US20050139671A1 - Method and system for exception processing of micr documents - Google Patents

Method and system for exception processing of micr documents Download PDF

Info

Publication number
US20050139671A1
US20050139671A1 US10/905,253 US90525304A US2005139671A1 US 20050139671 A1 US20050139671 A1 US 20050139671A1 US 90525304 A US90525304 A US 90525304A US 2005139671 A1 US2005139671 A1 US 2005139671A1
Authority
US
United States
Prior art keywords
correction
document
image
stored data
data field
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US10/905,253
Other languages
English (en)
Inventor
David McGlamery
Kathryn Harrington
Russell Parsons
Raymond Beichler
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Bank of America Corp
Original Assignee
Bank of America Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US10/707,669 external-priority patent/US7165723B2/en
Application filed by Bank of America Corp filed Critical Bank of America Corp
Priority to US10/905,253 priority Critical patent/US20050139671A1/en
Priority to BRPI0418196-4A priority patent/BRPI0418196A/pt
Priority to PCT/US2004/043832 priority patent/WO2005066880A1/fr
Priority to EP04815829A priority patent/EP1700249B1/fr
Priority to CA2546849A priority patent/CA2546849C/fr
Assigned to BANK OF AMERICA CORPORATION reassignment BANK OF AMERICA CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: HARRINGTON, KATHRYN GERRALD, MCGLAMERY, DAVID CRAIG, PARSONS, RUSSELL M., BEICHLER, RAYMOND G.
Publication of US20050139671A1 publication Critical patent/US20050139671A1/en
Priority to US13/672,060 priority patent/US8864029B2/en
Abandoned legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/98—Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns

