Abstract: Systems for dynamic unauthorized activity detection are provided. In some arrangements, issue data may be received from, for instance, a customer of an enterprise organization. The issue data may include a data file containing metadata associated with a plurality of checks written or issued by the customer. As those checks are cashed, the checks may be evaluated for potential unauthorized activity. Accordingly, check data and/or check image data may be received by the enterprise organization. The check and/or check image data, as well as the metadata, may be analyzed using machine learning to determine whether unauthorized or potential unauthorized activity has occurred. Based on the determination, one or more actions may be identified and executed.

Abstract: Aspects of the disclosure relate to enhanced check processing systems with improved check validation features and enhanced information security. A computing platform may determine whether a correlation between source data and metadata associated with a check exceeds a predetermined correlation threshold. Based on determining that the correlation does not exceed the predetermined correlation threshold, the computing platform may direct an OCR computing system to perform character recognition on the check. Then, the computing platform may determine whether a discrepancy between the metadata and an OCR output from the OCR computing system exceeds a predetermined resolution threshold. In response to determining that the discrepancy between the OCR output and the metadata does not exceed the predetermined resolution threshold, the computing platform may update stored records associated with the check.

Abstract: Embodiments of the present invention provide apparatuses and methods that help validate and process payment instruments for different products, such as but not limited to credit card payments, mortgage payments, or any other type of payment. The payment amount from a payment instrument may be determined from a multiple locations on the payment instrument. In addition, a payment amount may be determined from a remittance document that accompanies the payment instrument, such as a remittance coupon that is mailed along with a check. The amount in the remittance courtesy box, the minimum amount due, the last payment made, and the full balance remaining may all be captured and used to validate the amount on the payment instrument. Moreover, one or more confidence scores for the amounts on the payment instrument and remittance document may be used to validate the payment amount.

Abstract: Systems for controlling scanning devices and capturing image data are provided. In some examples, image data may be received by a computing platform. The image data may be received via a first network and from another computing platform in wired communication with a scanning device. In some arrangements, image quality analysis may be performed and data may be extracted from the image data. The results of the data analysis, as well as the image data and extracted data may be transmitted, via a second network different from the first network, to an associate computing device. In some examples, input received by the associate computing device may be transmitted to the computing platform indicating whether the image is approved or rejected for further processing. If the image is approved, the image data and extracted data may be transmitted, via the second network, to another device for matching and further processing functions.

Abstract: Aspects of the disclosure relate to enhanced check processing systems with improved check validation features and enhanced information security. A computing platform may determine whether a correlation between source data and metadata associated with a check exceeds a predetermined correlation threshold. Based on determining that the correlation does not exceed the predetermined correlation threshold, the computing platform may direct an OCR computing system to perform character recognition on the check. Then, the computing platform may determine whether a discrepancy between the metadata and an OCR output from the OCR computing system exceeds a predetermined resolution threshold. In response to determining that the discrepancy between the OCR output and the metadata does not exceed the predetermined resolution threshold, the computing platform may update stored records associated with the check.

Abstract: Systems for dynamically detecting duplicate items are provided. In some examples, a system, may receive a document, document image, document details or the like. The system may identify at least one other document for comparison to the received document. The system may perform optical character recognition on the document or document image to identify data within one or more standard fields of the document. The detected data may be compared to the at least one other document and, if no matches exist, the document may be identified as not a duplicate. If one or more matches exist, the system may identify x and y coordinates of a location of data within one or more standard fields on the received document. A corresponding location on the at least one other document may be identified based on the x and y coordinates.

Abstract: Systems for controlling scanning devices and capturing image data are provided. In some examples, image data may be received by a computing platform. The image data may be received via a first network and from another computing platform in wired communication with a scanning device. In some arrangements, image quality analysis may be performed and data may be extracted from the image data. The results of the data analysis, as well as the image data and extracted data may be transmitted, via a second network different from the first network, to an associate computing device. In some examples, input received by the associate computing device may be transmitted to the computing platform indicating whether the image is approved or rejected for further processing. If the image is approved, the image data and extracted data may be transmitted, via the second network, to another device for matching and further processing functions.

