BANK OF AMERICA CORPORATION patent applications on February 20th, 2025
Patent Applications by BANK OF AMERICA CORPORATION on February 20th, 2025
BANK OF AMERICA CORPORATION: 15 patent applications
BANK OF AMERICA CORPORATION has applied for patents in the areas of G06F11/34 (3), H04L9/40 (2), G06F21/62 (2), H04L9/32 (2), G06F11/30 (2) G06F11/3495 (1), G06F16/254 (1), G06F21/554 (1), G06F21/6218 (1), G06F40/284 (1)
With keywords such as: data, user, based, computing, application, memory, interaction, access, module, and request in patent application abstracts.
Patent Applications by BANK OF AMERICA CORPORATION
Inventor(s): Karthikeyan Krishnan of Chennai (IN) for bank of america corporation, Param Jabbal of Frisco TX (US) for bank of america corporation, Mukesh Kumar Jain of Jacksonville FL (US) for bank of america corporation, Lazar Kaplansky of Fair Lawn NJ (US) for bank of america corporation, Muthuraj Kumaresan of Singapore (SG) for bank of america corporation, Frank Maglio of North Brunswick NJ (US) for bank of america corporation, Vikas Kumar Sahu of Hyderabad (IN) for bank of america corporation, Raghunandan Sonawa of Sanganer (IN) for bank of america corporation
IPC Code(s): G06F11/34, G06F11/30, G06F16/28
CPC Code(s): G06F11/3495
Abstract: systems, computer program products, and methods are described herein for application anomaly detection using advanced computational ai machine learning modeling. in this way, performance metric data is extracted and the variances are derived by comparing the performance metrics of the application workload for the current time period against the same for a previous period. the ai model is trained at regular intervals by using the derived performance metrics data to identify only the candidate workloads which are degrading or underperforming at an early state, while avoiding reporting workloads that are not causing impact to performance stability of applications across an entity database network. the system monitors application workload across a relational database of an entity for degraded application performance and identifies changes in application workload performance and applies the anomaly detection artificial intelligence machine learning model.
Inventor(s): Naga Vamsi Krishna Akkapeddi of Charlotte NC (US) for bank of america corporation, Awan Nord of Costa Mesa CA (US) for bank of america corporation
IPC Code(s): G06F16/25, G06F16/906, G06F16/93
CPC Code(s): G06F16/254
Abstract: a system for extracting and providing information from a source document includes a memory and a processor. the memory stores data associated with the source document. the processor is configured to extracts data from the source document and stores that extracted data as a first extracted data in the memory. when a request for information is received, the processor then determines if the first extracted data includes all the requested information and if it does not, the processor extracts second extracted data from the image file and stores the second extracted data along with the first extracted data and the image file in the memory. the requested information is then provided to the requesting process from the first and second extracted data.
Inventor(s): Shailendra Singh of Thane West (IN) for bank of america corporation, Vinod Maghnani of Gurugram (IN) for bank of america corporation, Sunil Bhashetty of Hyderabad (IN) for bank of america corporation, Tulasi Nekkanti of Hyderabad (IN) for bank of america corporation, Zakir Basha Shaik of Hyderabad (IN) for bank of america corporation
IPC Code(s): G06F21/55, G06F3/01, G06F21/62, G06T19/00
CPC Code(s): G06F21/554
Abstract: a method includes rendering on displays of a plurality of extended reality (xr) devices an xr environment. the xr environment includes a first user avatar authorized to interact with an xr application of the plurality of xr applications and a second user avatar unauthorized to interact with the xr application. the method includes receiving, by sensors of an xr device, sensor data indicative of a user intent to interact with the xr application by the second user avatar, generating, based on the sensor data, an estimation of an unauthorized interaction with the xr application by the second user avatar, executing, based on the estimation of the unauthorized interaction, a data obfuscation of information associated with an authorized interaction with the xr application by the first user avatar, and re-rendering on the displays of the plurality of xr devices the xr application in accordance with the executed data obfuscation.
Inventor(s): Arjun Thimmareddy of Charlotte NC (US) for bank of america corporation, Aarron Gull of East Northport NY (US) for bank of america corporation
IPC Code(s): G06F21/62
CPC Code(s): G06F21/6218
Abstract: an information-security automated system for authorizing a user request for access to a module and for identifying anomalous user authorization requests may include components for receiving the user request for access to the module from the authorization request tool over a computer network, a computer machine comprising a processor, and computer-executable instructions stored on a computer-readable medium configured to cause the processor to perform steps of receiving a user request for access to a module, generating a peer group proximity dataset, generating a user dataset, calculating a critical score, determining if the critical score is less than an enterprise threshold, and generating an approval or denial of the user request based upon the critical score. in some examples the process may include the step of executing machine learning instructions to generate a second approval or a second denial of a second user request for access to a second module.
