Fraud scores are calculated independently for each evaluation using the data provider’s proprietary risk model. As a result, the same person may receive different scores across applications or transactions when the submitted information or underlying risk signals differ.
Common reasons for score differences
Differences may result from changes in:
Phone number, including how often it has been associated with the individual, phone-number validation, or correlation.
Address information, such as ZIP code or city.
Other identity, device, behavioral, or transaction details included in the evaluation.
The different data available to the provider at the time each evaluation was processed.
Even small changes in submitted information can affect individual risk components and the overall fraud score.
How to investigate score variation
When comparing evaluations:
Compare the input fields submitted for each evaluation.
Review the individual risk components returned by the data provider.
Look for differences in phone validation, phone correlation, and address information.
Review the reason codes returned with each evaluation. Reason codes can help identify the specific factors or signals that contributed to the score.
Use Alloy’s Rule Explainability feature to review the underlying logic for a tag and what contributed to a given tag being set.
Important considerations
Different scores do not necessarily indicate an error. If the evaluations contained different inputs or were processed at different times, score variation may be expected.
If the same inputs produced materially different results, collect the relevant evaluation IDs, timestamps, request payloads, and responses before contacting Support. Do not include passwords, authentication codes, or other sensitive credentials.