Abstract: There are provided systems and methods for a machine learning-based network trained to perform risk assessment through device data. A service provider server receives device data of a user device associated with a merchant account registered with a merchant server for a merchant service, and receives, from the merchant server, a request containing a unique token identifier for initiating a risk assessment operation to generate a device assessment score for the user device, where the device assessment score indicates a level of risk between the user device and the merchant account. The service provider server selects a risk assessment engine to perform the risk assessment operation and generates the device assessment score and a narrative for the device assessment score, and sends, to the merchant server through an application programming interface, a message containing a unique device identifier for the user device, the device assessment score and the narrative.

Abstract: A method may include generating a user interface (UI) to facilitate interaction with a risk management system. The UI may include a first element indicating a rule used by the risk management system to manage risk for a client, a second element indicating effectiveness of the rule, and a third element invocable to modify the rule. The method may also include monitoring activity of the client to determine whether the activity of the client shifts the client into a different category of client; determining that the client is shifted into the different category; based on the shift, modifying the second element to include a recommended modification to the rule; and in response to receiving an interaction with the second element, applying the recommended modification to the rule.

Abstract: There are provided systems and methods for a machine learning-based network trained to perform risk assessment through device data. A service provider server receives device data of a user device associated with a merchant account registered with a merchant server for a merchant service, and receives, from the merchant server, a request containing a unique token identifier for initiating a risk assessment operation to generate a device assessment score for the user device, where the device assessment score indicates a level of risk between the user device and the merchant account. The service provider server selects a risk assessment engine to perform the risk assessment operation and generates the device assessment score and a narrative for the device assessment score, and sends, to the merchant server through an application programming interface, a message containing a unique device identifier for the user device, the device assessment score and the narrative.

Abstract: A method may include generating a user interface (UI) to facilitate interaction with a risk management system. The UI may include a first element indicating a rule used by the risk management system to manage risk for a client, a second element indicating effectiveness of the rule, and a third element invocable to modify the rule. The method may also include monitoring activity of the client to determine whether the activity of the client shifts the client into a different category of client; determining that the client is shifted into the different category; based on the shift, modifying the second element to include a recommended modification to the rule; and in response to receiving an interaction with the second element, applying the recommended modification to the rule.

Abstract: There are provided systems and methods for a machine learning-based network trained to perform risk assessment through device data. A service provider server receives device data of a user device associated with a merchant account registered with a merchant server for a merchant service, and receives, from the merchant server, a request containing a unique token identifier for initiating a risk assessment operation to generate a device assessment score for the user device, where the device assessment score indicates a level of risk between the user device and the merchant account. The service provider server selects a risk assessment engine to perform the risk assessment operation and generates the device assessment score and a narrative for the device assessment score, and sends, to the merchant server through an application programming interface, a message containing a unique device identifier for the user device, the device assessment score and the narrative.

Abstract: A method may include generating a user interface (UI) to facilitate interaction with a risk management system. The UI may include a first element indicating a rule used by the risk management system to manage risk for a client, a second element indicating effectiveness of the rule, and a third element invocable to modify the rule. The method may also include monitoring activity of the client to determine whether the activity of the client shifts the client into a different category of client; determining that the client is shifted into the different category; based on the shift, modifying the second element to include a recommended modification to the rule; and in response to receiving an interaction with the second element, applying the recommended modification to the rule.