US 11,729,011 B1
Rapid and efficient case opening from negative news
Angelica Bullard, Oakland, CA (US); Mauricio Flores, Oakland, CA (US); Ian Kloville, San Francisco, CA (US); Jeremy Norvell, Livermore, CA (US); Sameer Shetty, Concord, NC (US); and Michael Traverso, Chicago, IL (US)
Assigned to Wells Fargo Bank, N.A., San Franclsco, CA (US)
Filed by Wells Fargo Bank, N.A., San Francisco, CA (US)
Filed on Aug. 29, 2022, as Appl. No. 17/897,574.
Application 17/897,574 is a continuation of application No. 16/711,951, filed on Dec. 12, 2019, granted, now 11,431,519.
Int. Cl. H04L 12/18 (2006.01); G06N 20/00 (2019.01); G06F 40/295 (2020.01); G06Q 50/26 (2012.01); H04L 67/53 (2022.01); G06N 7/01 (2023.01); G08B 7/06 (2006.01)
CPC H04L 12/1895 (2013.01) [G06F 40/295 (2020.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 50/265 (2013.01); H04L 67/53 (2022.05); G08B 7/06 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A machine-learning method implemented by a computing system, the method comprising:
monitoring, by the computing system, a plurality of news sources, which generate a set of news alerts, to detect a subset of news alerts satisfying a criterion;
applying, by the computing system, an entity extraction model to the subset of news alerts to identify a set of persons or organizations associated with the criterion;
generating, by the computing system, an enriched alert comprising one or more of the news alerts in the subset of news alerts and data on the set of persons or organizations;
applying, by the computing system, a predictive model to determine a probability that the enriched alert will trigger a suspicious activity report;
determining, by the computing system, that the probability is greater than a threshold probability;
applying, by the computing system and in response to determining that the probability is greater than the threshold, a relevance model to identify a destination computing device; and
transmitting, by the computing system, the enriched alert to the identified destination computing device;
wherein applying the entity extraction model produces a first person or organization named in the subset of news alerts, and a second person or organization who is not named in the subset of news alerts but who is related to the first person or organization.