Using machine learning to predict performance of secure documents

A system, comprising:

• at least one processing circuitry;
• and
• at least one non-transitory storage media storing instructions, that when executed by the at least one processing circuitry, cause the at least processing circuitry to:
• detect a transmission of a request from a requesting computing device to a recipient computing device to perform one or more tasks associated with a secure document;
• identify, based on the request in the detected transmission, one or more machine learned models in a plurality of machine learned models, the one or more machine learned models have been trained on one or more features of one or more historical secure documents and task completion data associated with the one or more historical secure documents, and determine, using the identified one or more machine learned models, one or more probabilities associated with a failure of the recipient computing device to complete performance of one or more tasks associated with the secure document, wherein the determined one or more probabilities are indicative of a failure to complete performance of the one or more tasks based on at least one of the following:
• a type of task in the one or more tasks, a time of transmission of the request, a time associated with performance of at least one task in the one or more tasks, and any combination thereof;
• generate, based on the determined one or more probabilities, one or more feature modification recommendations, each feature modification recommendation in the one or more feature modification recommendations being associated with a value of probability indicative of an improved likelihood of a successful completion of performance of the one or more tasks by the recipient computing device, wherein generation of the one or more feature modification recommendations includes:
• comparing each value of probability to one or more threshold values of probability;
• and
• selecting, based on the comparing, at least one feature modification recommendation associated with a value of probability exceeding the one or more threshold values of probability for presentation of the at least one feature modification recommendation on a graphical user interface of the requesting computing device;
• and
• present the generated one or more feature modification recommendations and associated respective values of probability on the graphical user interface of the requesting computing device.

A computer program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processing circuitry, cause the at least one programmable processing circuitry to:

• detect a transmission of a request from a requesting computing device to a recipient computing device to perform one or more tasks associated with a secure document;
• identify, based on the request in the detected transmission, one or more machine learned models in a plurality of machine learned models, the one or more machine learned models have been trained on one or more features of one or more historical secure documents and task completion data associated with the one or more historical secure documents, and determine, using the identified one or more machine learned models, one or more probabilities associated with a failure of the recipient computing device to complete performance of the one or more tasks, wherein the determined one or more probabilities are indicative of a failure to complete performance of the one or more tasks based on at least one of the following:
• a type of task in the one or more tasks, a time of transmission of the request, a time associated with performance of at least one task in the one or more tasks, and any combination thereof;
• generate, based on the determined one or more probabilities, one or more feature modification recommendations, each feature modification recommendation in the one or more feature modification recommendations being associated with a value of probability indicative of an improved likelihood of a successful completion of performance of the one or more tasks by the recipient computing device;
• and
• present the generated one or more feature modification recommendations and associated respective values of probability on a graphical user interface of the requesting computing device.