Definitions

  • MICR magnetic ink character recognition
  • Check processing and sorting systems have also been developed in which a check or similar MICR document has its image captured and stored electronically. Such an image can be archived so that it is indexed or joined with its accompanying data from a MICR read.
  • MICR documents have also been captured photographically for storage in microfilm format. This feature is being removed as electronic image processing and retrieval replaces the use of microfilm.
  • the typical high-speed processing of documents having MICR data includes reading and storing a MICR line, endorsing the document with applicable information, imaging the item so that the image can be stored in an archive facility, and sorting items for processing. Items for which the MICR reads properly, and for which no errors are detected in the data, sort to pockets for routine processing. Any items with a failed MICR read or an exception are typically sorted to a reject pocket and are handled through an exception process.
  • the exception process typically includes attempting to read the MICR with an alternate, slower type of reader to achieve a better read rate, and if that fails, manually reviewing the paper document and keying in the appropriate data.
  • FIG. 1 is a flow chart which illustrates the current process for processing MICR documents at many financial institutions.
  • various steps in the process are represented by process blocks.
  • Process blocks can also represent stopping points or paths for different types of items.
  • items with MICR data are loaded into a high-speed processor.
  • the MICR data on the item is recognized and captured by a read head.
  • the data is transferred to a file for storage with indicators that signify which fields have apparently read correctly, and which ones have failed to read.
  • Logic failures are also detected. A logic failure occurs when data has apparently been captured successfully, but makes no sense, so it must be assumed that the data as captured is erroneous.
  • FIG. 1 is a flow chart which illustrates the current process for processing MICR documents at many financial institutions.
  • various steps in the process are represented by process blocks.
  • Process blocks can also represent stopping points or paths for different types of items.
  • items with MICR data are loaded into a high-speed processor.
  • the MICR data on the item is recognized and captured by
  • items also typically pass through an endorsement feature, which typically puts a date, location of scan, and other data related to the financial institution performing the processing.
  • the item optionally can move through a microfilm unit to have a photographic image captured. Next, the item moves under and over image scanners. An image of the item (front and back) is created and stored.
  • Transit items are checks drawn on other financial institutions, and are pocketed for delivery to those institutions.
  • items can also be sorted to “truncation pockets” (not shown) for items to be stored for a retention period and then discarded in accordance with new practices allowing an image rather than physical items be used as long-term documentation of a transaction.
  • the data correction process, 108 also results in items eventually being sorted into corrected, on-us items 116 , and corrected, transit items, 118 . Items from the high-speed process are then merged, eventually, with items from the correction or “reject repair” process at block 120 . Thus, both the reject items and the good items, are typically eventually sorted to their destinations, shown consolidated at blocks 122 and 124 .
  • the process shown in FIG. 1 may include both a “prime pass” a subsequent pass, also called a “subpass” or a “rehandle,” if on us or especially transit items need to ultimately pocket into more physical pockets than are available on the sorting equipment. For example, if items need to pocket into, say, 50 transit item pockets for 50 different destination banks, and a sorter only has 30 pockets available for transit items, a subpass or rehandle is needed. In such a case, for example, some items might first be pocketed into a pocket that covers multiple destinations such as all the banks in a certain state or region. Then, the sorting process is repeated on these items to finally separate them into individual pockets destined for each bank. Errors can occur and the correction process can be invoked on either the prime pass or the subpass.
  • the correction process includes the use of check mender equipment to place correction strips on the bottom of each document so new, readable MICR can be placed on each document. The resulting delay considerably reduces the processing time for each batch of MICR items processed by a financial institution.
  • the present invention can improve the processing time for large numbers of MICR encoded documents within a financial institution.
  • the number of items which are pocketed as rejects due to digit errors can be significantly reduced. This reduction can be accomplished due to the realization that only the routing/transit field from the MICR data of an item needs to be read correctly in order for it to be properly pocketed. Additionally, speed and efficiency of handling documents with exceptions can be improved. Correction for documents which are pocketed as rejects due to digit errors is improved through the use of an image based correction process which can be referred to herein as MICR image correction or “MIC.”
  • MICR image correction MICR image correction
  • Embodiments of the invention can also be used to correct image data received electronically when paper documents have been scanned elsewhere. Embodiments of the invention can additionally be used to process documents with other exceptions, such as a dollar amount that is above a threshold parameter.
  • a method of processing a MICR encoded document and/or its image, where the document is subject to an exception that may be related to a stored data field includes the receiving of an image of the document.
  • the document can be routed to a destination subject to a determination that the exception does not prevent the routing of the document.
  • a verification process can be performed on at least one portion of an image of the document, wherein the at least one portion will typically correspond to stored data related to the exception.
  • a correction can be applied to a stored data field based at least in part on the verification process. In a prime pass, this correction can involve the MIC process, or other exception handling.
  • a master file is maintained to store information about corrections applied, and the master file can be used to make corrections in subsequent passes of the same items.
  • exceptions such as digit errors in stored data fields can be corrected by an optical character recognition (OCR) process that is performed on the stored, electronic image.
  • OCR optical character recognition
  • the portion of the document to which the OCR process is applied corresponds to the stored data field.
  • the OCR process is performed on a snippet of the document that includes the account number.
  • a process according to an embodiment of the invention can include routing the document to a destination pocket and subsequently to a destination subject to a determination that the exception(s) or error(s) do(es) not prevent the routing of the document.
  • an error or other exception does not prevent the routing of the document if it is not related to the routing/transit field.
  • Embodiments of the correction process can be applied to image data received from another institution which scanned the MICR documents.
  • the OCR process result is used to apply a correction to the error in the stored data field.
  • This correction can be based on a comparison of the result of the OCR process and the digits within the stored data field which have been captured, albeit only partially or incorrectly. If a determination is made that the correction cannot be successfully determined by the comparison with the result of the OCR process, the image and MICR data is displayed on a user terminal, for manual correction, albeit by reference to an image of the document, rather than the document itself.
  • an improved correction process can be applied when an error appears in a stored data field which has two or more corresponding areas within the image of the item. For example, if the error is in an amount, two results of an OCR process can be used. One result can be obtained from optically scanning the MICR line, and another result can be obtained from optically scanning a written amount. In some cases, still another OCR process result can be obtained if the amount is listed both numerically, and written out.
  • exceptions can be defined programmatically. For example, an exception can be defined for when the dollar amount of an item exceeds a pre-selected threshold parameter. Such an item can then be verified using its image. This verification can be accomplished either using the MIC process and treating the item as if the amount has an error, or by immediate, operator verification.
  • a system for processing MICR encoded documents can include a sorter to sort and read the documents and route documents to a destination pocket when an exception condition does not prevent the routing.
  • a sorter can be operatively interconnected with a computing platform to provide, among other elements, the OCR processing and apply corrections to the error in the stored data field based on a comparison of the result of an OCR process and the data in the stored field.
  • the computing platform can also provide for the storage and routing of the images for manual verification and/or correction at user terminals as required.
  • Computer program instructions, computer programs or computer code, possibly in the form of a computer program product can implement portions of the invention.
  • These computer program code instructions can operate a computing platform which controls a sorter and other hardware within the system.
  • the handling of physical items in order to process exceptions or perform reject repair can be reduced or eliminated.
  • many items having exceptions, specifically exceptions which do not prevent the routing of the items can be routed to a destination and any verification or correction required, whether automated or manual, can be performed using only the images of the items. Additionally, data referring to documents that were scanned elsewhere can be verified and/or corrected. Thus, overall check processing time can be reduced.
  • FIG. 1 is a flow diagram which illustrates a process in which all MICR encoded items having MICR failures or other errors are routed to a reject pocket for a physical data correction process.
