Bank of America Corporation

Prabhat Ranjan

Nurani Parasuraman

Kevin A Delson

Rajsekhar Singha Roy

Siten Sanghvi

Naga Vamsi Krishna Akkapeddi

William August Stahlhut

Monika Kapur

John Ryan Bowling

Steven Nathan Greene

Jeff Lojko

Febby John Oommen

Sireesha K Gorantla

Joseph Anil Kumar Mendemu

Manish Nahata

Ketulkumar Vinodchandra Joshi

Karan Singh Negi

Christopher Herman Cokis

Krishna Chand Paruchuri

Ketul Vinodchandra Joshi

Various aspects of the disclosure relate to distributed ledger computing systems and customizing tokens for securing and facilitating transactions recorded in the distributed ledger. A token customization module may be used to build customized controls into a token for use in a blockchain system. The token customization module may personalize or otherwise customize rules based on requirements of a user's particular use of the distributed ledger system. The customized rules may be used to trigger alerting behavior, prevent and/or automate particular transactions, provide geofencing and/or regional restrictions for transactions of a specified type, among others. Once built, the rules may be incorporated into the tokens and immutably memorialized in the distributed ledger. The customized tokens may be associated with or incorporate a smart contract to layer additional functionality.

Customized token rules generation system

Aspects of the disclosure relate to voice-based time-sensitive task processing over a high generation cellular network. A computing platform may establish a communication channel with a computing device. The computing platform may authenticate a user of the computing device, where the user is authorized to access the enterprise server. Then, the computing platform may detect, via the communication interface, a voice-based interaction from the authenticated user. The computing platform may cause the voice-based interaction to be captured as audio data. Subsequently, the computing platform may transform the audio data to textual data. The computing platform may analyze the textual data to identify a time-sensitive task related to an entity. Then, the computing platform may generate, based on the identified time-sensitive task, one or more instructions to execute the time-sensitive task. Subsequently, the computing platform may send, to an enterprise server, the one or more instructions to execute the time-sensitive task.

Voice-based time-sensitive task processing over a high generation cellular network

Monitoring backend batch processes/agents to identify currently enabled batch processes that running/executing on schedule and those that are not running/executing on schedule. In the event that currently enabled backend batch processes are identified as delayed, a delay time is determined. Such determinations are made on a regular interval, (e.g., hourly or the like), such that, reports is generated and communicated and/or a batch process status portal is updated on the regular interval to reflect the current delayed status of batch process or, in some embodiments, the current status of all of the backend batch processes currently enabled within an enterprise. Identification of backend batch processes that are currently being delayed and the associated delay time provides a basis for determining the cause(s) for the delay and possible corrective action(s), which may be implemented in conjunction with the determinations.

Systems for determining delayed or hung backend processes within process management applications

A system for exchanging authentication data between edge-nodes is provided. The system may include an edge-node network. The network may include a plurality of edge-nodes. Each edge-node may include a pairing module. Each pairing module may receive an instruction to pair with another edge-node. Each pairing module pair with another edge-node. The pairing module may continually transmit verification communications to other edge-nodes. The pairing module may continually discover responsive communications from other edge-nodes. The pairing module may continually receive responsive verification communications from other edge-nodes. Each edge-node may include an executable module. The executable module may determine occurrence of an event. Upon determination of the occurrence of an event, the executable module may analyze a stored event protocol. The protocol including an algorithm for implementing executables in response to an event. The executable module may determine an executable based on the algorithm, and execute the determined executable.

Edge-node authentication-data exchange system

A system executes multiple ruleset version scanning, warning and correction using a Software Deployment Management (SDM) environment such as Pega&#xae;. The system presents a code scanning interface to a user; receives input from the user selecting input rulesets comprising at least one ruleset and at least one version of the ruleset for scanning; accesses a guiderail database comprising a plurality of guiderails configured as best practices for SDM application development; scans the input rulesets comprising applying at least a portion of the plurality of guiderails to each of the input rulesets; and determining which of the input rulesets comprise compliance issues and a severity of each of the compliance issues; and presents an indication of severity of compliance issues for each of the input rulesets to the user using the code scanning interface.

Multiple ruleset version scanning, warning and correction tool

A system executes an enterprise framework for efficient software deployment using a Software Deployment Management (SDM) environment such as Pega&#xae;. The system includes an orchestration framework to receive a single input from an administrator; and in response to receiving the single input from the administrator, initiating an end-to-end software deployment process. A smart framework receives instructions from the orchestration framework to initiate the end-to-end software deployment process; manages a rule-set for code development; and packages a product based on developed code. A shell script stores the product in a versioning repository; and publishes a release note corresponding to the product. The orchestration framework deploys the product to a testing environment; and performs a restart for each server. The smart framework validates deployment; and performs a diagnostic check. A testing framework performs a smoke test and a regression test.

Enterprise framework for efficient software deployment

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Plano, TX, United States of America

Prabhat Ranjan