US 12,067,502 B1
Systems and methods for using machine learning for managing application incidents
Jennifer Ann Stave, Minneapolis, MN (US); Jiaju Liu, Phoenix, AZ (US); and Saara Raja, Waxhaw, NC (US)
Assigned to Wells Fargo Bank, N.A., San Francisco, CA (US)
Filed by Wells Fargo Bank, N.A., San Francisco, CA (US)
Filed on Jan. 16, 2023, as Appl. No. 18/154,962.
Application 18/154,962 is a continuation of application No. 16/824,175, filed on Mar. 19, 2020, granted, now 11,556,815.
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 5/04 (2023.01); G06F 16/2455 (2019.01); G06N 20/00 (2019.01)
CPC G06N 5/04 (2013.01) [G06F 16/2456 (2019.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving extracted data pertaining to a plurality of applications;
generating model-input data from the extracted data;
generating model-output data at least in part by processing the generated model-input data with a plurality of machine-learning models each independently trained to make one or more application-incident predictions, wherein the plurality of machine-learning models comprises a plurality of application-specific machine-learning models comprising:
a first machine-learning model that is trained using a training dataset specific to a first application and to a second application to make application-incident predictions with respect to the first application; and
a second machine-learning model that is trained using the training dataset to make application-incident predictions with respect to the second application different from the first application;
making, based at least in part on the model-output data, an application-incident-likely determination that a likelihood of an occurrence of an application incident exceeds an application-incident-likelihood threshold, the application incident corresponding to the first application or to the second application; and
responsive to making the application-incident-likely determination, outputting one or more alerts of the likelihood of the occurrence of the application incident.