Abstract: Aspects of the disclosure relate to processing systems that perform item recognition and profile generation for dynamic event processing. A computing platform may receive a first check image containing first check data, and may generate a profile correlating the first check data to a user account. The computing platform may receive a second check image containing second check data. The computing platform may receive profile information corresponding to one or more recognized fields of the second check image, where the profile information includes the information associated with the profile. The computing platform may determine whether a confidence score indicating a correlation between the second check data and the profile exceeds a predetermined correlation threshold. Based on determining that the confidence score does exceed the predetermined correlation threshold, the computing platform may send commands directing an event processing platform to process the second check image based on the profile.

Abstract: Aspects of the disclosure relate to enhanced check processing systems with improved check validation features and enhanced information security. A computing platform may determine whether a correlation between source data and metadata associated with a check exceeds a predetermined correlation threshold. Based on determining that the correlation does not exceed the predetermined correlation threshold, the computing platform may direct an OCR computing system to perform character recognition on the check. Then, the computing platform may determine whether a discrepancy between the metadata and an OCR output from the OCR computing system exceeds a predetermined resolution threshold. In response to determining that the discrepancy between the OCR output and the metadata does not exceed the predetermined resolution threshold, the computing platform may update stored records associated with the check.

Abstract: Aspects of the disclosure relate to enhanced check processing systems with improved check validation features and enhanced information security. A computing platform may determine whether a correlation between source data and metadata associated with a check exceeds a predetermined correlation threshold. Based on determining that the correlation does not exceed the predetermined correlation threshold, the computing platform may direct an OCR computing system to perform character recognition on the check. Then, the computing platform may determine whether a discrepancy between the metadata and an OCR output from the OCR computing system exceeds a predetermined resolution threshold. In response to determining that the discrepancy between the OCR output and the metadata does not exceed the predetermined resolution threshold, the computing platform may update stored records associated with the check.

Abstract: Systems for dynamically detecting duplicate items are provided. In some examples, a system, may receive a document, document image, document details or the like. The system may identify at least one other document for comparison to the received document. The system may perform optical character recognition on the document or document image to identify data within one or more standard fields of the document. The detected data may be compared to the at least one other document and, if no matches exist, the document may be identified as not a duplicate. If one or more matches exist, the system may identify x and y coordinates of a location of data within one or more standard fields on the received document. A corresponding location on the at least one other document may be identified based on the x and y coordinates.

Abstract: Embodiments of the present invention provide apparatuses and methods that help validate and process payment instruments for different products, such as but not limited to credit card payments, mortgage payments, or any other type of payment. The payment amount from a payment instrument may be determined from a multiple locations on the payment instrument. In addition, a payment amount may be determined from a remittance document that accompanies the payment instrument, such as a remittance coupon that is mailed along with a check. The amount in the remittance courtesy box, the minimum amount due, the last payment made, and the full balance remaining may all be captured and used to validate the amount on the payment instrument. Moreover, one or more confidence scores for the amounts on the payment instrument and remittance document may be used to validate the payment amount.

Abstract: Embodiments of the present invention provide apparatuses and methods that help validate and process payment instruments for different products, such as but not limited to credit card payments, mortgage payments, or any other type of payment. The payment amount from a payment instrument may be determined from a multiple locations on the payment instrument. In addition, a payment amount may be determined from a remittance document that accompanies the payment instrument, such as a remittance coupon that is mailed along with a check. The amount in the remittance courtesy box, the minimum amount due, the last payment made, and the full balance remaining may all be captured and used to validate the amount on the payment instrument. Moreover, one or more confidence scores for the amounts on the payment instrument and remittance document may be used to validate the payment amount.