  • FIG. 2 is a flow diagram which illustrates the processing of items according to embodiments of the invention.
  • FIG. 3 is a flowchart which illustrates further details of a method of processing items according to some embodiments of the invention.
  • FIG. 4 is a flowchart, which illustrates a method of subpass or rehandle processing of items according to some embodiments of the invention.
  • FIG. 5 is a block diagram of a system which handles MICR encoded items according to some embodiments of the invention.
  • this terminology refers to the idea of correcting information about MICR encoded documents which is stored in data structures for retrieval and manipulation. There are many ways to design a system to accommodate the storage of this information, as well as the storage of electronic images of documents such as checks. Reference will be made herein to updating strings and user bytes which either are or refer to such fields in systems which process MICR documents such as checks.
  • this terminology refers to information stored in what is commonly known as a “check image management system” (CIMS) and within a “check processing control system” (CPCS).
  • CIMS check image management system
  • CPCS check processing control system
  • check images and index information referring to the check images can be stored in a single file according to an industry standard “check image export” (CIE) format.
  • CIE has been used for many years by many banks to archive check images for their own internal use.
  • Images and index information in such a system can be stored in the same file or separated.
  • the index information is separated and stored in an electronic cash letter (ECL) for communicating between financial institutions for the purpose of settlement.
  • Index information can also be stored with electronic images in an “image cash letter” (ICL) to provide for the truncation of the paper documents.
  • ECL electronic cash letter
  • ICL image cash letter
  • exception is any condition occurring when a document is processed that causes a verification process to take place as described herein.
  • a verification process can be synonymous with a correction process as in many cases, this exception will be a MICR digit read error.
  • embodiments of the present invention provide for other exceptions to be defined programmatically.
  • high-dollar items, relative to a pre-set threshold amount can be defined as exception items and verified or corrected in the same manner as if there were a read error in the amount of the item, for example, if there were a desire to verify checks from certain drawers or to certain payees. In such a case, many items may in fact be correct, but a verification process is used in part to determine this with relative certainly.
  • FIG. 2 is a flow diagram and process diagram which illustrates the flow, 200 , of items according to some embodiments of the invention.
  • FIG. 2 also shows some of what happens to stored MICR data according to some embodiments of the invention. Further detail on how the data is handled is covered in FIGS. 3, 4 and 4 .
  • MICR encoded items are loaded into a high-speed processor. As before, the processor reads the MICR data and the data is transferred to a file for storage. On at least the prime pass, an item is endorsed, an image is created and stored, and in some cases, a photographic image is made for microfilm purposes.
  • Block 203 represents an incoming image file from another financial institution. The logic for the correction process is the same as with paper processing.
  • An image file would be processed in a single pass.
  • the incoming information may only be electronic as the future of check processing changes from paper to image.
  • the MICR data for the images as captured by the sending bank may still contain MICR digits errors from the sending bank MICR capture equipment.
  • the correction process will still follow the logic as described in FIG. 2 using the same image and image technology, only without on-us paper and without any transit images or items.
  • Blocks 204 and 205 of FIG. 2 together determine whether the items qualifies for automated exception processing. As before, a determination is made at block 204 as to whether the item reads or was read good. If the item reads good, a determination is made at block 205 as to whether it should be handled as a programmed exception. In this example, the exception would be that the value of the item exceeds a pre-set threshold parameter. If the item exceeds the parameter, it is treated as a reject and the image is assigned a reject user byte. At this point, if desired, it can handled by the MIC process described herein and further discussed below. Alternatively, it can be immediately sent for manual correction by essentially treating it as a physical reject.
  • FIG. 2 This may be desired, for example, if mishandling of high-dollar items were viewed as a significant risk.
  • FIG. 2 These alternative processing paths are shown in FIG. 2 by dashed lines.
  • a locally sorted paper item reads good, it is pocketed at block 206 .
  • Pockets in the example of FIG. 2 eventually break down into a sort of items into on-us items at block 208 , and transit items at block 210 .
  • items can also be pocketed into truncation pockets (not shown).
  • good items also cause a valid user byte to be generated in the CIMS/CPCS system at block 212 .
  • the item is routed to the traditional physical reject process which commences at block 216 and the item is assigned a reject user byte. If a digit error has occurred, that is an error in which a digit within a field was not able to be read, the item is again routed to the physical reject process if the error occurs in the routing/transit (R/T) field and the item is assigned a reject user byte. In such a case, the item cannot be sorted since the R/T field determines the final destination of the item.
  • R/T routing/transit
  • the item can still be sorted and pocketed at high-speed.
  • the error as determined at block 214 is found not to be a logic or routing/transit failure, the item is sorted into a pocket at block 206 , in the same manner as a good item.
  • An on-us or transit reject user byte will then be assigned to the item indicating the item has sorted good, but needs further attention for corrective purposes.
  • the MICR image correction process takes place.
  • the process can be the same regardless of where the paper item was first read and sorted, and regardless of whether the item is in its prime pass or a subpass.
  • This process can also be used to verify programmed exceptions, such as high-dollar items, by treating them as if they had a digit error. Thus, it may still be referred to as a correction process.
  • CIMS/CPCS systems will recognize all the items that have a on-us or transit reject user byte. It is or was known at this point into which pocket the item needs to be or has been sorted, since the information needed to sort the item is generally determined from the routing/transit number.
  • items are pocketed as on-us items, 208 , which include good on-us items and on-us rejects, and transit items, 210 , which include good transit items and transit rejects.
  • on-us items 208
  • transit items 210
  • a truncation pocket will include good truncated items and truncation rejects, as embodiments of the invention can be applied to items to be truncated as well as to transit and on-us items.
  • Master file 219 can be created and accessed as part of the MIC process.
  • a master file for a particular unit of work (UOW) is created when a MIC process is initiated on the prime pass.
  • the file is updated each time a transit or any other type of item which will be rehandled is corrected through the MIC process.
  • the information stored in the master file including any indexing, MICR data, and sequence numbers will be stored until the subpass, where the same rejects, and possibly new rejects will typically be encountered. At this point, the rehandle rejects are reviewed and the master file is checked to determine if each reject was previously rejected. If so, the item is corrected using the original MIC information from the master file.
  • the rehandle reject will go through the same MIC correction process that a prime pass reject goes through. Note that there can be multiple subsequent passes or rehandles for a unit of work, in which case a second or third rehandle will have access to data in the master file not only from the prime pass, but also from previous subpasses.
  • paper rejects are handled with a physical exception pocketing and correction process at block 220 .
  • This process can be used to correct paper rejects, or to verify exceptions, such as for high-dollar items, which were routed here after processing at block 205 .
  • This process results in on-us items pocketed at block 222 and transit items pocketed at block 224 . In each case, these items will now have good data stored within CIMS and CPCS. These items are merged with the high-speed sorted items at block 226 .
  • the documents are stored in on-us pockets 228 and transit pockets 230 , where in each case the physically pocketed items include both good items and reject items.
  • the documents can now proceed to their destinations and any MICR data correction necessary can be provided through the high-speed MICR image correction process according to embodiments of the invention.
  • MICR data is frequently exchanged via an electronic cash letter in parallel with the presentment of paper documents.
  • a financial institution to which transit items are to be presented will be able to identify and acquire the correct MICR information notwithstanding the fact that the paper documents may not read error free.
  • FIG. 3 is a flow chart illustrating a process, 300 , for MIC reject repair in an example system based on CIMS and CPCS.
  • the data fields being repaired can correspond to paper items that were first sorted either locally, or at another institution.
  • the process begins at block 301 .
  • a determination is made as to whether the current pass is a prime pass entry reject or a rehandle entry reject. If a rehandle, processing proceeds to block 303 , which specifies the process detailed in FIG. 4 , discussed below. If prime pass, processing proceeds to block 304 .
  • the appropriate image and MICR information is retrieved from CIMS and CPCS.
  • This MICR information includes the various stored data fields, and what in CIMS and CPCS parlance is referred to as a “string” that includes a “user byte.”
  • the string designates an item as valid, as an on-us reject, as a transit reject.
  • the string can also designate the item as simply a reject if it is a paper reject requiring paper reject processing in the manner of the prior art.
