US 12,081,562 B2
Predictive remediation action system
Matthew Louis Nowak, Midlothian, VA (US); David Walter Peters, Richmond, VA (US); Keith D. Greene, Mechanicsville, VA (US); and Catherine Barnes, Glen Allen, VA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Oct. 25, 2021, as Appl. No. 17/509,437.
Prior Publication US 2023/0126193 A1, Apr. 27, 2023
Int. Cl. H04L 9/40 (2022.01); G06N 20/00 (2019.01)
CPC H04L 63/1416 (2013.01) [G06N 20/00 (2019.01); H04L 63/1433 (2013.01); H04L 63/1483 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
compiling, by a first computing device, ownership data and metric data as input data to a machine learning model data store, wherein the ownership data comprises data representative of assets, involved in one or more incidents, of an entity and data representative of relationships between the assets, wherein the metric data comprises data representative of development operations tools metric data of the assets;
determining, by a second computing device, a relationship between the input data and an occurrence of one or more incidents in new incident data, representative of a plurality of incidents involving one or more of the assets with corresponding one or more assigned remediation actions, wherein each remediation action was assigned to mitigate reoccurrence of a corresponding incident;
predicting, via a machine learning model trained to recognize one or more relationships between the occurrence of one or more incidents and second assets data, wherein the second assets data comprises data representative of second assets and data representative of relationships between the second assets, a relationship between the occurrence and the second assets data, based upon the input data from the machine learning model data store; and
outputting a notification assigning one or more of the assigned remediation actions to at least one second asset.