US 12,335,440 B2
Fraud detection in contact centers using deep learning model
Nick A. Maiorana, Charlotte, NC (US); Judy Cantor, Tinton Falls, NJ (US); Kevin R. Cieslak, Novato, CA (US); David Gorlesky, Concord, NC (US); and Jeremy Ernst, 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 Mar. 14, 2024, as Appl. No. 18/605,541.
Application 18/605,541 is a continuation of application No. 18/047,059, filed on Oct. 17, 2022, granted, now 11,949,811.
Application 18/047,059 is a continuation of application No. 17/119,326, filed on Dec. 11, 2020, granted, now 11,477,320, issued on Oct. 18, 2022.
Application 17/119,326 is a continuation of application No. 16/901,878, filed on Jun. 15, 2020, granted, now 10,904,381, issued on Jan. 26, 2021.
Application 16/901,878 is a continuation of application No. 16/138,265, filed on Sep. 21, 2018, granted, now 10,721,350, issued on Jul. 21, 2020.
Claims priority of provisional application 62/720,761, filed on Aug. 21, 2018.
Prior Publication US 2024/0223699 A1, Jul. 4, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. H04M 1/64 (2006.01); G06N 3/08 (2023.01); G10L 15/22 (2006.01); H04M 3/22 (2006.01); H04M 3/51 (2006.01); G06N 3/04 (2023.01)
CPC H04M 3/5166 (2013.01) [G06N 3/08 (2013.01); G10L 15/22 (2013.01); H04M 3/2281 (2013.01); G06F 2218/12 (2023.01); G06N 3/04 (2013.01); G10L 2015/223 (2013.01); H04M 2201/40 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A computing system comprising:
memory; and
one or more processors in communication with the memory and configured to:
obtain, during a call into a contact center from a user device, data indicative of a set of actions performed by the user device within the contact center and a corresponding set of results performed by the contact center during the call;
convert the set of actions and the corresponding set of results into a sequence of code pairs using a dictionary, wherein each code pair of the sequence of code pairs includes an action code corresponding to an action of the set of actions performed by the user device during the call and a result code corresponding to a respective result of the set of results performed by the contact center during the call;
determine an activity pattern during the call based on the sequence of code pairs;
calculate a probability that the call is fraudulent based on the activity pattern during the call; and
provide, to a fraud management system, a notification of the probability that the call is fraudulent.