Bank of America Corporation

Sean Denton

Stephen Thomas Shannon

Monika Kapur

David Michael Steele

Nelson John Chevis, Sr

The disclosure relates to an edge computing-based distributed network architecture. A central server in the architecture may include a client-location monitoring module for tracking a principle location of a client, which may be co-located with a remote hub institution. The central server may also include a client information packaging module, for packaging information associated with the client into a digital package; a natural-disaster monitor module, for monitoring for future natural-disasters; and a transmission module for transmitting a packaging instruction from the natural-disaster monitor module to the client information packaging module when the natural-disaster monitor module communicates that a natural-disaster is predicted to occur within a certain threshold distance and within a certain threshold amount of time. The transmission module may also retrieve, following packaging, the package from the client information packaging module and transmit the digital package to the remote hub institution for secure, albeit typically temporary, storage thereat.

Edge computing-based distributed network architecture that enables preemptive client-targeted local data storage

Apparatus and methods for maintaining service during a communication network outage. The apparatus may include an outage monitor. The outage monitor may monitor conditions that may affect the performance or integrity of a WAN. The apparatus may include a digital switch that may be configured to switch, responsive to a state variable in the monitor, between: a regular-operations information machine at an edge location; and a contingency server disposed at the edge location. When the switch engages the contingency server, data on the contingency server may be available to one or more of banking associates, call center attendants, customers and other suitable enterprise personnel and systems.

Adaptive edge-shift for enterprise contingency operations

The invention utilizes a two-component system to detect third party security threats and drive improved security threat mitigation based on the detection. The first component of the system is a security threat assessment engine, which receives and/or identifies external data and internal data regarding third parties in order to determine information security threats posed by third-parties. The second component of the system is an analytics engine, which may comprise a machine learning component which is configured to detect threat patterns and anomalies. In response to the detection of the threat patterns and anomalies the security threat assessment engine may be modified in order to more accurately determine security threats. The system after identifying a security threat, generates a notification associated with the security threat and transfers the notification to a first set of third parties that may be affected by the security threat.

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Rock Hill, SC, United States of America

Sean Denton