Common Questions About Fraud & Risk Analytics.
How is the fraud model trained?
The model is trained on your historical transaction data, including known fraud cases, to identify patterns associated with fraudulent activity — validated against held-out data before deployment to estimate real-world accuracy.
What is device fingerprinting and why does it matter for fraud?
Device fingerprinting identifies characteristics of the device used for a transaction (without requiring invasive permissions), which can help flag suspicious patterns like the same device being used across many different user accounts.
What happens when the model flags a transaction?
Flagged transactions can be routed into a case management queue for risk team review, with the model's confidence score and contributing factors shown to help reviewers make faster decisions.
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