Abstract: A system for optical character recognition pre-verification is provided. The system may review payment documents. The payment documents may include remit stubs and paper checks. The system, utilizing optical character recognition software, may determine dollar amounts on the remit stubs and the paper checks. The optical character recognition software may determine a confidence level of whether the determined amount is the same amount that the writer of the check. If the confidence level is above first predetermined threshold level of confidence and below a second predetermined threshold level of confidence, the system may present an operator with a pre-verification GUI. The pre-verification GUI may include a view of the remit stub, a view of the check, the dollar amount due, a match button and a do not match button. Upon selection of either the match or do not match button, the payment may be processed in another check-processing system.

Abstract: A method for database retrieval is provided. The method may include receiving a history datastore. The method may include receiving a payment, i.e., a paper check. The method may include simultaneously scanning the check into a grayscale image and black and white image. The method may include reviewing each pixel on the black and white image alone and in combination with surrounding pixels to determine an arrangement of shaded pixels. When the arrangement of shaded pixels is determined to be above a predetermined threshold of similarity to a predefined set of characters, the method may determine a subset of characters and store the subset of characters in a memory. The method may include crawling the history datastore to determine information which corresponds to the subset of characters stored in memory and retrieving the corresponding information. The method may include showing the corresponding information and the payment on a GUI.

Abstract: A system for optical character recognition pre-verification is provided. The system may review payment documents. The payment documents may include remit stubs and paper checks. The system, utilizing optical character recognition software, may determine dollar amounts on the remit stubs and the paper checks. The optical character recognition software may determine a confidence level of whether the determined amount is the same amount that the writer of the check. If the confidence level is above first predetermined threshold level of confidence and below a second predetermined threshold level of confidence, the system may present an operator with a pre-verification GUI. The pre-verification GUI may include a view of the remit stub, a view of the check, the dollar amount due, a match button and a do not match button. Upon selection of either the match or do not match button, the payment may be processed in another check-processing system.

Abstract: A method for database retrieval is provided. The method may include receiving a history datastore. The method may include receiving a payment, i.e., a paper check. The method may include simultaneously scanning the check into a grayscale image and black and white image. The method may include reviewing each pixel on the black and white image alone and in combination with surrounding pixels to determine an arrangement of shaded pixels. When the arrangement of shaded pixels is determined to be above a predetermined threshold of similarity to a predefined set of characters, the method may determine a subset of characters and store the subset of characters in a memory. The method may include crawling the history datastore to determine information which corresponds to the subset of characters stored in memory and retrieving the corresponding information. The method may include showing the corresponding information and the payment on a GUI.

Abstract: Embodiments of the present invention provide apparatuses and methods that help validate and process payment instruments for different products, such as but not limited to credit card payments, mortgage payments, or any other type of payment. The payment amount from a payment instrument may be determined from a multiple locations on the payment instrument. In addition, a payment amount may be determined from a remittance document that accompanies the payment instrument, such as a remittance coupon that is mailed along with a check. The amount in the remittance courtesy box, the minimum amount due, the last payment made, and the full balance remaining may all be captured and used to validate the amount on the payment instrument. Moreover, one or more confidence scores for the amounts on the payment instrument and remittance document may be used to validate the payment amount.

Abstract: Embodiments of the present invention provide apparatuses and methods that help validate and process payment instruments for different products, such as but not limited to credit card payments, mortgage payments, or any other type of payment. The payment amount from a payment instrument may be determined from a multiple locations on the payment instrument. In addition, a payment amount may be determined from a remittance document that accompanies the payment instrument, such as a remittance coupon that is mailed along with a check. The amount in the remittance courtesy box, the minimum amount due, the last payment made, and the full balance remaining may all be captured and used to validate the amount on the payment instrument. Moreover, one or more confidence scores for the amounts on the payment instrument and remittance document may be used to validate the payment amount.