	US 12,341,645 B2
	Systems and methods for prioritizing alerts
Milind Patel, Frisco, TX (US); Yar Savchenko, Frisco, TX (US); Nikitha Kondapally, Frisco, TX (US); Adonis Moore, Midlothian, VA (US); and Kevin Nguyen, Grand Prairie, TX (US)
Assigned to CAPITAL ONE SERVICES, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Aug. 17, 2021, as Appl. No. 17/404,375.
Prior Publication US 2023/0054815 A1, Feb. 23, 2023
Int. Cl. H04L 41/0686 (2022.01); G06N 20/00 (2019.01); H04L 41/0604 (2022.01); H04L 41/0631 (2022.01); H04L 41/069 (2022.01); H04L 41/16 (2022.01)

CPC H04L 41/0604 (2013.01) [G06N 20/00 (2019.01); H04L 41/0631 (2013.01); H04L 41/0686 (2013.01); H04L 41/069 (2013.01); H04L 41/16 (2013.01)]

19 Claims

1. A system for prioritizing alerts, comprising:

one or more processors; and

memory in communication with the one or more processors and storing instructions that are configured to cause the system to:

receive a first alert from a first application, the first alert comprising one or more fields, the one or more fields comprising at least a title and an identifier;

transmit a first prompt to rate the first alert to one or more user devices associated with one or more users;

receive a first rating label for the first alert, the first rating label comprising at least one of at least three options;

train a machine learning model to associate the first rating label with the first alert;

generate alert standards using the machine learning model from the one or more fields and the first rating label, the alert standards comprising field requirements;

receive a second alert from the first application;

determine, using the machine learning model, whether the second alert is similar to the first alert based on a predetermined similarity threshold;

based on the second alert satisfying the predetermined similarity threshold:

associate the first rating label with the second alert; and

transmit the second alert with the first rating label to the one or more user devices for display; and

based on the second alert failing to satisfy the predetermined similarity threshold:

transmit the second alert to the one or more user devices with a second prompt to rate the second alert;

receive a second rating label for the second alert;

train the machine learning model to associate the second rating label with the second alert; and

transmit the second alert with the second rating label to the one or more user devices for display; and

dynamically update the alert standards; and

transmit the updated alert standards to the one or more user devices.