Signals gathering attributes associated with the phone number - including line type, telecom carrier, the status of the phone, geographic location, velocity and country-of-origin to run through our machine learning models.
Checking the phone number with the database of customer-contributed reputation information enables us to identify known cases of the number that have been associated with fraud to improve results.
Once the above steps are complete (in a matter of milliseconds), Signals returns a risk assessment back to the web or mobile application. The score ranges from 0 to 100 and helps inform the decision to block, check or allow the related transaction.
HOW IT WORKS
Every time you or your clients send cash, arranging delivery, transferring sensitive information, or giving access to personal data to a counterparty that could be identified solely by a mobile phone number, there is a chance that the transaction might be compromised intentionally or not.
The most common types of fraudulent activities to be identified are identity theft, chargeback and return fraud, advanced fee and money transfer scams. Cybercriminals may also exploit different attack types such as social engineering, device attacks and communication channel attacks to impersonate a decent counterparty.
Signals identify normal and abnormal patterns in the mobile number behaviour and its context, as well as their historical changes and advise you on the most logical action to take.
100 FREE requests $0.05 per consequent request Number normalisation included Carrier and phone type info Country-of-origin check Email support