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DataNexx

Data category

Accounting, Audit & Tax Data

Reconciliation exceptions, audit workpapers, review notes and tax memos — each linked to how it was resolved.

Accounting data for AI is the working record behind the numbers: reconciliation exceptions, adjusting entries, audit workpapers, review notes and tax memos. AI teams use it to build tools that close the books, test controls and research tax questions. Final statements are public; the judgment that produced them is not. DataNexx helps firms license de-identified records with each client's written authorization.

Why it matters for AI

Recorded, judged, resolved.

Financial statements show the final numbers; working papers show the judgment behind them — the exception, the adjusting entry, the reviewer's challenge and the sign-off. Client identities and account details are removed, and nothing is licensed without the client's written authorization.

Typical data

  • Reconciliation exceptions
  • Adjusting entries & rationale
  • Audit workpapers
  • Review notes & clearance
  • Tax position memos
  • Prior-period corrections
  • Month-end close timings
  • Budget vs actual commentary

Representative workflow

Illustrative

  1. 01Source records
  2. 02Reconciliation
  3. 03Exception
  4. 04Accountant's adjustment
  5. 05Reviewer note
  6. 06Cleared & signed off
  7. 07Final reported figure

Who typically holds it

  • Accounting and audit firms
  • Tax advisory practices
  • Corporate finance and controlling teams
  • Outsourced bookkeeping providers

Potential AI applications

  • Reconciliation and close assistants
  • Audit sampling and anomaly detection
  • Tax research models
  • Financial reasoning evaluation sets

Which systems hold accounting and audit data?

The general ledger and the ERP hold the entries. Close and reconciliation tools hold the exceptions and who cleared them. Audit software holds workpapers, sampling and review notes. Tax software and research files hold positions and memos.

The valuable part is the link between these. An exception, the adjusting entry, the reviewer's challenge and the sign-off together form one worked example.

  • Reconciliation exceptions with the reason and the fix
  • Adjusting entries with the accountant's rationale
  • Audit workpapers with review notes and clearance
  • Tax position memos with the conclusion reached

What do AI teams build with accounting data?

Teams train close assistants that suggest the right adjustment for an exception. They train anomaly detection on samples an auditor flagged. They build evaluation sets from tax memos, where a qualified person has already reached a conclusion.

Records with a reviewer's sign-off show what a correct answer looks like. That is hard to find anywhere else.

Close timings are useful too. Records of which tasks ran late, and why, help teams build tools that plan the month-end.

What about client confidentiality and audit independence?

Accountants owe their clients confidentiality. Professional codes, such as the AICPA's confidential client information rule in the US, bar disclosure without client consent. Tax preparers face an extra rule: Section 7216 of the US tax code bars using or sharing tax return information without the taxpayer's consent. So each client must authorize in writing, and client identities and account details are removed.

Audit firms have one more check. A licensing deal must not create a business relationship that impairs independence, for example if the AI company is an audit client. Your independence team should confirm this before work starts. This is not legal or ethics advice; your own advisers decide.

How does a firm prepare a first description?

A short description is enough for a first review. No client files are needed.

  • Service lines covered: bookkeeping, audit, tax or advisory
  • Which systems hold the records and over which years
  • Whether engagement letters already address data reuse
  • Any independence constraints you already know about

Example record (illustrative)

Illustrative record: a fictional, de-identified month-end exception. Not a real client.
FieldWhat it holds
Account classAccrued expenses, operating company
ExceptionSupplier invoice booked twice across two periods
Adjusting entryReversal of the duplicate, with the accountant's rationale
Reviewer noteManager asks for the supplier statement; evidence attached
StatusCleared and signed off before the close deadline
RedactionsClient, supplier and bank details replaced with tokens

Frequently asked questions

Can an accounting firm license client data?

Only with each client's written authorization and after client identities and account details are removed. Tax return information needs the taxpayer's consent under US rules.

Does licensing affect audit independence?

It can if the deal creates a business relationship with an audit client. Your independence team checks this before any work starts.

Are financial statements useful on their own?

Less so. Published statements are often public. The value is in the working papers: the exception, the adjustment, the review and the sign-off.

Which firms hold this kind of data?

Audit and accounting firms, tax practices, outsourced bookkeeping providers and corporate finance teams with long close histories.

Is there a cost to the firm?

No. There is no fee to the data owner. Compensation comes from the licence with the AI company.

What happens after we send a description?

We reply within 24 hours. If there is a fit, we work through client consent and confidentiality with you, then help prepare a documented, de-identified dataset.

Trust & compliance

Data licensing without losing control.

Your data stays yours until you decide otherwise. We assess before anything is shared, and we treat rights and privacy as conditions of a transaction — not afterthoughts.

No raw data for an initial evaluation

Nothing moves without authorization

Ownership is not the same as licensing rights

Specialist review where it is needed

Scoped records, never bulk exports

How we handle rights, privacy and confidentiality

Own valuable data?

Check your data's licensing potential.

A confidential, no-raw-data assessment of your company's records — from lab results and production logs to cases, claims and transactions.

Building AI?

You specify it. We source it.

Tell us the proprietary data your model needs — domain, structure, formats and rights. We approach the organizations that produce it.