System and methods for managing graphical user interfaces for one or more automated teller machines
Disclosed embodiments may include a system that may receive an indication that a user is accessing an ATM, receive, from the ATM, average session duration data over a predetermined period, generate, using a machine learning model, a busyness score for the ATM based on the average session duration data over the predetermined period, and determine whether the busyness score for the ATM exceeds a busyness score threshold. When the busyness score for the ATM does not exceed the busyness score threshold, the system may cause the ATM to present, via a first graphical user interface, a default ATM experience. When the busyness score for the ATM exceeds the busyness score threshold, the system may cause the ATM to present via, a second graphical user interface, a busy ATM experience.
1 . An automated teller machine (ATM), comprising:
one or more processors; and
memory in communication with the one or more processors and storing instructions that are configured to cause the ATM to:
generate a busyness score over a predetermined period;
determine whether the busyness score exceeds a busyness score threshold;
when the busyness score does not exceed the busyness score threshold:
cause the ATM to present, via a first graphical user interface, a custom cash withdrawal option;
dispense an amount of cash corresponding to the custom cash withdrawal option; and
when the busyness score exceeds the busyness score threshold:
cause the ATM to present, via a second graphical user interface, one or more predefined cash withdrawal options; and
dispense an amount of cash corresponding to the one or more predefined cash withdrawal options.
2 . The ATM of claim 1 , wherein the instructions when executed by the one or more processors are further configured to cause the ATM to present the custom cash withdrawal option before the one or more predefined cash withdrawal options when the busyness score for the ATM does not exceed the busyness score threshold.
3 . The ATM of claim 2 , wherein the instructions when executed by the one or more processors are further configured to cause the ATM to present the one or more predefined cash withdrawal options before the custom cash withdrawal option when the busyness score for the ATM exceeds the busyness score threshold.
4 . The ATM of claim 1 , wherein the instructions when executed by the one or more processors are further configured to cause the ATM to present one or more first requests for each individual check total being deposited when the busyness score for the ATM does not exceed the busyness score threshold.
5 . The ATM of claim 4 , wherein the instructions when executed by the one or more processors are further configured to cause the ATM to present only a second request for a total value of all checks being deposited when the busyness score for the ATM exceeds the busyness score threshold.
6 . The ATM of claim 1 , wherein the instructions when executed by the one or more processors are further configured to cause the ATM to present, via the second graphical user interface, an option to authenticate a user using a mobile device or a quick response (QR) code to allow the user to pre-stage a transaction using the mobile device when the busyness score for the ATM exceeds the busyness score threshold.
7 . The ATM of claim 1 , wherein the busyness score is generated by a machine learning model, and the machine learning model comprises a neural network.
8 . An automated teller machine (ATM) comprising:
one or more processors; and
memory in communication with the one or more processors and storing instructions that are configured to cause the ATM to:
generate a busyness score over a predetermined period;
determine whether the busyness score exceeds a first busyness score threshold;
determine whether the busyness score exceeds a second busyness score threshold;
when the busyness score does not exceed the first busyness score threshold, cause the ATM to present, via a first graphical user interface, a default ATM experience;
when the busyness score exceeds the first busyness score threshold but does not exceed the second busyness score threshold, cause the ATM to present, via a second graphical user interface, a hybrid ATM experience;
when the busyness score exceeds the second busyness score threshold, cause the ATM to present via, a third graphical user interface, a busy ATM experience; and
dispense an amount of cash corresponding to a selection of a custom cash withdrawal or one or more predefined cash withdrawals on the first, second, or third graphical user interfaces.
9 . The ATM of claim 8 , wherein causing the ATM to present the default ATM experience comprises causing the ATM to present, via the first graphical user interface, an advertisement, educational content, or both to a user, and a custom cash withdrawal option presented before one or more predefined cash withdrawal options.
10 . The ATM of claim 9 , wherein:
causing the ATM to present the hybrid ATM experience comprises causing the ATM to present the custom cash withdrawal option before one or more predefined cash withdrawal options without presenting the advertisement or the educational content, and
causing the ATM to present the busy ATM experience comprises causing the ATM to omit the advertisement or the educational content.
11 . An automated teller machine (ATM), comprising:
one or more processors; and
memory in communication with the one or more processors and storing instructions that are configured to cause the ATM to:
generate a busyness score over a predetermined period;
determine whether the busyness score exceeds a busyness score threshold;
when the busyness score does not exceed the busyness score threshold, cause the ATM to present, via a first graphical user interface, a default ATM experience;
when the busyness score exceeds the busyness score threshold, cause the ATM to present via, a second graphical user interface, a busy ATM experience; and
dispense an amount of cash corresponding to a custom cash withdrawal or one or more predefined cash withdrawals based on input to the first or second graphical user interfaces.
12 . The ATM of claim 11 , wherein causing the ATM to present the default ATM experience comprises causing the ATM to present, via the first graphical user interface, an advertisement, educational content, or both to a user, and a custom cash withdrawal option.
13 . The ATM of claim 12 , wherein causing the ATM to present the advertisement or educational content to the user occurs prior to presenting the user with options for conducting a transaction.
14 . The ATM of claim 12 , wherein the busy ATM experience omits the advertisement, educational content, or both.
15 . The ATM of claim 11 , wherein causing the ATM to present the default ATM experience comprises causing the ATM to present, via the first graphical user interface, a custom cash withdrawal option before one or more predefined cash withdrawal options.
16 . The ATM of claim 15 , wherein causing the ATM to present the busy ATM experience comprises causing the ATM to present, via the second graphical user interface, the one or more predefined cash withdrawal options before the custom cash withdrawal option.
17 . The ATM of claim 11 , wherein causing the ATM to present the default ATM experience comprises causing the ATM to present, via the first graphical user interface, one or more first requests for each individual check total being deposited.
18 . The ATM of claim 17 , wherein causing the ATM to present the busy ATM experience comprises causing the ATM to present, via the second graphical user interface, only a second request for a total value of all checks being deposited.
19 . The ATM of claim 11 , wherein causing the ATM to present the busy ATM experience comprises causing the ATM to present, via the second graphical user interface, a quick response (QR) code to allow the user to pre-stage a transaction using a mobile device or an option to authenticate via a mobile device.
20 . The ATM of claim 11 , wherein the busyness score is generated by a machine learning model, and the machine learning model comprises a neural network.