A False positive refers to a legitimate transaction or user activity that is mistakenly flagged as fraudulent. Security or fraud detection systems that report excessive false positives can disrupt the customer experience, delay important transactions, and strain operational resources because of the amount of manual effort required to resolve them and reauthorize the flagged activities. While false positives will occur with every risk management system, their reduction is a key goal for internal fraud teams as well as CX leaders.
Use case/ examples of false positive
Spending false positives: Flagging legitimate customer activity as suspicious, for example, if purchases are made in an atypical category, foreign location, or unusually large amount, because a customer is traveling.
Location false positives: Blocking a legitimate user from logging in due to an unfamiliar IP address or the use of a new device, despite no otherwise malicious activity.
Credit invisible false positives: Interrupting onboarding for users who have thin credit files and forcing a manual review even in the absence of red flags.