Inventor(s): Nitin Bansal of Hisar (IN) for bank of america corporation, Kapil Juneja of Jaipur (IN) for bank of america corporation, Rajalakshmi Arumugam of Chennai (IN) for bank of america corporation, Kumaraguru Mohan of Perungalathur (IN) for bank of america corporation, Venkatesh Polneedi of Hyderabad (IN) for bank of america corporation, Anil Garg of Gurugram (IN) for bank of america corporation, Gaurav Kumar Kashyap of Delhi (IN) for bank of america corporation
IPC Code(s): G06F40/284, G06F11/34
CPC Code(s): G06F40/284
Abstract: a system for interaction pattern recognition receives an input primary interaction and accesses clusters indicating interaction group patterns. each cluster includes a respective primary interaction and secondary interactions linked to that primary interaction. each cluster is identified by a respective non-fungible token. the system then determines a non-fungible token of the input primary interaction, compares it to the non-fungible tokens of the clusters, selects a first cluster based on a match between the non-fungible token of the input primary interaction and a first non-fungible token identifying the first cluster, determines the secondary interactions in the first cluster as linked to the input primary interaction, retrieves the secondary interactions from the clusters, generates a recommended group of interactions including the input primary interaction and the retrieved secondary interactions, and provides the recommended group of interactions and an indication that the retrieved secondary interactions are linked to the input primary interaction.
Inventor(s): Varshini RV of Madurai (IN) for bank of america corporation, Thilagaraj Kannaiyan of Salem (IN) for bank of america corporation, Madhav Vaidyanath of Chennai (IN) for bank of america corporation
IPC Code(s): G06N10/60, G06N10/40
CPC Code(s): G06N10/60
Abstract: a method for memory reallocation for micro applications using quantum computing includes receiving logs for a micro applications server. a first score is determined based on the received logs. the first score is compared to a score threshold. in response to determining that memory reallocation is needed, the first score is compared to a plurality of scores. in response to the first score not matching any of the plurality of scores, a predicted memory configuration is determined based on the first score. an improved memory configuration is determined based on the predicted memory configuration. the improved memory configuration determines a respective memory allocation for micro applications hosted by the micro applications server. the improved memory configuration is deployed to the micro applications server. the micro applications server is restarted.
Inventor(s): Rahul Yaksh of Austin TX (US) for bank of america corporation, Amer Ali of Jersey City NJ (US) for bank of america corporation, Brian Jacobson of Los Angeles CA (US) for bank of america corporation, Elvis Nyamwange of Little Elm TX (US) for bank of america corporation, Erik Dahl of Newark DE (US) for bank of america corporation, Hari Vuppala of Charlotte NC (US) for bank of america corporation, Pratap Dande of Saint Johns FL (US) for bank of america corporation, Rahul Phadnis of Charlotte NC (US) for bank of america corporation, Sailesh Vezzu of Hillsborough NJ (US) for bank of america corporation
IPC Code(s): G06Q30/018, G06V30/412
CPC Code(s): G06Q30/0185
Abstract: systems and methods for alerting an organization about activity that may be fraudulent. systems may include a computer processor, a storage module, a cleaning module, a preprocessing module, a features extraction module, and a machine learning module. the computer processor may be configured to run a fraud detection engine by collecting publicly available electronic forms every 36 hours, using the modules to store the forms, clean the data, preprocess the data, and run a machine learning model to extract features and to determine if a threshold indicating a risk of fraud has been exceeded. the machine learning models include a liquid, solvency, and profitability ratio classification model, a disclosure classification model, a sentiment analysis model, an anomaly detection classification model, an ownership analysis classification model, and an esg disclosure classification model. when exceeding a threshold, the computer processor may notify an administrator of the exceeded threshold's identity.
Inventor(s): Aeric Solow of Richardson TX (US) for bank of america corporation, Manu Kurian of Dallas TX (US) for bank of america corporation
IPC Code(s): G06Q30/0201, G06Q30/0251
CPC Code(s): G06Q30/0201
Abstract: a predictive ai model generation and execution system with a plurality of engines is provided. a data exchange computing engine may receive and process one or more data streams to generate processed data, and send the processed data to a model generation and execution computing engine. the model generation and execution computing engine may receive the processed data and update a first predictive artificial intelligence model using the processed data. the client interface computing engine may receive a model execution request, generate and send a first graphical user interface, receive model execution data from the external client computing system, and send the model execution data to the workflow management computing engine. the workflow management computing engine may generate one or more model execution instructions based on the model execution data, and send the one or more model execution instructions to the model generation and execution computing engine.
