Interactive transaction tracker

A system, comprising:

• a memory;
• and
• at least one processor coupled to the memory and configured to:
• activate, based on receiving a user request to initiate a remote deposit from a remote deposit application, an interactive user interface (UI), wherein the interactive UI provides at least a status of the remote deposit;
• predict, by a first trained machine learning model, an occurrence of a remote deposit matter preventing advancement of the remote deposit process;
• predict, by a second trained machine learning model, one or more remote deposit remediation tasks to overcome the remote deposit matter;
• modify a weighting of metadata during training of the second trained machine learning model to trend towards greater success, wherein the greater success is recognized by an advancement or completion of the remote deposit process, and wherein the metadata includes any of:
• a time to complete a task, a time to complete the one or more remediation tasks, a time for advancing the remote deposit process after encountering a matter, or a total time to complete the remote deposit process;
• display, on the interactive UI, the one or more remote deposit remediation tasks;
• and
• advance, based on the user completing the one or more remote deposit remediation tasks, the remote deposit process;
• and
• wherein the metadata further includes a user acceptance or denial, through the interactive UI, of the completion of the remote deposit process.

A non-transitory computer-readable device having instructions stored thereon that, when executed by at least one computing device, causes the at least one computing device to perform operations comprising:

• activating a remote deposit application;
• activating, based on receiving a user request to initiate a remote deposit from the remote deposit application, an interactive user interface (UI), wherein the interactive UI provides at least a status of the remote deposit;
• predicting, by a first trained machine learning model, an occurrence of a remote deposit matter preventing advancement of the remote deposit process;
• predicting, by a second trained machine learning model, one or more remote deposit remediation tasks to overcome the remote deposit matter;
• modifying a weighting of metadata during training of the second trained machine learning model to trend towards greater success, wherein the greater success is recognized by an advancement or completion of the remote deposit process, and wherein the metadata includes any of:
• a time to complete a task, a time to complete the one or more remediation tasks, a time for advancing the remote deposit process after encountering a matter, or a total time to complete the remote deposit process;
• displaying, on the interactive UI, the one or more remote deposit remediation tasks;
• and
• advancing, based on the user completing the one or more remote deposit remediation tasks, the remote deposit process;
• and
• wherein the metadata further includes a user acceptance or denial, through the interactive UI, of the completion of the remote deposit process.