Classifications

• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q30/00—Commerce
  • G06Q30/04—Billing or invoicing
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F40/00—Handling natural language data
  • G06F40/10—Text processing
  • G06F40/166—Editing, e.g. inserting or deleting
  • G06F40/186—Templates
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q20/00—Payment architectures, schemes or protocols
  • G06Q20/38—Payment protocols; Details thereof
  • G06Q20/389—Keeping log of transactions for guaranteeing non-repudiation of a transaction
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q20/00—Payment architectures, schemes or protocols
  • G06Q20/38—Payment protocols; Details thereof
  • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
  • G06Q20/401—Transaction verification
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
  • G06Q40/12—Accounting
  • G06Q40/123—Tax preparation or submission

Definitions

• the present disclosure relates generally to monitoring statuses of requests submitted via electronic documents, and more particularly to monitoring statuses of requests based on contents of electronic documents.
• a customer may input credit card information pursuant to a payment, and the merchant may verify the credit card information in real-time before authorizing the sale. The verification typically includes determining whether the provided information is valid (i.e., that a credit card number, expiration date, PIN code, and/or customer name match known information).
• a purchase order may be generated for the customer.
• the purchase order provides evidence of the order such as, for example, a purchase price, goods and/or services ordered, and the like.
• an invoice for the order may be generated. While the purchase order is usually used to indicate which products are requested and an estimate or offering for the price, the invoice is usually used to indicate which products were actually provided and the final price for the products. Frequently, the purchase price as demonstrated by the invoice for the order is different from the purchase price as demonstrated by the purchase order. As an example, if a guest at a hotel initially orders a 3-night stay but ends up staying a fourth night, the total price of the purchase order may reflect a different total price than that of the subsequent invoice.
• existing image recognition solutions may be unable to accurately identify some or all special characters (e.g., "!,” “@,” “#,” “$,” “ ⁇ ,” “%,” “&,” etc.). As an example, some existing image recognition solutions may inaccurately identify a dash included in a scanned receipt as the number “1 .” As another example, some existing image recognition solutions cannot identify special characters such as the dollar sign, the yen symbol, etc.
• such solutions may face challenges in preparing recognized information for subsequent use. Specifically, many such solutions either produce output in an unstructured format, or can only produce structured output if the input electronic documents are specifically formatted for recognition by an image recognition system. The resulting unstructured output typically cannot be processed efficiently. In particular, such unstructured output may contain duplicates, and may include data that requires subsequent processing prior to use.
• a VAT reclaim request may not result in successful reclaiming of taxes paid.
• the failure to obtain a reclaim may be due to, for example, the request being denied, the request not being received by an appropriate tax authority, and the like.
• an entity may wish to provide additional information needed to successfully obtain the reclaim.
• Existing solutions for confirming that a reclaim has been successfully obtained typically include manual checking by, e.g., noting each reclaim request and sending a status request for each reclaim request to the appropriate tax authorities. Such manual checking therefore requires additional recordkeeping and is subject to human error.
• Certain embodiments disclosed herein include a method for automatically monitoring a request indicated in an electronic document.
• the method comprises: analyzing the electronic document to determine at least one request parameter, wherein the electronic document includes at least partially unstructured data; creating, based on the analysis of the electronic document, a request template for the electronic document, wherein the request template is a structured dataset including the determined at least one request parameter; setting, based on the created request template, a timer, wherein the timer is set at least with respect to a time of submission of the request; and upon expiration of the timer, determining, based on the created request template, a status of the request.
• Certain embodiments disclosed herein also include a non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to perform a process, the process comprising: analyzing the electronic document to determine at least one request parameter, wherein the electronic document includes at least partially unstructured data; creating, based on the analysis of the electronic document, a request template for the electronic document, wherein the request template is a structured dataset including the determined at least one request parameter; setting, based on the created request template, a timer, wherein the timer is set at least with respect to a time of submission of the request; and upon expiration of the timer, determining, based on the created request template, a status of the request.
• Certain embodiments disclosed herein also include a system for automatically monitoring a request indicated in an electronic document.
• the system comprises: a processing circuitry; and a memory, the memory containing instructions that, when executed by the processing circuitry, configured the system to: analyze the electronic document to determine at least one request parameter, wherein the electronic document includes at least partially unstructured data; create, based on the analysis of the electronic document, a request template for the electronic document, wherein the request template is a structured dataset including the determined at least one request parameter; set, based on the created request template, a timer, wherein the timer is set at least with respect to a time of submission of the request; and upon expiration of the timer, determine, based on the created request template, a status of the request.
