Realtime risk check for credit/debit card authorization requests (for card issuers)
Please refer to API Authentication for API URL and authentication.
This API endpoint can be used for real-time transaction approval decisions.
Note you must call /v1/customers API at least once prior to calling this API with customer information so Sardine can pre-compute customer-level risk information and can correlate the cardId
(/v1/issuing/risks) to the transaction.paymentMethod.card.hash
(/v1/customers) that is sent in this API request.
Sardine automatically sets issuingrisk
as the checkpoint for this API endpoint. You can review the rules applied under the issuingrisk
checkpoint in Sardine Dashboard.
Authorizations
Basic authentication header of the form Basic <encoded-value>
, where <encoded-value>
is the base64-encoded string username:password
.
Body
unique identifier for the given customer session on your platform, generated by your service. We expect it to be short-lived (e.g. expires after 30 min)
Id of customer. Please use the same value you sent to v1/customers API
ID of the partner/business/merchant this event is tied to
Name of the partner/business/merchant this event is tied to
Name of the checkpoints to be invoked. Defaults to issuingrisk
if omitted.
You can pass custom checkpoint names after they are created. Please discuss with Sardine.
Example: ["issuingrisk"]
Key-value pair for string type custom fields to be made available in the dashboard and rule editor. Example: ”customerSegment”:”premium”
Key-value pair for boolean type custom fields to be made available in the dashboard and rule editor.
Example: ”verifiedCustomer": true
Key-value pair for number type custom fields to be made available in the dashboard and rule editor.
Example: ”internalRiskScore": 57
Information about the purchase verification message sent to the cardholder and channel.
Response
Status of the API response
Unique identifier for the given customer session as provided by you in the API request payload
Risk level like very_high, high, medium and low
AML risk level like high, medium and low.
ML Risk Score for this particular transaction. The ML model used to predict the score is trained on various features and can be used once sufficient data and feedback have been provided.
List of live and shadow rules that triggered for this session
Result of rule evaluations for each checkpoint. issuingrisk
checkpoint is executed by default.
List of reason codes returned for this session (it is omitted if empty). Example: ALWR