![]() ![]() The higher the LOA the more likely the user is who they claim to be. The LOA score is a number between 0.0 to 4.0. A custom Risk Analyzer module can be implemented by the Acceptto team that can communicate with any external resources.An external risk engine can call the generic score API to provide the score for the users.Calling an external API to fetch the score for a given user and context.The Risk Analyzers are designed to be modular and there are multiple ways of integrating new risk analyzers: The location will be obtained from the phone or browser and if not provided, falls back to the IP-based location. Location Risk Analyzer: Provides a score based on the user's obtained location.IP Risk Analyzer: Provides a score based on the user's IP address.DBFP Risk Analyzer: Provides a score based on the user's browser fingerprint.Auth Method Risk Analyzer: Provides a score based on the authenticator used for the last MFA.AIML Risk Analyzer: Provides a score based on the user contextual information provided to Acceptto's AI/ML engine.This is a noninclusive list of built-in Risk Analyzers: For example, the IP Risk Analyzer gets some information about the IP address of the user and generates a score based on that address. Each Risk Analyzer focuses on a specific area and gets a specific kind of data. Risk Analyzers are responsible for fetching data from different sources and calculating a final score based on the collected information. LOA will be used by the smart MFA module to decide whether to increase or decrease the friction for the user.ĮGuardian's Risk Engine comes with an out of the box integration with the Policy Engine. EGuardian's Risk Engine is responsible for calculating the level of assurance (LOA) for each transaction.
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