Bank of America Corporation

Sudhakar Balu

Siva Kumar Paini

Sakshi Bakshi

Srinivasa Jitendra Dhanwada

Sathya Thamilarasan

Donna Maria Welch

Geeta Bora

Lakshmanan Palaniappan

Nagalaxmi Sama

Sri Lakshmi Priya Doraiswamy

Anup Kumar Kedia

A system for updating a software code executes a current version of the software code on a web application. The system receives a request message to update the current version of the software code to a new version of the software code. The system determines whether the software code is still being executed on the web application. In response to determining that the software code is still being executed on the web application, the system identifies a subset of portions of the software code that have not yet been executed, executes an update instruction to cause the subset of portions of the software code to be updated, and moves the updated subset of portions of the software code from a first memory block to a second memory block.

System and method for dynamic switching between an old version and a new version of a software code

A system for classifying software code determines a first function, a first set of operations, and a first criticality level of a first software code. The system determines a second function, a second set of operations, and a second criticality level of the second software code. The system determines that the first function of the first software code corresponds to the second function of the second software code. The system compares the operations of the first software code with the operations of the second software code and determines that the first and second software code have at least one operation in common with each other. The system determines that the first criticality level of the first software code corresponds to the second criticality level of the second software code. In response, the system classifies the first software code and the second software code in a first group.

System and method for classifying software code based on functionality and criticality

A device configured to identify automated process instructions for a network device. The automated process instructions include instructions for performing a series of actions on the network device. The device is further configured to identify a first time instance for executing the automated process instructions that does not occur within a time interval associated with a first system update for the network device and to execute the machine-executable code at the first time instance to perform the series of actions on the network device.

Scheduling a pausable automated process in a computer network

A system for protecting non-public information from a malicious user determines a set of input data entered into a web application. The system determines whether each input data is associated with non-public information. In this process, the system compares each input data with each of a set of keywords that are known to be associated with non-public information. In response to determining that input data corresponds to a keyword, the system determines that the input data comprises non-public information. In response, the system masks the input data and tags an authentication instruction to the masked input data. The system may receive a request to unmask the masked input data. In response to receiving the request, the system executes the authentication instruction.

System and method for protecting non-public information from malicious users

A system includes a memory and a processor. The memory stores a set of videos each of which is associated with an application of a set of applications and depicts a process performed using the application. For each video, the processor generates metadata associated with the depicted process, and stores the metadata within a collection of metadata in the memory. The processor receives a request for information from a user. In response, the processor identifies an application of the set of applications for use in generating a response to the request. The processor generates, based on the collection of metadata, instructions for interfacing with the first application to generate the response. The processor executes the instructions to interface with the first application to generate the response, and transmits the response to the user.

System and method for integration of automatic response generating systems with non-API applications

Aspects of the disclosure relate to monitoring, evaluating, and repairing bots in a hashchain-based distributed bot hub that process a workflow. In some embodiments, a computing platform may receive workflow information associated with performing a first workflow that includes executing one or more tasks using a plurality of virtual bots, instantiate a first subset of the plurality of bots to process the one or more tasks of the first workflow, and instantiate a first subset of the plurality of bots to process the one or more tasks of the first workflow. identifying a potential anomalous activity may include causing the monitor bot hub to remove the identified bot to a quarantine hub, and execute a repair process on the identified bot in the quarantine hub.

Dynamic workflow engine in an enterprise bot hub system

A system for detecting and countering malicious code executed on a web application detects a set of configuration parameter values from the web application. The system compares each configuration parameter value with a counterpart from among a set of historical configuration parameter values. The system determines the difference between a configuration parameter with a counterpart historical configuration parameter values. If the system determines that the difference between the configuration parameter and the counterpart historical configuration parameter is more than a threshold rate, the system determines that a malicious code is executed on the web application. In response, the system determines a function associated with the malicious code. The system determines one or more actions to counter the malicious code based on the function of the malicious code. The system executes at least one of the one or more actions.

System and method for detecting and countering malicious code

Aspects of the disclosure relate to an intelligent resource evaluation engine. A computing platform may monitor the plurality of RPA machines to detect parameter information. The computing platform may store the parameter information along with corresponding RPA machines as a key value pairs in a database. The computing platform may identify first current parameter information for a first RPA machine using the key value pairs. The computing platform may input the first current parameter information into an intelligent resource evaluation model, which may output first machine selection information for the first RPA machine. Based on identifying that the first RPA machine is sufficient to execute the first robotic automation process, the computing platform may send direct the first RPA machine to execute the first robotic automation process.

