Class Reason (1.21.0)

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Reason(value)

Enum that represents potential reasons for annotating an assessment.

Enums
Name	Description
REASON_UNSPECIFIED	Default unspecified reason.
CHARGEBACK	Indicates that the transaction had a chargeback issued with no other details. When possible, specify the type by using CHARGEBACK_FRAUD or CHARGEBACK_DISPUTE instead.
CHARGEBACK_FRAUD	Indicates that the transaction had a chargeback issued related to an alleged unauthorized transaction from the cardholder's perspective (for example, the card number was stolen).
CHARGEBACK_DISPUTE	Indicates that the transaction had a chargeback issued related to the cardholder having provided their card details but allegedly not being satisfied with the purchase (for example, misrepresentation, attempted cancellation).
REFUND	Indicates that the completed payment transaction was refunded by the seller.
REFUND_FRAUD	Indicates that the completed payment transaction was determined to be fraudulent by the seller, and was cancelled and refunded as a result.
TRANSACTION_ACCEPTED	Indicates that the payment transaction was accepted, and the user was charged.
TRANSACTION_DECLINED	Indicates that the payment transaction was declined, for example due to invalid card details.
PAYMENT_HEURISTICS	Indicates the transaction associated with the assessment is suspected of being fraudulent based on the payment method, billing details, shipping address or other transaction information.
INITIATED_TWO_FACTOR	Indicates that the user was served a 2FA challenge. An old assessment with `ENUM_VALUES.INITIATED_TWO_FACTOR` reason that has not been overwritten with `PASSED_TWO_FACTOR` is treated as an abandoned 2FA flow. This is equivalent to `FAILED_TWO_FACTOR`.
PASSED_TWO_FACTOR	Indicates that the user passed a 2FA challenge.
FAILED_TWO_FACTOR	Indicates that the user failed a 2FA challenge.
CORRECT_PASSWORD	Indicates the user provided the correct password.
INCORRECT_PASSWORD	Indicates the user provided an incorrect password.
SOCIAL_SPAM	Indicates that the user sent unwanted and abusive messages to other users of the platform, such as spam, scams, phishing, or social engineering.