Inventor(s): Jack Patrick Kelly of New York NY (US) for bank of america corporation, Michelle Anna-Frances Olsson of Brooklyn NY (US) for bank of america corporation, Daniel Steven Wennerstrum of Western Springs IL (US) for bank of america corporation
IPC Code(s): G06Q40/06, G06Q40/02
CPC Code(s): G06Q40/06
Abstract: systems, computer program products, and methods are described herein for modular subscription-centric resource architectures. the invention streamlines the user experience through a mobile banking application interface. it's designed to collect a user's resource account data, which includes their preferences, goals, and affiliations with one or more entities. by employing machine learning algorithms, the system analyzes the saved resource account data to ascertain the most fitting subscription tier recommendation. for those new to the platform, essential packages are recommended, while established users are presented with more detailed packages. the dashboard interface showcases the distinct benefits and features of each subscription tier, allowing for informed user selection. furthermore, within this dashboard interface, there's a section dedicated to customizable bundle selection.
Inventor(s): Amanda Jane Adams of Flint (GB) for bank of america corporation, Beverley Claire Morgan of Wrexham (GB) for bank of america corporation
IPC Code(s): H04L9/32, G06F11/30, G06F11/34, H04L67/50
CPC Code(s): H04L9/3236
Abstract: aspects of the disclosure relate to enhanced tracking of data over an asset lifecycle. a computing platform may receive, via the communication interface, user account information as part of an onboarding process in which a first user account is created. the computing platform may then compute, using a cryptographic hash function, a first hash value associated with the first user account, wherein the first hash value provides a trackable, immutable code corresponding to the first user account. thereafter, the computing platform may monitor one or more events in a transaction activity pool. upon detecting a new activity associated with the first user account in the transaction activity pool, the computing platform may append the new activity to a record in a trackable log linked to the first hash value.
Inventor(s): Elvis Nyamwange of Little Elm TX (US) for bank of america corporation, Sailesh Vezzu of Hillsborough NJ (US) for bank of america corporation, Amer Ali of Jersey City NJ (US) for bank of america corporation, Rahul Yaksh of Austin TX (US) for bank of america corporation, Hari Vuppala of Concord NC (US) for bank of america corporation, Pratap Dande of Saint Johns FL (US) for bank of america corporation, Brian Neal Jacobson of Los Angeles CA (US) for bank of america corporation, Erik Dahl of Newark DE (US) for bank of america corporation, Rahul Shashidhar Phadnis of Charlotte NC (US) for bank of america corporation
IPC Code(s): H04L9/32, G06F16/11
CPC Code(s): H04L9/3247
Abstract: systems, computer program products, and methods are described herein for dynamic, secure, token-based snapshot generation. the present disclosure is configured to receive, via an alternative access point, a user request to receive a snapshot of one or more resource repositories associated with a user; generate, using a token generator, a token based on at least the user request; authenticate, using an authentication subsystem, the user using the token to confirm legitimacy of the user request; generate, using a snapshot generator, the snapshot of the one or more resource repositories based on at least confirming the legitimacy of the user request, wherein the snapshot is generated based on pre-defined user preferences; embed, using a digital signature subsystem, the snapshot with a digital signature serving as an attestation; and display the snapshot on the user input device.
Inventor(s): Kamal D. Sharma of Mason OH (US) for bank of america corporation, Gilbert Gatchalian of Union NJ (US) for bank of america corporation, Kevin A. Delson of Woodland Hills CA (US) for bank of america corporation, Satya Veerabhadra Rao Iruku of Chesterfield NJ (US) for bank of america corporation, Noell York Eury of Charlotte NC (US) for bank of america corporation, Dhananjay Bhat of North Chelmsford MA (US) for bank of america corporation, Russ Ferguson of Brooklyn NY (US) for bank of america corporation
IPC Code(s): H04L41/12, H04L41/0816, H04L41/22
CPC Code(s): H04L41/12
Abstract: a system is provided for secure cross partition access and computing device recovery. in particular, the system may comprise a computing device that includes a non-transitory memory or storage device comprising one or more partitions. a user may attempt to log into the device and get locked out of the primary partition of the device after a threshold number of unsuccessful login attempts. the additional partitions of the computing device may store a portion of the authentication credential needed to access the primary partition and prompt the user using an item from the user data stored in a user-specific database. upon detecting that the user has successfully accessed a threshold number of partitions and/or successfully provided responses to the prompts from a threshold number of partitions, the system may unlock and grant access to the locked partitions.
