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公开(公告)号：US20210342798A1
公开(公告)日：2021-11-04
申请号：US16865759
申请日：2020-05-04
发明人： Barry Hall , Adam Desautels , Verlon S. Watson, III , Letishia R. Hunt , Brendan P. Murphy , Charles Christopher Harbinson
IPC分类号： G06Q20/10 , G06F16/55 , G06Q30/00 , G06Q40/02 , G06Q20/04 , G06N20/00 , G06N5/04 , G06K9/00 , G06F40/205 , G06K9/62 , G06K9/18
摘要： Aspects of the disclosure relate to performing enhanced deposit item processing using cognitive automation tools. In some embodiments, a computing platform may receive, from a deposit item input support server, image data associated with a deposit item. Subsequently, the computing platform may apply a machine learning classification model to the image data associated with the deposit item. In doing so, the computing platform may produce one or more predicted values for one or more fields of the deposit item and one or more confidence scores for the one or more predicted values. Based on these predicted values and confidence scores, the computing platform may generate and send one or more commands directing the deposit item input support server to accept or reject the deposit item, which in turn may cause the deposit item input support server to accept or reject the deposit item.
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公开(公告)号：US20210398399A1
公开(公告)日：2021-12-23
申请号：US16907584
申请日：2020-06-22
摘要： A system includes a template database storing, for each of a plurality of predefined root causes, a corresponding correspondence template and response form template. Each root cause corresponds to a cause of an exception associated with an ATM. An automatic reconciliation tool determines a exception has occurred associated with a ATM. A set of exception parameters are determined associated with the exception. A party is determined at the service provider with which to correspond in or order to resolve the exception. A root cause of the exception is determined. A correspondence template and a response form template are identified for the determined root cause and used to generate correspondence which includes a description of the exception, instructions for actions to take, and a link configured to provide access to a response form. The response form includes fields for providing a response parameter.
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公开(公告)号：US20210374575A1
公开(公告)日：2021-12-02
申请号：US16889242
申请日：2020-06-01
发明人： Christine Malabad , Jeffrey R. Goertz , Letishia R. Hunt , Clement Chellaraj , Eric Dryer , Clarence E. Lee , Charles Christopher Harbinson , Verlon S. Watson
摘要： Aspects of the disclosure relate to performing enhanced exception processing using cognitive automation tools. In some embodiments, a computing platform may receive interaction data identifying one or more actions performed by one or more users in resolving a plurality of exception items associated with an exception queue. Subsequently, the computing platform may train, using a learning engine, a machine learning model to resolve a first exception and a second exception of one or more exceptions based on the interaction data. Based on training the machine learning model, the computing platform may generate one or more configuration commands directing a processing module to implement the machine learning model to process additional exception items associated with the exception queue. The computing platform then may send the one or more configuration commands to the processing module.
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公开(公告)号：US11631018B2
公开(公告)日：2023-04-18
申请号：US16889242
申请日：2020-06-01
发明人： Christine Malabad , Jeffrey R. Goertz , Letishia R. Hunt , Clement Chellaraj , Eric Dryer , Clarence E. Lee , Charles Christopher Harbinson , Verlon S. Watson
IPC分类号： G06N5/00 , G06N5/043 , G06N20/00 , G06Q40/02 , G06Q20/10 , G06Q10/10 , G06Q10/0631 , G06Q20/04
摘要： Aspects of the disclosure relate to performing enhanced exception processing using cognitive automation tools. In some embodiments, a computing platform may receive interaction data identifying one or more actions performed by one or more users in resolving a plurality of exception items associated with an exception queue. Subsequently, the computing platform may train, using a learning engine, a machine learning model to resolve a first exception and a second exception of one or more exceptions based on the interaction data. Based on training the machine learning model, the computing platform may generate one or more configuration commands directing a processing module to implement the machine learning model to process additional exception items associated with the exception queue. The computing platform then may send the one or more configuration commands to the processing module.
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公开(公告)号：US11257334B2
公开(公告)日：2022-02-22
申请号：US16907584
申请日：2020-06-22
摘要： A system includes a template database storing, for each of a plurality of predefined root causes, a corresponding correspondence template and response form template. Each root cause corresponds to a cause of an exception associated with an ATM. An automatic reconciliation tool determines a exception has occurred associated with a ATM. A set of exception parameters are determined associated with the exception. A party is determined at the service provider with which to correspond in or order to resolve the exception. A root cause of the exception is determined. A correspondence template and a response form template are identified for the determined root cause and used to generate correspondence which includes a description of the exception, instructions for actions to take, and a link configured to provide access to a response form. The response form includes fields for providing a response parameter.
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公开(公告)号：US11436579B2
公开(公告)日：2022-09-06
申请号：US16865759
申请日：2020-05-04
发明人： Barry Hall , Adam Desautels , Verlon S. Watson , Letishia R. Hunt , Brendan P. Murphy , Charles Christopher Harbinson
IPC分类号： G06Q20/10 , G06F16/55 , G06Q30/00 , G06Q40/02 , G06Q20/04 , G06N20/00 , G06F40/205 , G06K9/62 , G06N5/04 , G06V30/226 , G06V30/224 , G06V30/10
摘要： Aspects of the disclosure relate to performing enhanced deposit item processing using cognitive automation tools. In some embodiments, a computing platform may receive, from a deposit item input support server, image data associated with a deposit item. Subsequently, the computing platform may apply a machine learning classification model to the image data associated with the deposit item. In doing so, the computing platform may produce one or more predicted values for one or more fields of the deposit item and one or more confidence scores for the one or more predicted values. Based on these predicted values and confidence scores, the computing platform may generate and send one or more commands directing the deposit item input support server to accept or reject the deposit item, which in turn may cause the deposit item input support server to accept or reject the deposit item.
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公开(公告)号：US20210398094A1
公开(公告)日：2021-12-23
申请号：US16907518
申请日：2020-06-22
发明人： Letishia R. Hunt , Timothy Alan Mincey , Douglas Scott Wilson , Michael M. Wisser , Stuart C. Jones , Lucy M. Lahera , Shawn Cart Gunsolley , Eric T. Dryer
摘要： A device memory stores contact information for associates tasked with resolving the exceptions and a set of correspondence templates for requesting predefined types of information from one or more service providers. A processor determines a first exception has occurred associated with a first ATM. An exception profile is determined for the first exception. The exception profile is provided for viewing in a user interface accessible to the first associate. The processor receives, from the user interface, a request for information associated with resolving the first exception. Using the correspondence templates, correspondence is generated which includes the request for the information associated with resolving the first exception. The correspondence is addressed to the first service provider. The correspondence is provided to the first service provider.
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