Bank of America Corporation

Gopikrishna Nemalikanti

Manu Jacob Kurian

Jayachandra Varma

Saritha Vrittamani

Jason T Findley

Sorin N Cismas

Paul Roscoe

Jerzy Miernik

Abhishek Nagpal

Kevin A Delson

Gilbert M Gatchalian

Albena Noveva Fairchild

Crystal M Sundaramoorthy

A method for extracting, correlating, consolidating and presenting metadata from transmissions is provided. The method may include receiving a TCP/IP transmission. The transmission may include a header and a body. The method may include extracting an originating IP address from a location of the transmission. The location may be in the header or in the body. The IP address may be extracted in binary form. The method may include determining an accuracy and validity metric of the transmission using an artificial intelligence module. The method may include converting the extracted IP address from binary form into hexadecimal form. The method may include embedding the hexadecimal form of the IP address into one or more unused options of the header. The method may include processing the transmission. The processing may be completed upon determination that the transmission is a valid transmission.

Network forensic system for performing transmission metadata tracking and analysis

Systems and methods for batch multiplexing a plurality of transactions are provided. A system may include a machine-learning ('ML') based engine configured to receive instructions to execute a first transaction, derive a plurality of sets of delay parameters for the first transaction, and display the sets of delay parameters on a graphical user interface ('GUI') associated with a sender of the instructions. The engine may be configured to receive a selection of a set of delay parameters, and, based on the selection, append the first transaction to one of a plurality of pending transaction queues. The engine may be further configured to, within a maximum time window, combine the transactions in the pending transaction queue to create a single multiplexed transaction, and execute the multiplexed transaction. The engine may also be configured to demultiplex the multiplexed transaction after it is executed.

Batch transaction multiplexing engine

Aspects of the disclosure relate to transforming event data associated with an entity using a multicomputer platform and directing a client computing device to perform a determined action based on a detected event characteristic of the event data and a detected current event. With some embodiments, an event tracking server detects the current event from sensed data provided by a sensed data server and identifies a correlation measure between the detected event characteristic and the detected current event. The event tracking server may direct one or more client computing devices to perform one or more actions related to an entity based on the correlation measure.

Event tracking and notification based on sensed data

Systems and methods for self-referencing utilization calculation and dynamic resource allocation for digital transmissions are provided. Systems may include a target resource module configured to derive and store a target resource allocation for each sender from a plurality of senders. Systems may include a cost-calculation engine configured to generate a resource cost estimate for a transmission based on metadata associated with the transmission, and embed the resource cost estimate in the metadata. Systems may also include a resource allocation module configured to allocate digital resources for the transmission based on the metadata. Allocating digital resources for the transmission may reserve the digital resources for the transmission and prevent overloading of the digital resources.

Systems and methods for providing self-referencing utilization calculation and dynamic resource allocation based thereon for digital transmissions

The system provides the ability for primary users (e.g., parents, or the like) to assign actions to dependent users (e.g., kids, or the like) through the use of devices located at the location of the dependent users (e.g., home, or the like). The actions may be tasks for the dependent users to complete using devices (e.g., appliances or other devices). Moreover, the primary users can monitor if the dependent users are undertaking the assigned actions using the devices, and in response, may control the use of other devices at the same location (e.g., entertainment devices) until the dependent users undertake the actions (e.g., start, complete, etc. the actions). Assignment of the actions and control of the devices may be made automatically in order to aid in achieving the one or more desired actions. Notification of the actions and/or instructions on how to perform the actions may pushed to the devices.

Device control based on action completion

Aspects of the disclosure relate to utilizing smart data tags to track and control secure enterprise data. A computing platform may receive, from an enterprise user computing device, enterprise data. Subsequently, the computing platform may determine one or more tags to be applied to the enterprise data. Then, the computing platform may generate a smart data object based on the enterprise data received from the enterprise user computing device and the one or more tags determined to be applied to the enterprise data received from the enterprise user computing device. Next, the computing platform may send, to an enterprise data storage platform, the smart data object, and sending the smart data object to the enterprise data storage platform may cause the enterprise data storage platform to store the smart data object in a repository comprising a plurality of smart data objects maintained by the enterprise data storage platform.

Utilizing smart data tags to track and control secure enterprise data

Aspects of the disclosure relate to analyzing smart data using an automated response system. A computing platform may receive, from a user device, user feedback information comprising user feedback corresponding to an enterprise organization. Thereafter, the computing platform may identify, based on the user feedback information, identification information comprising a sender of the user feedback and an issue corresponding to the user feedback. Then, the computing platform may retrieve, from a hierarchical rules server and based on the identification information, hierarchy information comprising a hierarchy ranking of a plurality of automated responses. Subsequently, the computing platform may determine, based on analyzing the hierarchy information and the user feedback, an automated response from the plurality of automated responses. Next, the computing platform may generate one or more commands directing an external response server to execute the automated response. Then, the computing platform may transmit the one or more commands.

Automated response system using smart data

A method for throttling an allocation of resources for processing digital transmissions is provided. The method may include receiving initial digital transmissions from a plurality of client systems and analyzing the initial digital transmissions. The analyzing may determine a cluster of digital transmissions, an amount of resources for processing the cluster and a time-window for processing the cluster. The method may further include allocating the determined amount of resources to each of the clusters. The method may also include processing recurrently, for each of the systems, digital transmissions received after the initial digital transmissions. Concurrently with the periodic processing, the method may include, for each client system, monitoring digital transmissions including recording a transmission log, identifying changes in the log, assigning a credibility score and throttling, dynamically, the amount of resources allocated, based on the credibility score and the identified change.

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Frisco, TX, United States of America

Gopikrishna Nemalikanti