US 12,367,524 B2
Settings optimization engine using artificial intelligence to enhance client privacy
Crystal M. Sundaramoorthy, Charlotte, NC (US); Elena Kvochko, New York, NY (US); Albena N. Fairchild, Spruce Pine, NC (US); and Jinna Kim, Charlotte, NC (US)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Jul. 27, 2023, as Appl. No. 18/226,908.
Application 18/226,908 is a continuation of application No. 16/897,394, filed on Jun. 10, 2020, granted, now 11,756,112.
Prior Publication US 2023/0368286 A1, Nov. 16, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 40/02 (2023.01); G06F 21/62 (2013.01); G06N 20/00 (2019.01); G06Q 50/26 (2024.01)
CPC G06Q 40/02 (2013.01) [G06F 21/6245 (2013.01); G06N 20/00 (2019.01); G06Q 50/265 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computing platform, comprising:
at least one processor;
a communication interface communicatively coupled to the at least one processor; and
memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:
identify, by inputting enterprise account data and third party source data for a first individual into a settings optimization model, a subset of a plurality of individuals having common characteristics with the first individual;
identify, using the settings optimization model, one or more discrepancies between initial account settings for the first individual and account settings for the subset of the plurality of individuals, wherein the account settings for the subset of the plurality of individuals are included in the enterprise account data for the plurality of individuals, wherein the setting optimization model is further configured to identify investment recommendations, based on an identified risk tolerance for the first individual, and wherein identifying the investment recommendations comprises:
identifying that the first individual has applied maximum privacy settings to an account,
identifying, based on the maximum privacy settings, that the first individual is risk averse, and
generating a recommendation to shift from a higher risk investment to a lower risk investment;
identify, based on the one or more discrepancies between the initial account settings for the first individual and the account settings for the subset of the plurality of individuals, one or more account settings modifications for the first individual;
monitor an event processing system to detect an interaction by the first individual;
based on the detected interaction, compare account settings corresponding to the detected interaction to the one or more account settings modifications, wherein the comparison of the account settings corresponding to the detected interaction to the one or more account settings modifications results in a determination that a first modification of the one or more account settings modifications applies to the account settings corresponding to the detected interaction; and
send one or more commands directing an enterprise data source to modify the initial account settings based on the first modification, wherein sending the one or more commands directing the enterprise data source to modify the initial account settings based on the first modification causes the enterprise data source to modify the initial account settings based on the first modification.