Abstract: Systems and processes for automatically configuring user authentication rules for each of a plurality of users for use in transactions. A neural network engine receives first party preferences data from a first party computer that includes user authentication requirement criteria associated with a plurality of transaction types, and receives at least two of user behavior data, user historical data, authenticator data associated with a mobile device of the user, and mobile device metadata. The neural network engine then generates an output value based on this data, transmits the output value to a score comparator for comparison to a required score specified by the first party, and receives feedback data from the score comparator when the output value is not within a tolerance of the required score. When the output value is within the tolerance, then the neural network engine generates user authentication rules recommendations and transmits them to the first party computer.

Abstract: Systems and processes for automatically configuring user authentication rules for each of a plurality of users for use in transactions. A neural network engine receives first party preferences data from a first party computer that includes user authentication requirement criteria associated with a plurality of transaction types, and receives at least two of user behavior data, user historical data, authenticator data associated with a mobile device of the user, and mobile device metadata. The neural network engine then generates an output value based on this data, transmits the output value to a score comparator for comparison to a required score specified by the first party, and receives feedback data from the score comparator when the output value is not within a tolerance of the required score. When the output value is within the tolerance, then the neural network engine generates user authentication rules recommendations and transmits them to the first party computer.