• Figure 1 is a network diagram utilized to describe the various disclosed embodiments.
• Figure 2 is a schematic diagram of a validation system according to an embodiment.
• Figure 3 is a flowchart illustrating a method for automatically monitoring a request indicated in an electronic document according to an embodiment.
• Figure 4 is a flowchart illustrating a method for creating a dataset based on at least one electronic document according to an embodiment.
• the various disclosed embodiments include a method and system for automatically monitoring a request indicated in an electronic document.
• a dataset is created based on an electronic document indicating information related to a request.
• the request may be for a reclaim of value-added taxes (VATs) paid during a transaction.
• VATs value-added taxes
• a request template of transaction attributes is created based on the created dataset.
• a value for a timer is determined and the timer is set using the determined timer value.
• the timer value may be based on a period of time beginning with the time of submission of the request indicated in the electronic document.
• the determination may include determining, based on the created request template, a status of the request. If the request was not granted, at least one cause of the lack of granting may be determined.
• a notification indicating the status of the request may be generated. When the request is not granted, the notification may further include the determined at least one cause of the lack of granting.
• Fig. 1 shows an example network diagram 100 utilized to describe the various disclosed embodiments.
• a request monitor 120 an enterprise system 130, a database 140, and a plurality of data sources 150-1 through 150-N (hereinafter referred to individually as a data source 150 and collectively as data sources 150, merely for simplicity purposes), are communicatively connected via a network 1 10.
• the network 1 10 may be, but is not limited to, a wireless, cellular or wired network, a local area network (LAN), a wide area network (WAN), a metro area network (MAN), the Internet, the worldwide web (WWW), similar networks, and any combination thereof.
• LAN local area network
• WAN wide area network
• MAN metro area network
• WWW worldwide web
• the enterprise system 130 is associated with an enterprise, and may store data related to purchases made by the enterprise or representatives of the enterprise as well as data related to the enterprise itself.
• the enterprise system 130 further stores data related to requests (e.g., requests for VAT reclaims) to be submitted by the enterprise (e.g., an image file showing a VAT reclaim request form submitted by an employee of the enterprise).
• requests e.g., requests for VAT reclaims
• the enterprise may be, but is not limited to, a business whose employees may purchase goods and services subject to VAT taxes while abroad.
• the enterprise system 130 may be, but is not limited to, a server, a database, an enterprise resource planning system, a customer relationship management system, or any other system storing relevant data.
• the data stored by the enterprise system 130 may include, but is not limited to, electronic documents (e.g., an image file showing, for example, a completed VAT reclaim request form, a scan of an invoice, a text file, a spreadsheet file, etc.). Each electronic document may show, e.g., an invoice, a tax receipt, a purchase number record, a VAT reclaim request, and the like. Data included in each electronic document may be structured, semi-structured, unstructured, or a combination thereof. The structured or semi-structured data may be in a format that is not recognized by the request monitor 120 and, therefore, may be treated as unstructured data.
• electronic documents e.g., an image file showing, for example, a completed VAT reclaim request form, a scan of an invoice, a text file, a spreadsheet file, etc.
• Each electronic document may show, e.g., an invoice, a tax receipt, a purchase number record, a VAT reclaim request, and the like.
• the database 140 may store data related to statuses of pending requests. Such data may include, e.g., statuses of requests determined or obtained by the request monitor 120, causes of lack of granting of requests, or both.
• the data sources 150 store at least information related to the status of pending or processed requests.
• the data sources 150 may include, but are not limited to, tax authority servers.
• the data source 150-1 may be a server of an Israel tax authority
• the data source 150-8 may be a server of a Scotland tax authority.
• the request monitor 120 is configured to create a request template based on request parameters identified using machine vision of an electronic document indicating information related to a VAT reclaim request with respect to a transaction.
• the request monitor 120 may be configured to retrieve the electronic document from, e.g., the enterprise system 130.
• the request verifier 120 is configured to at least determine a status of the request.
• the request monitor 120 is configured to create datasets based on electronic documents including data at least partially lacking a known structure (e.g., unstructured data, semi-structured data, or structured data having an unknown structure). To this end, the request monitor 120 may be further configured to utilize optical character recognition (OCR) or other image processing to determine data in the electronic document.
• OCR optical character recognition
• the request monitor 120 may therefore include or be communicatively connected to a recognition processor (e.g., the recognition processor 235, Fig. 2).