  • an optical character recognition process is performed on a snippet from the image. On a first pass, in example embodiments, this snippet is at least one portion of the image, the portion which includes the MICR printed numbers which correspond to the stored data field in question.
  • the OCR process reads the snippet optically, as opposed to with a MICR read head.
  • the result of the OCR process is compared with the MICR data in the stored data field to determine the likely, correct content of the field. This determination can be made in such a way that the probability that the field is actually supposed to be what is determined can be assigned a confidence level.
  • a system can be set up to test for a certain minimum confidence level as shown at block 308 , before allowing a correction to be applied to the stored data field.
  • the validity of the correction proposed is subject to having been successfully determined by the comparison, within a given confidence. This forces the system to only allow the MIC error correction if there is a substantial likelihood that the error correction will be successful in that the correct contents of the stored data field will be determined and restored.
  • required confidence levels can be set by the operators of a system. Assuming the minimum read confidence level is passed at block 308 , a reject repair string based on the comparison of the OCR result and the data in the stored field is updated at block 310 .
  • a failure to match an item against the master file will result in correction as if the item was a prime pass item, at block 310 , as will be understood through the fact that the MIC correction process is referenced in FIG. 4 , discussed below.
  • the process repeats if there are additional errors to be corrected. If not, as in the case where all needed reject repair items have been corrected, the image repair string(s) are merged with the MICR data at block 314 . In example embodiments, all the corrected MICR data is then merged into CIMS/CPCS at block 316 .
  • a test is made at block 318 to determine if the stored data field with the failure corresponds to the amount field for the item. If not, the image and the failed MICR data are sent to a workstation for image-based repair at block 320 . A repair string is updated based on operator keying at block 322 . The process then returns again to block 312 where it repeats if there are additional items to be corrected. Note that in this case, an operator only needs to correct one item at a time, and furthermore works with an image of the document rather than the document itself. Thus, within the steps shown in FIG. 3 , working with paper rejects has been completely eliminated.
  • At least one additional OCR process result is obtained from a portion of the image at block 324 .
  • at least two portions of the image have an OCR process performed for a comparison of the result of an OCR process with the contents of a stored data field when the field corresponds to an amount.
  • the OCR process is performed on the printed MICR and on a written, numerical amount. All three of these pieces of information can be compared at block 326 . Note that depending on the OCR algorithms and processes used, in most cases it is possible to perform an OCR process on a written out amount as well as a printed numerical amount.
  • the result arrived at by this comparison is also checked against a minimum read confidence level. If the minimum level is achieved, the reject repair string data is updated at block 310 . Otherwise, the image is sent to a workstation for image-based repair at block 320 , as previously described.
  • OCR algorithms can be applied to the process described in FIG. 3 to achieve the desired result.
  • Specific OCR products are available that have been designed to optically determine and read printed MICR characters, handwriting, printed amounts, etc. It is also known how to compare the results of more than one algorithm, or the results of an algorithm with stored values and make determinations within certain confidence intervals. One way of accomplishing this is via a voting algorithm.
  • Optical character recognition is a mature art and it is readily understood in the data processing arts how to apply it to achieve various results.
  • Various companies produce OCR products and systems for varied applications, for example, ScanSoft, Inc. of Massachusetts, in the United States.
  • FIG. 4 illustrates a rehandle, subsequent pass, or “subpass” process, 400 , according to example embodiments of the invention.
  • Each rehandle exception item including digit error rejects other exceptions, for example, high-dollar items, are input to the process as shown at block 402 .
  • the item is compared with the data in master file 406 in an attempt to auto-correct by updating a stored data field related to the exception using data from the prime pass (or a previous subpass). If the auto-correct process is successful at decision block 408 , processing branches to block 410 , where a determination is made as to whether the item is the last item in the unit of work. If so, corrected strings are built in CPCS at block 412 and the process ends. If not, processing branches back to block 404 where another auto-correct is attempted on the next item in the unit.
  • FIG. 5 presents a system and network block diagram, which illustrates the operating environment for at least some example embodiments of the invention.
  • Incoming paper items in this case checks
  • the documents are sorted and read at a high-speed sorter, 504 , for example, an IBM 3890 high-speed sorter.
  • the checks pass through a capture area where read heads capture the MICR data and organize it into stored data fields.
  • This data is transmitted to computer system 506 via connectivity 508 .
  • This connectivity can be provided by any of various types of networks, for example, IBM System Network Architecture (SNA), an internal Internet protocol (IP) network, or a local area network (LAN).
  • SNA IBM System Network Architecture
  • IP Internet protocol
  • LAN local area network
  • Computing system 506 stores the MICR data, master files, and other required information on fixed storage media 510 .
  • boxed transit items are shown at 516 and boxed on-us items are shown at 518 .
  • Boxed truncation items (not shown) can also be included.
  • Items which cannot be routed for example paper reject 520 , are routed to a low-speed document processor, 522 , for processing as a paper reject.
  • items that have been sorted for delivery to appropriate destinations, 516 and 518 can now proceed through the normal process, while the data is corrected using techniques based in computing system 506 and images stored in fixed storage 510 .
  • the techniques previously discussed relative to creating repair strings based on optical character recognition results and comparisons are directed and controlled by computer program code 524 , at least in part stored in and read from fixed storage 526 .
  • a number of operator terminals, 528 are interfaced to computer system 506 by Ethernet 530 .
  • FIG. 5 is provided as an illustrative example only.
  • document sorting machines that can be used to provide the sorting/capture/imaging functions.
  • Most sorters typically have conventional document diverting mechanisms which route the documents to the various pockets.
  • Sorting instructions to cause the documents to be routed are received from a processor within the sorting machine, or from an external computing platform, or sometimes both depending on the particular operations being carried out at any particular time.
  • the computing platform can be a mainframe, server, workstation, and even a desktop or personal computer given the processing power that has been achieved in such devices in recent years.
  • some embodiments of the invention can be implemented through extensive use of computer program products, or computer program instructions to carry out methods according to the invention. These instructions in combination with a computing platform processor and other devices form the means to carry out embodiments of the invention.
  • These computer program instructions may be part of a computer program or multiple programs which are supplied as a computer program product.
  • Such a computer program product may take the form of a computer readable media that allows computer program instructions to be loaded into computing platforms.
  • a computer program product in the form of a medium containing the appropriate instructions is shown as removable storage medium 532 .
  • computer program instructions which implement the invention can also be supplied over a network.
  • the medium is a stream of information being retrieved when the computer program product is downloaded.
  • Computer programs which implement embodiments of the invention can reside on any medium that can contain, store, communicate, propagate, or transport the program for use by or in connection with any computing platform or instruction execution system, apparatus, or device.
  • the medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system or device.
  • the computing platform, storage mediums, connectivity, and sorting machine can all be combined into one large device and the computer program instructions could be stored within an optical, magnetic, or electronic module type storage devices.
  • strings within a CPCS system are updated and managed according to some example embodiments of the invention.
  • the invention can be implemented in other types of systems. Detail on CPCS and CIMS is presented as an example only.
  • good items that are sorted to pockets build an “I-String” within CPCS with a valid user byte. Items with digit errors that do not prevent sorting and all paper reject items build on the same “I-String” but, with other types of CPCS user bytes.
  • Transit reject string specified images and data will download to the OCR process. Certain digit errors will be corrected via this process if the logic can correct a failed digit with a specified confidence level.
  • on-us reject string specified images and data download to the OCR process. Items with digits failing in the amount field will go through an additional OCR/MICR/written amount verification process to determine if handwriting, printed numbers, or both can create a good read. Images and data for remaining items will download to workstations for digit correction via key entry by an operator referencing an image rather than a paper document.
  • on-us items go through the process of the invention with a low priority compared to transit items.
  • the “I-String” can be merged with a repair string(s) to create an “Adjusted I-String” or an “M-String” indicating the items have been corrected.
  • a final merge for all items in a batch waits until reject D-string specified items have been corrected.
  • employing an embodiment of the invention reduces the number of reject D-string items, the time involved in processing the batch is also reduced.

