US 11,941,234 B1
Graphical user interface allowing entry manipulation
Alexis Pastore, Charlotte, NC (US)
Assigned to TRUIST BANK, Charlotte, NC (US)
Filed by Truist Bank, Charlotte, NC (US)
Filed on Jan. 18, 2023, as Appl. No. 18/155,826.
Application 18/155,826 is a continuation of application No. 18/060,717, filed on Dec. 1, 2022.
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 3/0484 (2022.01); G06F 3/0482 (2013.01); G06F 18/21 (2023.01); G06F 18/2321 (2023.01); G06F 18/2413 (2023.01); G06F 18/243 (2023.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06Q 20/24 (2012.01); G06Q 40/03 (2023.01)
CPC G06F 3/0484 (2013.01) [G06F 3/0482 (2013.01); G06Q 20/24 (2013.01); G06Q 40/03 (2023.01); G06F 18/217 (2023.01); G06F 18/2321 (2023.01); G06F 18/24143 (2023.01); G06F 18/24323 (2023.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01)] 19 Claims
OG exemplary drawing
 
1. A system for displaying a graphical user interface allowing entry manipulation, said system comprising:
a back-end server operating an 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 accounts to the online application;
provide a list of entries associated with a specified instrument;
enable a user to select one or more of the entries in the list to be satisfied independent of the other entries; and
enable the user to satisfy the selected entries using the one or more external accounts; said method further comprising:
training the machine learning model by clustering algorithms using unsupervised learning clustering of data such as external accounts to the online application;
performing a cluster model to group external accounts to online application points based on similarities using unlabeled data;
acquiring receiving data, such as user select transactions in the list to be satisfied; and
entering termed data ingestion, wherein when versioning incoming data, if new data is subsequently collected and entered, a new model will be generated and preprocessing will be updated.