How to de-identify accounting records for AI licensing

You can de-identify accounting records by stripping every personal identifier, applying the required anonymity tests, and then exporting the cleaned files to AI labs. We can run the process for you, or you can use our self-service tools if you prefer.

Why de-identifying accounting records matters

AI labs need real-world financial workflows to train useful models, but they cannot accept data that could reveal an employee, a customer, or a confidential business partner. Removing names, employee IDs, invoice numbers, bank details, and precise timestamps satisfies the legal anonymity tests used in major privacy regimes. When the data passes those tests, you can license it without exposing privacy risks or breaching customer contracts.

Identifiers to strip and cleaned data example

The data you own is often called "company data," "business records," or "operating records." A typical accounting row may contain a full customer name, an employee badge number, a unique invoice identifier, a bank account number, and an exact timestamp. After de-identification those fields are replaced with generic placeholders such as "Client A," "employee 632," masked bank digits, and a month-level date. The financial amounts and line-item structure stay unchanged, preserving the value for model training while eliminating personal identifiers.

Key identifiers you must remove

1. Full names of customers, employees or partners
2. Direct employee IDs or badge numbers
3. Customer-specific account numbers or codes
4. Bank account or routing numbers
5. Exact invoice numbers that are unique to a single transaction
6. Precise timestamps (down to seconds)
7. Any free-text field that includes personal contact information

Need data de-identified to meet HIPAA, CCPA or GDPR? See how we do it

Our de-identification service

We handle the entire cleaning workflow as a broker-managed service. First, we map your ERP or accounting system to understand where the data lives. Then we export raw files to an isolated, logged workspace that no one else can access. Automated scripts mask or replace the identifiers listed above, and the original raw copies are deleted on a recorded date to create an audit trail. Stable placeholders (for example "employee 632") are generated so the same pseudonym appears across all files, preserving relational integrity. Trained human reviewers inspect a random sample to confirm that no personal data remains, and we produce a written report that documents the removal process and the privacy test applied. The cleaned dataset is delivered to the AI lab only after you sign off on the final quote. For more details on the service, visit our de-identification page.

Pricing and licensing basics

Most approved deals land between $100,000 and $2 million USD, with a typical range of $200,000 to $300,000 USD. The price you receive depends on how much data you generate, the type of data, the years of continuous history on the same tools, and how rare your industry is. Clean rights and visible reasoning also raise the value. You keep ownership of the data and licence it to the AI lab, usually for a one-time payment; a later refresh is possible if you choose. The buyer pays our broker fee after the deal closes, and the de-identification fee is typically covered by the AI lab, though the exact arrangement is negotiated case by case.

Next step and compliance check

Before any buyer sees the data, we run a compliance check that confirms you own the records, that your customer contracts allow de-identified use, and that all personally identifiable information has been removed. The check also records which anonymity test was applied, whether it follows GDPR, CCPA, or another regional rule. The test you need depends on where the people in the data live; you can read more about regional privacy rules on our regions page. If you are ready to see what your accounting records look like once de-identified, click the button below to start the short questionnaire. After you submit, we will contact you with a tailored plan and a timeline that matches the complexity of your data.