Landscapes

  • Engineering & Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Character Discrimination (AREA)
US10/905,253 2003-12-31 2004-12-22 Method and system for exception processing of micr documents Abandoned US20050139671A1 (en)

Priority Applications (6)

Application Number Priority Date Filing Date Title
US10/905,253 US20050139671A1 (en) 2003-12-31 2004-12-22 Method and system for exception processing of micr documents
BRPI0418196-4A BRPI0418196A (pt) 2003-12-31 2004-12-30 método para processar pelo menos imagem de documento codificado de reconhecimento de caractere de tinta magnética, e, aparelho para processar documentos codificados de reconhecimento de caractere de tinta magnética
PCT/US2004/043832 WO2005066880A1 (fr) 2003-12-31 2004-12-30 Procede et systeme de traitement d'exception de documents micr
EP04815829A EP1700249B1 (fr) 2003-12-31 2004-12-30 Procede et systeme de traitement d'exception de documents micr
CA2546849A CA2546849C (fr) 2003-12-31 2004-12-30 Procede et systeme de traitement d'exception de documents micr
US13/672,060 US8864029B2 (en) 2003-12-31 2012-11-08 Method and system for exception processing of MICR documents

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US10/707,669 US7165723B2 (en) 2003-12-31 2003-12-31 System and method for the processing of MICR documents that produce read errors
US10/905,253 US20050139671A1 (en) 2003-12-31 2004-12-22 Method and system for exception processing of micr documents

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US10/707,669 Continuation-In-Part US7165723B2 (en) 2003-12-31 2003-12-31 System and method for the processing of MICR documents that produce read errors

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US13/672,060 Continuation US8864029B2 (en) 2003-12-31 2012-11-08 Method and system for exception processing of MICR documents

Publications (1)

Publication Number Publication Date
US20050139671A1 true US20050139671A1 (en) 2005-06-30

Family

ID=34753174

Family Applications (2)

Application Number Title Priority Date Filing Date
US10/905,253 Abandoned US20050139671A1 (en) 2003-12-31 2004-12-22 Method and system for exception processing of micr documents
US13/672,060 Expired - Lifetime US8864029B2 (en) 2003-12-31 2012-11-08 Method and system for exception processing of MICR documents

Family Applications After (1)

Application Number Title Priority Date Filing Date
US13/672,060 Expired - Lifetime US8864029B2 (en) 2003-12-31 2012-11-08 Method and system for exception processing of MICR documents

