PRACTICAL RESOURCE
How to prepare a financial workflow data sample for AI
Start with one task a reviewer can verify.
Start with one task a reviewer can verify. A credit union can separate a member posting from a control total. A loan broker can match a revised disclosure to an approval. A claims adjuster can link an observation to the right estimate. A synthetic example can show the process before anyone discusses release of real records.
What the public programs establish
- Scale AI names financial services and insurance brokerage in its Data Partnerships materials and describes scoped package review. Ask which role, workflow and outcome it is seeking and what evidence would be sufficient. Scale Data Partnerships
- Troveo publishes a guide for financial firms that discusses financial models, research memos and portfolio reports. It describes provider-reported buyer interest and exclusions. Confirm actual terms, acceptance criteria and payment in writing for your own example. Troveo financial data guide
- Appen describes sample approval, anonymization and operational workflows spanning systems. Ask how an example preserves the reason for a decision without exposing identities or rights-restricted material. Appen enterprise data
These are public offers and statements about demand. A program description alone cannot tell you whether a particular file will be accepted, licensed or paid for. The occupation-based tasks in OpenAI’s GDPval provide evidence of evaluation design, a separate signal from procurement. OpenAI GDPval
Build three examples around the same question
For a reconciliation exercise, use an independently written mock ledger with an original event and a verified adjustment. Write a second case with a similarly numbered unrelated record. In the third case, remove the cross-reference so that the correct answer is to request more evidence. Specify which decision the reviewer makes and which documents the model can see. Give the reviewer a separate answer key.
| Field | Record it before any handoff |
|---|---|
| Evidence source | Who created each record, who can authorize reuse, and where the relevant version is held |
| Restrictions | Customer records, market feeds, vendor data, confidential terms, health information, and anything outside the approved task |
| Expected output | An evidence summary, a record association, or a documented request for missing proof |
| Human decision | Who reviews the output and retains authority for transactions, coverage or other consequential decisions |
Removing names may leave transaction or health data identifiable. Confirm each party’s authority and the obligations applicable to the proposed use with qualified reviewers before any actual transfer. The FTC’s financial privacy materials and HHS’s de-identification guidance cover different regulated contexts. FTC financial privacy resources · HHS de-identification guidance
Explore credit union reconciliation, loan broker document review and claims adjuster evidence. Describe a synthetic workflow to Fiund
An original reconciliation with an unmatched adjustment
Use invented demonstration units. Event E-12 records 80 units, adjustment A-12 removes 5 units and explicitly references E-12, and a control sheet records 75 for that pair. A separate adjustment A-21 refers to E-21. Ask which supplied records support the 75-unit result and whether A-21 belongs in it.
The reference uses E-12 and its linked A-12. A-21 cannot be included merely because its number looks similar. In a second case, remove A-12’s event reference: the answer must identify the missing association rather than assume it. Keep measure, period, unit and source link with each figure. The exercise tests administrative evidence matching and performs no real transaction, financial assessment or filing.