Inventor(s): Susan Moss of Vestal NY (US) for bank of america corporation, Malinda Kieffer of Chillicothe MO (US) for bank of america corporation, Tanya Wilson of Newark DE (US) for bank of america corporation, Andrzej Grabski of Glen Rock NJ (US) for bank of america corporation, Donna Phillips of Newark DE (US) for bank of america corporation, Kiran Boosetty of Jacksonville FL (US) for bank of america corporation, Robert R. Rosseland of Charlotte NC (US) for bank of america corporation, Ravinder Sodhi of Plano TX (US) for bank of america corporation, Gerard Gay of Seattle WA (US) for bank of america corporation, Rahul Mishra of Pennington NJ (US) for bank of america corporation, Samuel M. Moiyallah of Newark DE (US) for bank of america corporation
IPC Code(s): H04L9/40
CPC Code(s): H04L63/10
Abstract: an artificially intelligent system for selection of user entitlements may be provided. the system may include a receiver that receives data elements. the system may include an artificially intelligent engine. the artificially intelligent engine may receive the data elements from the receiver and process and/or manipulate the data elements. the processing and/or manipulating the data elements may include identifying ownership data of hardware, identifying ownership data of software entitlements based on the identified ownership data of the hardware, identifying groups of users and group-based access to the current set of entitlements and previous sets of entitlements, mapping the group-based access based on the groups of users and group-based access findings, identifying the user's level of access to the current set and previous sets of entitlements, using the data elements to generate a description for each entitlement in an entitlement subset and generating a selectable template for the user's future entitlements.
Inventor(s): Mark Schaaf of Fort Mill SC (US) for bank of america corporation
IPC Code(s): H04L9/40, H04L41/16, H04L51/08
CPC Code(s): H04L63/145
Abstract: processes and machines are disclosed for detecting malicious email campaigns based on unique but similarly spelled attachments. email log(s) from network appliances are retrieved, filtered, normalized, and converted into field-based organized data for comprehensive analysis. cluster analysis is performed. filenames of email attachments are transformed into numerical vectors and a cosine similarity termset analysis is performed on the numerical vectors. data is organized into time bins for burst detection. statistical analysis is performed on the time bins. pattern recognition is performed to identify alphanumeric similarities in the filenames of the attached files in order to detect malicious email campaigns. machine learning may be used to optimize the cosine similarity threshold and other query variables, and to update existing cybersecurity filters and firewalls. mitigation can be performed to remove malicious emails that were delivered to recipient mailboxes.
Inventor(s): Jennifer Sanctis of Charlotte NC (US) for bank of america corporation, Srinivas Chavali of Charlotte NC (US) for bank of america corporation, Taylor Farris of Hoboken NJ (US) for bank of america corporation
IPC Code(s): H04W12/30, G06F21/32, H04W12/63
CPC Code(s): H04W12/35
Abstract: a system that dynamically adjusts an operation of software running on a first mobile device is provided. the system may include an application. the system may include an authentication module configured to authorize a user's login credentials, capture a biometric characteristic of the user, and authenticate the captured biometric characteristic based on a comparison to a stored biometric characteristic. the system may also include a tracking module configured to track a location of each of the plurality of mobile devices and based on the location, determine a number of mobile devices within a pre-determined range to the first mobile device. the system may include a throttling module configured to adjust the operation of the application based on the number of mobile devices, the adjusting including at least one of operating the application in read-only mode, partial-access mode and full-access mode and re-adjusting when a change in location is detected.
BANK OF AMERICA CORPORATION patent applications on February 20th, 2025
- BANK OF AMERICA CORPORATION
- G06F11/34
- G06F11/30
- G06F16/28
- CPC G06F11/3495
- Bank of america corporation
- G06F16/25
- G06F16/906
- G06F16/93
- CPC G06F16/254
- G06F21/55
- G06F3/01
- G06F21/62
- G06T19/00
- CPC G06F21/554
- CPC G06F21/6218
- G06F40/284
- CPC G06F40/284
- G06N10/60
- G06N10/40
- CPC G06N10/60
- G06Q30/018
- G06V30/412
- CPC G06Q30/0185
- G06Q30/0201
- G06Q30/0251
- CPC G06Q30/0201
- G06Q40/06
- G06Q40/02
- CPC G06Q40/06
- H04L9/32
- H04L67/50
- CPC H04L9/3236
- G06F16/11
- CPC H04L9/3247
- H04L41/12
- H04L41/0816
- H04L41/22
- CPC H04L41/12
- H04L9/40
- CPC H04L63/10
- H04L41/16
- H04L51/08
- CPC H04L63/145
- H04W12/30
- G06F21/32
- H04W12/63
- CPC H04W12/35