Country Status (5)

Country Link
US (2) US20050139671A1 (fr)
EP (1) EP1700249B1 (fr)
BR (1) BRPI0418196A (fr)
CA (1) CA2546849C (fr)
WO (1) WO2005066880A1 (fr)

Cited By (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060186194A1 (en) * 2004-06-18 2006-08-24 Richardson Joseph L Image exchange without full micr qualification
US20070098244A1 (en) * 2005-11-03 2007-05-03 Ncr Corporation Method of processing misoriented document items in an image-based check processing system
US20070136198A1 (en) * 2005-12-14 2007-06-14 Pitney Bowes Incorporated Method of facilitating the tracing and/or auditing of operations performed during check image processing
EP2078278A2 (fr) * 2006-10-26 2009-07-15 Bank of America Corporation Procédé et système pour une confidentialité d'image de chèque améliorée
US20090263004A1 (en) * 2006-01-30 2009-10-22 Kari Hawkins Prioritized exception processing system and method with in a check processing system and method
US20090300068A1 (en) * 2008-05-30 2009-12-03 Tang ding-yuan System and method for processing structured documents
US20100014744A1 (en) * 2008-07-16 2010-01-21 Toshiba Tec Kabushiki Kaisha Data reading apparatus, method of controlling the same, and printer
US7747061B2 (en) 2006-12-08 2010-06-29 Wells Fargo Bank, N.A. Method and apparatus for any which way check acceptance
US20100258629A1 (en) * 2009-04-14 2010-10-14 Document Capture Technologies, Inc. Infrared and Visible Imaging of Documents
US20110172808A1 (en) * 2008-09-22 2011-07-14 Gui Fu Paper sheet management system, paper sheet mangement apparatus, paper sheet management method, and paper sheet management program
US8023718B1 (en) * 2007-01-16 2011-09-20 Burroughs Payment Systems, Inc. Method and system for linking front and rear images in a document reader/imager
US8023717B1 (en) * 2007-01-16 2011-09-20 Burroughs Payment Systems, Inc. Method and system for processing backwards documents in a document reader/imager
US20120166342A1 (en) * 2006-01-30 2012-06-28 Reid Scott T System and method for processing checks and check transactions
US20120177295A1 (en) * 2011-01-07 2012-07-12 Yuval Gronau Document comparison and analysis for improved OCR
US20120177291A1 (en) * 2011-01-07 2012-07-12 Yuval Gronau Document comparison and analysis
US20140052697A1 (en) * 2012-08-20 2014-02-20 Bank Of America Corporation Correction of check processing defects
US8660957B2 (en) 2006-01-30 2014-02-25 Solutran Control features in a system and method for processing checks and check transactions
US9070010B2 (en) 2012-08-06 2015-06-30 Bank Of America Corporation Image check content estimation and use
US9721236B2 (en) 2012-08-09 2017-08-01 Bank Of America Corporation Distributed processing of a check image
US10049350B2 (en) 2015-06-25 2018-08-14 Bank Of America Corporation Element level presentation of elements of a payment instrument for exceptions processing
US10115081B2 (en) 2015-06-25 2018-10-30 Bank Of America Corporation Monitoring module usage in a data processing system
US10229395B2 (en) 2015-06-25 2019-03-12 Bank Of America Corporation Predictive determination and resolution of a value of indicia located in a negotiable instrument electronic image
US10373128B2 (en) 2015-06-25 2019-08-06 Bank Of America Corporation Dynamic resource management associated with payment instrument exceptions processing
US10664811B2 (en) 2018-03-22 2020-05-26 Bank Of America Corporation Automated check encoding error resolution

Families Citing this family (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8249396B2 (en) 2006-09-18 2012-08-21 Bank Of America Corporation System and methods for handling financial document returns and processing exceptions
EP2826003A4 (fr) 2012-03-12 2016-09-21 Top Image Systems Ltd Dispositif portable pour transactions de documents financiers
US9305228B1 (en) 2015-03-20 2016-04-05 Bank Of America Corporation Processing damaged items using image data lift
US9626596B1 (en) 2016-01-04 2017-04-18 Bank Of America Corporation Image variation engine
US9824299B2 (en) 2016-01-04 2017-11-21 Bank Of America Corporation Automatic image duplication identification
US10437880B2 (en) 2016-02-08 2019-10-08 Bank Of America Corporation Archive validation system with data purge triggering
US10437778B2 (en) 2016-02-08 2019-10-08 Bank Of America Corporation Archive validation system with data purge triggering
US10460296B2 (en) 2016-02-08 2019-10-29 Bank Of America Corporation System for processing data using parameters associated with the data for auto-processing
US9823958B2 (en) 2016-02-08 2017-11-21 Bank Of America Corporation System for processing data using different processing channels based on source error probability
US9952942B2 (en) 2016-02-12 2018-04-24 Bank Of America Corporation System for distributed data processing with auto-recovery
US10067869B2 (en) 2016-02-12 2018-09-04 Bank Of America Corporation System for distributed data processing with automatic caching at various system levels
US10810664B2 (en) 2017-06-20 2020-10-20 Bank Of America Corporation Item processing exception configurable pipeline

Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3737628A (en) * 1971-06-11 1973-06-05 Automatic Corp Automatically programmed test grading and scoring method and system
US4417136A (en) * 1981-08-05 1983-11-22 Ncr Canada Ltd - Ncr Canada Ltee Method and apparatus for improving bank operation productivity
US4555617A (en) * 1982-12-23 1985-11-26 Ncr Canada Ltd.-Ncr Canada Ltee Concurrent, image-based, reject-re-entry repair system and method
US5007100A (en) * 1989-10-10 1991-04-09 Unisys Corporation Diagnostic system for a parallel pipelined image processing system
US5257328A (en) * 1991-04-04 1993-10-26 Fuji Xerox Co., Ltd. Document recognition device
US5678046A (en) * 1994-11-18 1997-10-14 The Chase Manhattan Bank, N.A. Method and apparatus for distributing files on a file storage device
US5679940A (en) * 1994-12-02 1997-10-21 Telecheck International, Inc. Transaction system with on/off line risk assessment
US5740271A (en) * 1994-07-27 1998-04-14 On-Track Management System Expenditure monitoring system
US5754673A (en) * 1995-06-19 1998-05-19 Ncr Corporation Document image processing system including a first document path for the automated processing of documents and a second document path for the processing of documents requiring operator correction
US20010051921A1 (en) * 2000-02-01 2001-12-13 Garner Andrew J. Image enabled reject repair for check processing capture
US6351553B1 (en) * 1999-03-03 2002-02-26 Unisys Corporation Quality assurance of captured document images
US20040133516A1 (en) * 2000-04-28 2004-07-08 Zions Bancorporation Methods and systems for processing financial instrument deposits

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4523330A (en) 1982-12-23 1985-06-11 Ncr Canada Ltd - Ncr Canada Ltee Banking system and method
US6115509A (en) * 1994-03-10 2000-09-05 International Business Machines Corp High volume document image archive system and method
JPH09282387A (ja) * 1996-04-15 1997-10-31 Glory Ltd 帳票処理装置
US6654487B1 (en) 2000-03-03 2003-11-25 Charles H. Downs, Jr. Character recognition, including method and system for processing checks with invalidated MICR lines

Patent Citations (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3737628A (en) * 1971-06-11 1973-06-05 Automatic Corp Automatically programmed test grading and scoring method and system
US4417136A (en) * 1981-08-05 1983-11-22 Ncr Canada Ltd - Ncr Canada Ltee Method and apparatus for improving bank operation productivity
US4555617A (en) * 1982-12-23 1985-11-26 Ncr Canada Ltd.-Ncr Canada Ltee Concurrent, image-based, reject-re-entry repair system and method
US5007100A (en) * 1989-10-10 1991-04-09 Unisys Corporation Diagnostic system for a parallel pipelined image processing system
US5257328A (en) * 1991-04-04 1993-10-26 Fuji Xerox Co., Ltd. Document recognition device
US5740271A (en) * 1994-07-27 1998-04-14 On-Track Management System Expenditure monitoring system
US6181837B1 (en) * 1994-11-18 2001-01-30 The Chase Manhattan Bank, N.A. Electronic check image storage and retrieval system
US5917965A (en) * 1994-11-18 1999-06-29 The Chase Manhattan Bank, N.A. Method and apparatus for storing images of documents having magnetic ink code line
US5940844A (en) * 1994-11-18 1999-08-17 The Chase Manhattan Bank, Na Method and apparatus for displaying electronic image of a check
US5963659A (en) * 1994-11-18 1999-10-05 The Chase Manhattan Bank, N.A. Method and apparatus for correcting erroneously decoded magnetic ink characters
US5678046A (en) * 1994-11-18 1997-10-14 The Chase Manhattan Bank, N.A. Method and apparatus for distributing files on a file storage device
US6574377B1 (en) * 1994-11-18 2003-06-03 The Chase Manhattan Bank Electronic check image storage and retrieval system
US5679940A (en) * 1994-12-02 1997-10-21 Telecheck International, Inc. Transaction system with on/off line risk assessment
US5754673A (en) * 1995-06-19 1998-05-19 Ncr Corporation Document image processing system including a first document path for the automated processing of documents and a second document path for the processing of documents requiring operator correction
US6351553B1 (en) * 1999-03-03 2002-02-26 Unisys Corporation Quality assurance of captured document images
US20010051921A1 (en) * 2000-02-01 2001-12-13 Garner Andrew J. Image enabled reject repair for check processing capture
US20040133516A1 (en) * 2000-04-28 2004-07-08 Zions Bancorporation Methods and systems for processing financial instrument deposits

