Polyshares
No headcount rule; the length and texture of the record matter more32
Mercor
None stated33
Troveo
No minimum stated; its estimator starts at 2034
Nyne
20+ US W-2 employees and 3+ years35
Handshake AI
20+ full-time employees and 3+ years36
micro1
Pewter
20+ staff and 3+ years38
Endless
Roughly 30+ employees39
Ventra
30+ US employees and 3+ years of records40
Supersoniq
50+ employees and 5+ years41
What buyers value
What in a lender's records buyers value
The column on the right is not legal advice: it lists what to raise with the buyer before anything is exported.
| Data | Where it lives | Why a buyer values it | Raise with the buyer |
|---|---|---|---|
| Credit policy and underwriting guidelines | Policy manual, shared drive | The lender's rules for what it finances, at what advance rate, with which exceptions. | Nothing specific |
| Credit memo templates and committee notes | Word, loan origination system | How an analyst argues for a deal and how committee pushes back, with the outcome known later. | Borrower names, financials and guarantor details in completed memos. |
| Invoice and debtor verification checklists | Factoring software (Cadence, FactorFox) or SOPs | The steps a factor takes to confirm an invoice is real and the debtor will pay. | Account debtor names and invoice detail. |
| Covenant and borrowing-base monitoring routines | Spreadsheets, portfolio management system | Monthly checks on collateral and covenants, with the actions taken when a number slips. | Borrower figures behind each certificate. |
| Collections and workout playbook | SOPs, CRM notes | How the lender escalates from a reminder to a forbearance or a recovery, written as steps. | Named borrowers in collections notes. |
| Broker and referral pipeline | Salesforce, HubSpot | Where deals come from, how fast they are screened and why most are declined. | Broker agreements and applicant details. |
A week of records
A week of data at a lender
- Monday: 55 broker submissions screened against the credit box; 41 declined with a reason code.
- Tuesday: an analyst drafts a memo for an equipment loan from the template; committee asks for a second guarantor.
- Wednesday: the factoring desk verifies 300 invoices and calls four account debtors from the checklist.
- Thursday: borrowing-base certificates come in; two clients are over-advanced and get a call.
- Friday: the collections team moves one account to a forbearance plan under the workout playbook.
Process
How it works with each buyer
In each buyer's own published words. Where a buyer publishes nothing, we say so rather than guess.
micro1
- Internal docs, SOPs and playbooks, knowledge bases, project management workflows, internal comms, templates, CRM and workflow metadata, task histories11
- 30 to 200 employees37
- $100K-$2M+ per data package; over $1M for unique data7
- PII removed "when relevant"12
- The company keeps ownership of its data and reviews samples before release42
- Not published
Polyshares
Mercor
Selling or closing
Selling or closing your lender? License its data first
Specialty lenders are bought by banks, private credit funds and larger finance companies, often for the origination team and the portfolio. The written credit method is part of what makes that team work, and it is rarely priced on its own. If a sale is coming, ask each licensing company whether policy manuals, memo templates and monitoring routines can be licensed first, separately from borrower files. Pewter says it takes companies that are operating, downsizing, winding down or closed.3
FAQ
Commercial lenders and factoring: questions, answered
Credit policy, templates, checklists and playbooks. Troveo, writing for financial firms, leaves out client identities, account details and personal financial information, which is a useful line to draw before a first call about borrower files.47
No buyer prices lenders on their own. Published ranges mostly run $100K to $2M, as the buyers' own claims: micro1 states $100K-$2M+, Jottings $250K-$750K for deep multi-year sets, and monsterdata.ai $300K-$3M per year for a recurring license. Nyne says it beats written offers from other buyers, which makes a second quote worth having.7,51,52,46
Most buyers ask for approval before anything moves. Mercor says nothing leaves your systems until you approve it, Goldmined.ai says nothing sells without the owner's approval, and micro1 says the company reviews samples first. Ask how each would extract from a loan origination system before scoping.53,54,42
We do not answer legal questions. Ask the licensing company: their team reviews this with you before anything is signed.
We do not answer legal questions. Ask the licensing company: their team reviews this with you before anything is signed.
We do not answer legal questions. Ask the licensing company: their team reviews this with you before anything is signed.
We do not answer legal questions. Ask the licensing company: their team reviews this with you before anything is signed.
Before you sign
Legal questions go to the licensing company
We do not answer legal questions. Ask the licensing company before you sign: their team reviews these with you.
Questions for this kind of business
- How does your review treat guarantor personal data and consumer credit reports in commercial files?
- Do loan agreements, participation agreements or warehouse lines limit sharing borrower records?
- How will borrower tax returns and bank statements be found and removed?
- Who owns this data: the company, an estate, or someone else?
- How do CCPA, GDPR, UK GDPR and state privacy laws apply, and is de-identified data still personal information?
- Do customer, vendor or platform contracts, NDAs or API terms restrict this?
- Do professional rules apply (AICPA, IRC 7216, HIPAA, ABA Model Rule 1.17, insurance agency contracts, adviser rules, state boards)?
Questions for any buyer
- Is the license exclusive, and for how long?
- Can you sublicense the data, and to whom?
- Which AI labs will receive it, and will you tell us?
- How long do you keep it, and how is it deleted?
- What is your liability cap, and who indemnifies whom?
- Will the contract ban re-identification of people in the data?
- Who removes personal data, by what method, and do we approve it first?