Graphical user interface providing entry manipulation

A system for managing transactions in an online credit card application, said system comprising:

• a back-end server operating the online application and including:
• at least one processor employing a machine learning model for processing data and information;
• a communications interface communicatively coupled to the at least one processor;
• and
• a memory device storing data and executable code that, when executed, causes the at least one processor to:
• link one or more external bank accounts to the online application;
• provide a list of transactions that were made using the credit card;
• enable a user to select one or more of the transactions in the list to be paid independent of the other transactions;
• and
• enable the user to pay the selected transactions using the one or more external bank accounts, wherein the machine learning model is trained using unsupervised or semi-supervised training where none of the outputs or some of the outputs of the model are unknown, and wherein the machine learning model is further trained by comparing a generated output produced by the model in response to training data with a desired or correct output to generate an error that is communicated back through the model.

A method for managing transactions in an online credit card application, said method comprising:

• providing a back-end server operating the online application and including:
• at least one processor employing a machine learning model for processing data and information;
• a communications interface communicatively coupled to the at least one processor;
• and
• a memory device storing data and executable code, said method causing the at least one processor to:
• link one or more external bank accounts to the online application;
• provide a list of transactions that were made using the credit card;
• enable a user to select one or more of the transactions in the list to be paid independent of the other transactions;
• and
• enable the user to pay the selected transactions using the one or more external bank accounts, wherein the machine learning model is trained using unsupervised or semi-supervised training where none of the outputs or some of the outputs of the model are unknown, and wherein the machine learning model is further trained by comparing a generated output produced by the model in response to training data with a desired or correct output to generate an error that is communicated back through the model.