create_score
Create a score from labeled examples. Ask the user whether to use their data or generated sample data.
Creates a score, as POST /v1/scores. Up to 100 per organization per day.
| Input | Description |
|---|---|
data | Required. The examples: a JSON array of objects, or CSV text with a header row, each row with is_bad |
description | Optional. What the decision is and what is_bad means |
api_key | /mcp/keys only, if the client doesn't send the key as a header |
Returns model_id, job_id and request_id. Creating takes about 5 to 10 minutes: poll get_job_status, then call score with the model_id.
Before calling it
Ask the user whether to use data they already have or have you generate sample data. A score built on generated data is only for trying Finic out: it isn't calibrated to the company's real fraud distribution.
Good example data is:
- JSON records about customer identity or events: sign-ups, logins, payments, transactions.
- One row per past decision, with its real outcome as
is_bad(truewhen bad). - Only fields known at the time of the decision: no later chargebacks, fraud flags or verdicts.
- Consistent: the same field names and types in every row, in words, with units.
- Enough: 100+ rows with 20+ of each outcome, under 2 MB. Up to 2,000 rows are used.
The records you'll score later must have the same shape. See Example data.