Cited By (34)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7757938B2 (en) * 2004-06-18 2010-07-20 Digicor Llc Image exchange without full MICR qualification
US20060186194A1 (en) * 2004-06-18 2006-08-24 Richardson Joseph L Image exchange without full micr qualification
US20070098244A1 (en) * 2005-11-03 2007-05-03 Ncr Corporation Method of processing misoriented document items in an image-based check processing system
US20070136198A1 (en) * 2005-12-14 2007-06-14 Pitney Bowes Incorporated Method of facilitating the tracing and/or auditing of operations performed during check image processing
US8660957B2 (en) 2006-01-30 2014-02-25 Solutran Control features in a system and method for processing checks and check transactions
US8589301B2 (en) * 2006-01-30 2013-11-19 Solutran System and method for processing checks and check transactions
US20090263004A1 (en) * 2006-01-30 2009-10-22 Kari Hawkins Prioritized exception processing system and method with in a check processing system and method
US20120166342A1 (en) * 2006-01-30 2012-06-28 Reid Scott T System and method for processing checks and check transactions
US8126252B2 (en) 2006-10-26 2012-02-28 Bank Of America Corporation Method and system for enhanced check image privacy
EP2078278A2 (fr) * 2006-10-26 2009-07-15 Bank of America Corporation Procédé et système pour une confidentialité d'image de chèque améliorée
EP2078278A4 (fr) * 2006-10-26 2011-11-02 Bank Of America Procédé et système pour une confidentialité d'image de chèque améliorée
US7747061B2 (en) 2006-12-08 2010-06-29 Wells Fargo Bank, N.A. Method and apparatus for any which way check acceptance
US8023718B1 (en) * 2007-01-16 2011-09-20 Burroughs Payment Systems, Inc. Method and system for linking front and rear images in a document reader/imager
US8023717B1 (en) * 2007-01-16 2011-09-20 Burroughs Payment Systems, Inc. Method and system for processing backwards documents in a document reader/imager
US20090300068A1 (en) * 2008-05-30 2009-12-03 Tang ding-yuan System and method for processing structured documents
US20100014744A1 (en) * 2008-07-16 2010-01-21 Toshiba Tec Kabushiki Kaisha Data reading apparatus, method of controlling the same, and printer
US20110172808A1 (en) * 2008-09-22 2011-07-14 Gui Fu Paper sheet management system, paper sheet mangement apparatus, paper sheet management method, and paper sheet management program
US9305415B2 (en) * 2008-09-22 2016-04-05 Glory Ltd. Paper sheet management system, paper sheet mangement apparatus, paper sheet management method, and paper sheet management program
US20100258629A1 (en) * 2009-04-14 2010-10-14 Document Capture Technologies, Inc. Infrared and Visible Imaging of Documents
US8376231B2 (en) 2009-04-14 2013-02-19 Document Capture Technologies, Inc. Infrared and visible imaging of documents
US20120177295A1 (en) * 2011-01-07 2012-07-12 Yuval Gronau Document comparison and analysis for improved OCR
US20120177291A1 (en) * 2011-01-07 2012-07-12 Yuval Gronau Document comparison and analysis
US8472727B2 (en) * 2011-01-07 2013-06-25 Yuval Gronau Document comparison and analysis for improved OCR
US8472726B2 (en) * 2011-01-07 2013-06-25 Yuval Gronau Document comparison and analysis
US9070010B2 (en) 2012-08-06 2015-06-30 Bank Of America Corporation Image check content estimation and use
US9721236B2 (en) 2012-08-09 2017-08-01 Bank Of America Corporation Distributed processing of a check image
US8996476B2 (en) * 2012-08-20 2015-03-31 Bank Of America Corporation Correction of check processing defects
US20140052697A1 (en) * 2012-08-20 2014-02-20 Bank Of America Corporation Correction of check processing defects
US10049350B2 (en) 2015-06-25 2018-08-14 Bank Of America Corporation Element level presentation of elements of a payment instrument for exceptions processing
US10115081B2 (en) 2015-06-25 2018-10-30 Bank Of America Corporation Monitoring module usage in a data processing system
US10229395B2 (en) 2015-06-25 2019-03-12 Bank Of America Corporation Predictive determination and resolution of a value of indicia located in a negotiable instrument electronic image
US10373128B2 (en) 2015-06-25 2019-08-06 Bank Of America Corporation Dynamic resource management associated with payment instrument exceptions processing
US10664811B2 (en) 2018-03-22 2020-05-26 Bank Of America Corporation Automated check encoding error resolution
US11361287B2 (en) 2018-03-22 2022-06-14 Bank Of America Corporation Automated check encoding error resolution

Also Published As

Publication number Publication date
WO2005066880A1 (fr) 2005-07-21
EP1700249A1 (fr) 2006-09-13
CA2546849A1 (fr) 2005-07-21
CA2546849C (fr) 2014-03-18
US20130112748A1 (en) 2013-05-09
BRPI0418196A (pt) 2007-06-19
EP1700249B1 (fr) 2010-02-17
US8864029B2 (en) 2014-10-21

Similar Documents

Publication Publication Date Title
US8864029B2 (en) Method and system for exception processing of MICR documents
US7165723B2 (en) System and method for the processing of MICR documents that produce read errors
EP0552294B1 (fr) Lecture automatique amelioree de donnees
US20200210694A1 (en) Systems and methods for classifying payment documents during mobile image processing
US6863214B2 (en) Image enabled reject repair for check processing capture
US5874717A (en) Image-based document processing system
US20050281450A1 (en) System and method for correcting data in financial documents
US20060219773A1 (en) System and method for correcting data in financial documents
US4404649A (en) Document processing system
US5689579A (en) Rule-based circuit, method and system for performing item level reconciliation
US8126252B2 (en) Method and system for enhanced check image privacy
US7697728B2 (en) System and method of sorting document images based on image quality
US8639062B2 (en) Ensuring image integrity using document characteristics
US5237158A (en) Image-based document processing system providing for priority document shipment
US5708810A (en) Image-based document processing system having a platform architecture
US7773775B2 (en) Surrogate document indicator and methods of using same
US6125196A (en) Method for identifying suspect items in an out-of-balance transaction
US8255598B2 (en) Method and apparatus for managing item sequence numbers in an item processing system
US6769615B2 (en) Multi-pass merge process for the check processing control system
JPH05108689A (ja) 為替振込処理装置
JP6736277B2 (ja) 帳票処理方法、帳票処理装置、システムおよびプログラム
CA2641301A1 (fr) Integrite d'image au moyen des caracteristiques des documents

Legal Events

Date Code Title Description
AS Assignment

Owner name: BANK OF AMERICA CORPORATION, NORTH CAROLINA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:BEICHLER, RAYMOND G.;PARSONS, RUSSELL M.;MCGLAMERY, DAVID CRAIG;AND OTHERS;REEL/FRAME:016150/0884;SIGNING DATES FROM 20050114 TO 20050610

STCB Information on status: application discontinuation

Free format text: ABANDONED -- AFTER EXAMINER'S ANSWER OR BOARD OF APPEALS DECISION