Last updated: 16 July 2026 | Change log
Using the instruction.fraud object and setting the type value to fraudSight enables a risk assessment to run as part of the payment request.
Card payment with FraudSight enabled that results in a highRisk assessment outcome that stops the payment.
"fraud": {
"type": "fraudSight"
}Enable a FraudSight risk assessment
Perform the Fraud assessment but do not act on the outcome. Normally used for the initial launch while the data model is maturing.
Device fingerprint provided by Threatmetrix.
As well as core payment details such as the cardNumber, billingAddress and any settings in the instruction.fraud object, the following key:values are used as part of the risk assessment. By providing these, it means more data points and a slight increase in spotting potential fraud.
instruction.customer | firstName, lastName, email, phone, dateOfBirth, customerId, ipAddress | |
instruction.shipping | firstName, lastName, address |
Setting instruction.fraud.silentMode to true allows an assessment to be run but the outcome (highRisk) is not stopping the transaction. This is primarily used when first going live and a certain amount of real data is required to mature the data model and make the assessments more accurate. Normally a few weeks is enough but this varies with the number of transactions sent.
To provide even more data points for an assessment, you can run the Ravelin SDK on your customer's browser or device. This creates a fingerprint of a customer, based on data like ipAddress and browser details, and performs a GeoIP lookup for a rough idea of the location.
The deviceId representing this fingerprint is provided in instruction.fraud.deviceData.collectionReference.
The ThreatMetrix SDK is being phased out, instructions have been updated to use the Ravelin SDK. See the archived ThreatMetrix guide for details on the previous SDK.
If the fraud assessment score is high enough, a highRisk response is sent and the transaction will not continue.
{
"outcome": "fraudHighRisk",
"transactionReference": "2847f678-fd97-4558-b913-8945c8b11dc9",
"score": 97.0,
"reason": [
"Recent unexpected card activity"
]
}Unless flagged as fraudHighRisk, the final payment response includes basic details of what happened during the risk assessment.
...
"fraud": {
"outcome": "lowRisk",
"score": 44.0
}
...You can use the fraud outcome to conditionally skip 3DS. Set threeDS.bypassOn to fraudLowRisk and/or fraudReview in your request to bypass 3DS when those outcomes are returned.
outcome of the fraud assessment. highRisk outcomes stop the transaction before payment.
The score calculated by the fraud assessment. Set score thresholds to define lowRisk, highRisk and review outcomes
Next steps
- Testing (FraudSight tab) for scenario details and magic test values