Intelligent resource evaluator system for robotic process automations

Systems, methods, and apparatus are provided for modification of RPA controls during a workflow without impacting bot performance. A background scan initiated in parallel to an RPA application workflow may identify values for an application control parameter and a corresponding bot control parameter. Hashes of the values may be validated against a key value pair stored as a block in a distributed ledger. If changes have been made to the application control values, the bot control value will not match the application control value and validation will fail. If validation fails, an override may be generated for the bot value. An updated bot value may be stored in a temporary cache until the workflow is complete. Following completion of the workflow, a new block may be added to the blockchain storing a new key value pair including the application control value and the updated bot control value.

Dynamic modification of robotic process automation control parameters using blockchain technology for correcting workflow failure

Various systems, methods, and computer program products are provided for dynamically generating an API. The method includes extracting metadata from a command recording of a system API. The command recording of the system includes a starting breakpoint and an ending breakpoint for one or more repetitive processes. The method also includes determining one or more API parameters for an API to be generated based on the extracted metadata. The method further includes dynamically generating the API based on the API parameters. The method still further includes causing an authentication of the credentials relating to the API via robotic process automation.

System and method of automated processing for dynamic API generation

A system includes a memory, a display, and a processor. The processor determines that the display is displaying an element associated with an application. The element includes at least one of a graphical user interface and a web browser. In response to determining that the display is displaying the element, the processor records a video of the display, which depicts a process performed using the element, to obtain a first set of information from the application. The processor extracts, from the video, metadata associated with the process depicted in the video. The processor generates, based at least in part on the extracted metadata, a set of instructions for interfacing with the application. When executed by the processor, the set of instructions are configured to cause the processor to interface with the application to obtain the first set of information. The processor further stores the set of instructions in the memory.

System and method for intelligently generating code for use in integrating automated response generating systems with non-API applications

Apparatus and methods for intelligently monitoring multiple bots for failure or predicted failure and notifying a user through a proximate Internet-of-Things ('IoT') device are provided. A program may receive configuration files for each IoT device and access to monitor each bot. The program may monitor each bot through a resiliency scanner module. The program may generate a report about a failure or predicted failure of a bot. The program may activate a self-healing engine to attempt to heal the bot. The program may activate an event-stream engine. The event-stream engine may determine which IoT device to transmit a report and notify the user through that IoT device to the failure or predicted failure. The user may respond through the IoT device or another device.

Intelligent real-time Internet-of-Things alert

A processor receives a request to communicate a source data using a preferred communication channel and obtains a first set of communication templates that correspond to a type of the source data and the preferred communication channel. The processor determines that no communication template in the first set includes a template associated with an overall performance indicator that equals or exceeds a first threshold. The pressor selects from the first set of communication templates, one or more communication templates that are associated with the highest values of the overall performance indicator. The processor then obtains an individual performance indicator associated with each multimedia component included in the selected one or more communication templates and generates a custom communication template by adding multimedia components having high individual performance indicators. The processor transforms the source data based on the custom communication template and transmits the transformed communication using the preferred communication channel.

Transforming source data based on performance indicators associated with templates

A device configured to identify automated process instructions for a first network device. The automated process instructions include instructions for performing a series of actions on the first network device. The device is further configured to identify a first time instance for executing the automated process instructions that is before a time interval associated with a system update for the first network device, to identify a second time instance corresponding with a start time of the time interval associated with the system update for the first network device, and to identify a third time instance corresponding with an end time of the time interval associated with the system update for the first network device. The device is further configured to execute the machine-executable code at the first time instance, to pause the execution of the machine-executable code at a breakpoint at the second time instance, and to resume execution of the machine-executable code after the breakpoint at the third time instance after the system update is complete.

Automated process and system update scheduling in a computer network

A system includes a memory and a processor. The memory stores a queue that includes a sequence of slots, each of which is configured to store a request. The processor receives, from a user device, a request for information. In response, the processor stores the request in an end slot of the queue. The processor collects values for parameters associated with the system. The processor determines, based on the request and the collected values for the parameters, an estimate of a time to generate a response to the request. Generating the response includes identifying an application for use in generating the response, generating, based on a set of videos of processes previously performed using the application, instructions for interfacing with the application to generate the response, and executing the instructions to interface with the application. The processor further transmits, to the user device, the estimate of the time.

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Chennai, India

Sudhakar Balu