Bank of America Corporation

Scott Andrew Johnson

Michael Gerald Smith

Brian David Hanson

Saravana Kumar Govindarajan

Michael Scott Hjellming

Hyunmo Koo

Embodiments for extracting data for online account includes systems that receive at least one check images, apply one or more optical character recognition processes to at least a portion of the at least one check image, and convert image based data to text based data. The embodiments further identify check data in the text based data, identify online data from the check data, incorporate at least a portion of the online data into a portion of an online account, and provide the online account portion to a customer.

Check data lift for online accounts

Embodiments of the invention include systems, methods, and computer-program products for lifting metadata from financial documents to allow for automated exception processing. As such, allowing for automated decisions for exception processing to systematically be resolved base on matches between lifted metadata. The exceptions may include one or more irregularities such as bad micro line reads, outdated check stock, or misrepresentative checks that may result in a failure to match the check to an associated account for processing. As such, once an exception is identified during the processing the metadata lifted from the document with the exception may be utilized to search financial records at the financial institution to attempt to identify the correct version of the document. Subsequently, the system may correct the irregularity systematically and automatically.

Data lifting for exception processing

Embodiments of the invention include systems, methods, and computer-program products for lifting metadata from financial documents to allow for automated exception processing. As such, allowing for automated decisions for exception processing to systematically be resolved base on matches between lifted metadata. The exceptions may include one or more irregularities such as bad micro line reads, outdated check stork, or misrepresentative checks that may result in a failure to match the check to an associated account for processing. As such, once an exception is identified during the processing the metadata lifted from the document with the exception may be utilized to search financial records at the financial institution to attempt to identify the correct version of the document. Subsequently, the system may correct the irregularity systematically and automatically.

Embodiments for identifying errors based on data extracted from financial record images includes systems that receive one or more financial record images from a user, apply an optical character recognition process to at least a portion of the one or more financial record images, and identify record data based on the applied optical character recognition process comprising at least a name of a party to the financial record. The systems further identify errors associated with the one or more financial record images based on the record data.

Check data lift for error detection

Embodiments of the invention relate to systems, methods, and computer program products for extracting check data and using the check data for determining a disposition of a check. The system, method, and computer program product are configured to: a) receive an image of a check; b) apply an optical character recognition process to at least a portion of the image of the check; c) convert one or more image portions of the at least a portion of the image to text based data based at least partially on the application; d) identify a date of the check based on the text based data obtained from the one or more image portions; e) compare the date of the check to one or more authorization parameters; and f) provide a disposition of the check based on the comparison of the date of the check to the one or more authorization parameters.

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Atlanta, GA, United States of America

Scott Andrew Johnson