Banking Data

D•One gains access to user bank data directly from the banks, and financial institutions. This data is categorised and insights are produced to make it easy for credit providers to make use of the data.

Accounts

Accounts data corresponds to a distinct financial product belonging to a user. A user is able to choose which accounts to connect. This could be one bank account or many bank accounts. A schema and other information relating to accounts data can be found within the API reference page.

Transactions

Transactions represent a movement of funds either into or out of an account. Transactions are always associated with an account. If the applicant has never made any transactions, or the last transaction falls outside of the time window of the API call there might be no transactions. A schema and other information relating to transaction data can be found within the API reference page.

Categorisation

Every transaction is passed through our categorisation service where a merchant category and a purpose category are appended. The purpose categorises are organised into broad, concise and detailed categories. Broad categories are high-level category, concise are second level categories, and detailed are the most granular level. More details can be viewed in the tags object on the transactions API reference page.

Multiple versions of categorisation are maintained in production at the same time. Each partner is assigned a default categorisation version which is normally the most up to date version when the partner initially integrate with D•One. It is possible to pull transaction data for different versions using a query param on the transaction endpoint.

Running multiple versions of categorisation in production allows D•One to improve and update the categorisation version without forcing partners to upgrade to a new version.

Periodicity

Periodicity is a series of additional data fields which are appended to any transactions which re-occur. When periodic transactions are identified a mean amount is returned, along with the mean date difference (number of days between transactions). A variance score relating to both the amount, and the mean date difference is also provided. The amount variation can be used to show how consistent a payment amount is, and the time variation can be used to show how consistent the frequency is. This can be used to identify salary, rent payments, and other periodic transactions that may be relevant to credit decisions. Specifics can be viewed under the seriesMetadata object on the transactions API reference page.