Bank of America Corporation

Eric Dryer

Jeffrey R Goertz

Michael Matthew Wisser

Shawn Cart Gunsolley

Kerry Michelle Cantley

Michael Gerald Smith

Carl Parziale

Jennifer Ann Raley

Douglas Scott Wilson

Joshua Allen Beaudry

Marshall Bright Thompson

Gary L Best, Jr

James F Barrett, Ii

Edwin Andrew Wegleitner

Colleen Marie Powers

Andrew Patrick Bastnagel

Geoffrey Reed Williams

Verlon Safold Watson, Iii

James William Stark, Iii

Shiva-Sanjay Bhakta

Mike Stoll

Tim Gauvin

Krishna Kota

David T Frew

Mark D Zanzot

Anthony B Calderone

Letishia Renee Hunt

Philip Tobin

Garrett C Briggs

William Earl Thomas, Ii

Jordan Josiah Conklin

Pratap Dande

Kevin A Delson

Morgan Stewart Allen

Lalit Dhawan

Gilbert M Gatchalian

Linda Haddad

Eric Scott Sandoz

Lowell Robert Huff

Rebecca Stepp Morgan

Clarence Edward Lee, Ii

Erin Cassell

Charles Christopher Harbinson

George Miller Abernethy

Ronald Hollander

Sean B Kang

Chad Ryan Compton

Jeffrey Robert Woodside

Timothy Alan Mincey

Clarence E Lee

Verlon S Watson

William D Arthur

Brendan Patrick Spencer Murphy

Clement Chellaraj

Lucy M Lahera

Christine Malabad

Verion S Watson, Iii

A bot automatically compiles transaction information for a consumer from merchants that sell products in various categories and merchants that sell products in only a single category. The bot categorizes the consumer's purchases from the merchants and determines percentages of consumer spending in each category. The bot may obtain a category for purchases from merchants selling a single category of items based on a merchant identifier such as a merchant code. For other merchants, the bot may obtain category information from the merchant or from an analysis of a category code, or a product or service description or identifier. The categories and percentages of the consumer's purchases may be provided by the bot to the consumer or to a third party. The bot may provide special offers and promotions to a consumer based on the compiled category information and percentage spending by the consumer by category.

Automated debundling and categorization of purchases

A device includes a memory configured to store prioritization thresholds. The prioritization thresholds include one or both of threshold values and threshold ranges associated with an age and an amount of exceptions. A processor of the device receives exceptions associated with operation of at least a portion of the plurality of ATMs. For each exception of the plurality of exceptions, the processor determines, based on a comparison of an age property of the exception to an age threshold of the prioritization thresholds, an age score for the exception. The processor determines, based on a comparison of an amount property of the exception to an amount threshold of the prioritization thresholds, an amount score for the exception. Based on the age and amount scores, a prioritization score is determined for the exception which corresponds to a measure of an order in which action should be taken to resolve the exception.

System for dynamic exception prioritization

Aspects of the disclosure relate to performing enhanced exception processing using cognitive automation tools. In some embodiments, a computing platform may receive interaction data identifying one or more actions performed by one or more users in resolving a plurality of exception items associated with an exception queue. Subsequently, the computing platform may train, using a learning engine, a machine learning model to resolve a first exception and a second exception of one or more exceptions based on the interaction data. Based on training the machine learning model, the computing platform may generate one or more configuration commands directing a processing module to implement the machine learning model to process additional exception items associated with the exception queue. The computing platform then may send the one or more configuration commands to the processing module.

Performing enhanced exception processing using cognitive automation tools

An ATM pre-registration tool allows a user to request an amount of cash from an ATM before traveling to that ATM. The pre-registration tool receivers a user's request and determines whether a specified ATM contains the requested cash. If the ATM does not contain the requested cash, the pre-registration tool informs the user that the ATM does not contain sufficient funds to fulfill the user's request. If the ATM contains the requested cash, the pre-registration tool instructs the ATM to reserve that cash for the user.

Automatic teller machine with pre-registration

An ATM exception handler automatically handles certain forms of exceptions. The exception handler receives messages indicating amounts of cash counted and amounts of cash shown at different ATMs. If exceptions are indicated by these messages, the exception handler attempts to reconcile exceptions with each other depending on several factors, such as, the servicer of the ATMs and day of servicing.

Automated exception handling for automatic teller machines

Systems, method, apparatuses, and software are described for automatically detecting defects in financial transactions, automatically determining resolutions to the defects based on historical defect patterns, an interacting with customers to provide information and/or receive instructions regarding defects and how they should be resolved.

Actionable exception alerts

A system for performing secure maintenance on automated machines may include a maintenance management apparatus and an automated machine. The maintenance management apparatus is configured for scheduling the maintenance appointment for the automated machine, in response to scheduling the maintenance appointment and creating and communicating a maintenance security code to the automated machine. The automated machine is configured for receiving a request from a maintenance provider to initiate the maintenance appointment, validating the maintenance provider using the maintenance security code and providing access to a secure item storage unit, determining that the maintenance provider has completed the maintenance appointment, and communicating information associated with the maintenance appointment to the maintenance management apparatus and/or a computing device of the maintenance provider.

Performing secure maintenance processing on an automated machine

Automated machine with self-reconciliation of resources

A system includes a template database storing, for each of a plurality of predefined root causes, a corresponding correspondence template and response form template. Each root cause corresponds to a cause of an exception associated with an ATM. An automatic reconciliation tool determines a exception has occurred associated with a ATM. A set of exception parameters are determined associated with the exception. A party is determined at the service provider with which to correspond in or order to resolve the exception. A root cause of the exception is determined. A correspondence template and a response form template are identified for the determined root cause and used to generate correspondence which includes a description of the exception, instructions for actions to take, and a link configured to provide access to a response form. The response form includes fields for providing a response parameter.

Automatic exception reconciliation

Tracking and processing of resources associated with an automated machine for reconciliation

Embodiments of the invention include systems, methods, and computer-program products for providing an internal digital encoding as an overlay of a data element on a resource distribution instrument for blank space correction. The invention identifies a type of resource distribution instrument with blank space or faded spaces and queue it for encoding. In this way, the encoding may be a layer for a user to view the data element to confirm the resource associated with the resource distribution instrument. The encoding may be embedded into the resource distribution instrument and removable upon external transmission.

Real-time image capture correction device

Remote maintenance initiation and communication for an automated machine

Growing community of inventors

Charlotte, NC, United States of America

Eric Dryer