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: 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: 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: The systems and methods that validate data are provided. The systems and methods include a validation module which is a single solution for validating data in multiple services. The validation module is incorporated into a service. The validation module is provided with a configuration file that includes a test case identifier and with test case data that corresponds to the test case identifier. The validation module hijacks a request that is processed by a service and identifies a data element in the request that corresponds to the test case identifier in the configuration file. The validation module then validates data in the request against test case data that corresponds to the test case identifier.

Abstract: A user can select one or more friendly funding sources to make a payment. The friendly funding sources are pre-approved by a “friend” of the user and have restrictions for use. When the user desires to make a payment, the user sees one or more friendly funding sources and can choose any combination of friendly funding sources and conventional funding sources for making the payment.

Abstract: A user can select one or more friendly funding sources to make a payment. The friendly funding sources are pre-approved by a “friend” of the user and have restrictions for use. When the user desires to make a payment, the user sees one or more friendly funding sources and can choose any combination of friendly funding sources and conventional funding sources for making the payment.

Abstract: A user can select one or more friendly funding sources to make a payment. The friendly funding sources are pre-approved by a “friend” of the user and have restrictions for use. When the user desires to make a payment, the user sees one or more friendly funding sources and can choose any combination of friendly funding sources and conventional funding sources for making the payment.