Method and system for forecasting service level indicator metrics for anomaly detection
AssigneeJPMorgan Chase Bank, N.A.
InventorsDavid DEPPE, Hrudai BATTINI, Makarand BHALEKAR, Ramya Lekha ARCOT BHASKER
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AssigneeJPMorgan Chase Bank, N.A.
InventorsDavid DEPPE, Hrudai BATTINI, Makarand BHALEKAR, Ramya Lekha ARCOT BHASKER
Estimating the term…
Various methods and processes, apparatuses or systems, and media for forecasting of service level indicator (SLI) metrics using deep learning algorithms in order to detect anomalies and to provide accurate alerts to users are disclosed. The method includes: receiving information that relates to an incoming call volume for a particular queue from among a set of queues; analyzing, by using a model, the first information in order to determine a set of SLI metrics that relate to the queue; generating a forecast of one or more of the SLI metrics for the queue; and displaying, via a graphical user interface, information that relates to the forecast.
A method for forecasting of service level indicator (SLI) metrics with respect to a customer contact center, the method being implemented by at least one processor, the method comprising:
A computing apparatus for forecasting of service level indicator (SLI) metrics with respect to a customer contact center, the computing apparatus comprising:
A non-transitory computer readable storage medium storing instructions for forecasting of service level indicator (SLI) metrics with respect to a customer contact center, the storage medium comprising executable code which, when executed by a processor, causes the processor to:
Dependencies are inferred from the claim text.