Data models
The API reference shows you the endpoints; this section shows you the data — each model the platform can return, laid out flat so you never have to click through nested objects one by one to understand a payload.
Which product returns what
Each family on these pages is what a feature returns: ask an engine for accounts_read and the banking models are what comes back. The same models reach your systems whichever product you integrate with, and each product has its own overview of the ones it returns and of how they arrive:
How to read these pages
Each page covers one result: a short introduction — what the data is, where it comes from, what to use it for — followed by the model itself and its nested objects, each one flattened into its own expandable tree. The trees are rendered directly from the live API specification, so they can never drift from what the API actually returns.
Two family maps
Results are grouped by family, and there are two maps depending on what kind of source was read. Each page in this section covers one family, and opens by stating the exact path its data lives at.
Banks, card issuers and consumer finance
Accounts, cards, deposits, loans, investments and direct debits, under one object:
Public administrations
The keys you address in your code — data.customer.profile, data.employment.labor_check, data.driver.vehicles…
Driver & vehicles family
In both
The flows’ session envelope
In both flows, the family map travels as data inside the session results — the same object their webhooks deliver:
What the session has to say about itself and about the data it read, oldest first.
Most sessions say nothing and the list is empty. When it is not, each entry is a situation that
was detected while the session ran: an error or a warning about a read, an info note, or a
flag — the type raised for you. A flag never means something of ours failed; it means the
session found something worth a decision on your side, and location points at the part of this
document it is about.
A situation is reported ONCE however many times it occurred, so this list is a set of facts and
not a log: automate on message_id, which is stable, and treat message as text for a person.