公开(公告)号：US11842391B2

公开(公告)日：2023-12-12

申请号：US17233300

申请日：2021-04-16

Applicant: FIDELITY INFORMATION SERVICES, LLC

Inventor： Benjamin Wellmann ,  Zachary Jasinski ,  Matthew Petersen ,  Eric Bond ,  Daniel Wakeman ,  David Berglund

IPC: G06Q40/00 ,  G06Q40/03 ,  G06F9/54 ,  G06F40/20 ,  G06N20/00

CPC classification number: G06Q40/03 ,  G06F9/547 ,  G06F40/20 ,  G06N20/00

Abstract: Systems and methods for activity risk management are disclosed. A system for activity risk management may include a memory storing instructions and at least one processor configured to execute instructions to perform operations including: accessing document data associated with at least one of a transaction or an individual; normalizing the document data; classifying the normalized document data; extracting model input data from the classified document data; applying a machine learning model to the extracted model input data to score the document data, the machine learning model having been trained to generate a favorability output indicating a favorability of the transaction or individual; and generating analysis data based on the scored document data.

公开(公告)号：US11816476B2

公开(公告)日：2023-11-14

申请号：US17448561

申请日：2021-09-23

Applicant: Fidelity Information Services, LLC

Inventor： Per Karlsson ,  Benjamin Wellmann ,  Sheel Saket ,  Vida Lashkari

IPC: G06F8/71 ,  G06N20/00 ,  G06F11/32

CPC classification number: G06F8/71 ,  G06F11/327 ,  G06N20/00

Abstract: A method for training and using a machine-learning based model to reduce and troubleshoot incidents in a system may include receiving first metadata regarding a previous modification, extracting a first feature from the received first metadata, receiving second metadata regarding a previous incident, extracting a second feature from the received second metadata, training the machine-learning based model to learn an association between the previous modification and the previous incident, based on the extracted first feature and the extracted second feature, and using the machine-learning based model to determine a risk level for a proposed modification to a system.

公开(公告)号：US20230342685A1

公开(公告)日：2023-10-26

申请号：US18342813

申请日：2023-06-28

Applicant: FIDELITY INFORMATION SERVICES, LLC

Inventor： Joel E. DAKE ,  Damyn L. GESSLER ,  Shane M. PATZLSBERGER ,  Shane W. Strunk ,  Benjamin Wellmann

IPC: G06Q10/0631 ,  G06F40/40 ,  G06F9/451 ,  G06N20/00

CPC classification number: G06Q10/063114 ,  G06F40/40 ,  G06F9/451 ,  G06N20/00

Abstract: Some aspects of the present disclosure are directed to computer-implemented systems and methods for efficient ticket resolution. The methods may include: receiving a request to resolve an issue; analyzing, via natural language processing, the language in the request to determine the issue to be resolved; determining whether the issue meets a condition for automated resolution; if the condition is met: extracting, via an application programming interface and from the at least one user device, information needed to resolve the issue; and resolving the issue using the extracted information; and if the condition is not met: generating a ticket; assigning a work group to the ticket; determining whether a job aid associated with the issue exists; and forwarding at least one of: the job aid; received communications from the work group; and an estimated amount of time to resolution.

公开(公告)号：US11727331B2

公开(公告)日：2023-08-15

申请号：US17140812

申请日：2021-01-04

Applicant: FIDELITY INFORMATION SERVICES, LLC

Inventor： Joel E. Dake ,  Damyn L. Gessler ,  Shane M Patzlsberger ,  Shane W. Strunk ,  Benjamin Wellmann

IPC: G06Q10/00 ,  G06Q10/0631 ,  G06F40/40 ,  G06F9/451 ,  G06N20/00

CPC classification number: G06Q10/063114 ,  G06F9/451 ,  G06F40/40 ,  G06N20/00

Abstract: Some aspects of the present disclosure are directed to computer-implemented systems and methods for efficient ticket resolution. The methods may include: receiving a request to resolve an issue; analyzing, via natural language processing, the language in the request to determine the issue to be resolved; determining whether the issue meets a condition for automated resolution; if the condition is met: extracting, via an application programming interface and from the at least one user device, information needed to resolve the issue; and resolving the issue using the extracted information; and if the condition is not met: generating a ticket; assigning a work group to the ticket; determining whether a job aid associated with the issue exists; and forwarding at least one of: the job aid; received communications from the work group; and an estimated amount of time to resolution.