• the request monitor 120 is configured to analyze the created datasets to identify request parameters related to the request indicated in the electronic documents.
• the request parameters may include, but are not limited to, parameters related to the submission of the request (e.g., a date of submission, an entity submitting the request, and entity to receive the request, etc.), parameters related to a transaction related to the request (e.g., transaction parameters such as buyer, seller, price, quantity, types of products, date of transaction, transaction identification number, etc.), or both.
• the request monitor 120 is configured to create request templates based on the created datasets. Each request template is a structured dataset including the identified request parameters for a transaction.
• the request monitor 120 is configured to create a request template based on the electronic document.
• the request template may be, but is not limited to, a data structure including a plurality of fields. The fields may be predefined, and may include the identified request parameters.
• the request monitor 120 is configured to set a timer. Setting the timer may include, but is not limited to, determining a value for the timer based on the created request template.
• the request monitor 120 may be configured to query one of the data sources 150 for an estimated time of processing for the request.
• the timer may be set to expire based on a date of the transaction for which the request was made (e.g., the date of a purchase for which a VAT reclaim is sought) and an estimated time of processing.
• the request monitor 120 when the timer expires, is configured to check a status of the request to determine if the request has been granted. In a further embodiment, the request monitor 120 may be configured to query one of the data sources 150 for the status of the request. The status of the request may indicate, e.g., that the request was granted, that the request was declined, that the request was not received, that the request has been received but has not yet been processed, and the like.
• a cause of the lack of granting the request may be determined.
• a request may not be granted if, e.g., the request form was incomplete, the request form was not received by an appropriate request processing authority (e.g., a particular tax agency), the request did not meet one or more request granting requirements (e.g., for a VAT reclaim request, the request may only be granted if the buyer has a different country of residence or incorporation than the seller), information in the request did not match information indicated by documents evidencing the request, and the like.
• a lack of granting of the request may be associated with statuses indicating, but not limited to, that the request has been denied, that the request has not been received, that the request has been received but has not yet been processed, and the like.
• Potential causes of failure to grant a request may include circumstances or assumptions related to the cause of the non-granted request.
• the potential causes may be determined based on one or more causation rules.
• the causation rules may include potential causes associated with missing or incomplete information, whether the electronic document including the request is in the possession of an appropriate request processing authority, a difference between information in the request and request granting requirements, a difference between information in the request and information in an electronic document evidencing the request, and the like.
• Fig. 2 is an example schematic diagram of the request monitor 120 according to an embodiment.
• the request monitor 120 includes a processing circuitry 210 coupled to a memory 215, a storage 220, and a network interface 240.
• the data integrity manager 120 may include an optical character recognition (OCR) processor 230.
• OCR optical character recognition
• the components of the request verifier 120 may be communicatively connected via a bus 250.
• the processing circuitry 210 may be realized as one or more hardware logic components and circuits.
• illustrative types of hardware logic components include field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), Application-specific standard products (ASSPs), system-on-a-chip systems (SOCs), general-purpose microprocessors, microcontrollers, digital signal processors (DSPs), and the like, or any other hardware logic components that can perform calculations or other manipulations of information.
• the memory 215 may be volatile (e.g., RAM, etc.), non-volatile (e.g., ROM, flash memory, etc.), or a combination thereof.
• computer readable instructions to implement one or more embodiments disclosed herein may be stored in the storage 220.
• the memory 215 is configured to store software.
• Software shall be construed broadly to mean any type of instructions, whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. Instructions may include code (e.g., in source code format, binary code format, executable code format, or any other suitable format of code).
• the instructions when executed by the one or more processors, cause the processing circuitry 210 to perform the various processes described herein. Specifically, the instructions, when executed, cause the processing circuitry 210 to perform automatic monitoring of requests indicated in electronic documents, as discussed herein.
• the storage 220 may be magnetic storage, optical storage, and the like, and may be realized, for example, as flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVDs), or any other medium which can be used to store the desired information.
• flash memory or other memory technology
• CD-ROM Compact Discs
• DVDs Digital Versatile Disks
• the OCR processor 230 may include, but is not limited to, a feature and/or pattern recognition processor (RP) 235 configured to identify patterns, features, or both, in unstructured data sets. Specifically, in an embodiment, the OCR processor 230 is configured to identify at least characters in the unstructured data. The identified characters may be utilized to create a dataset including data required for verification of a request.
• RP pattern recognition processor
• the network interface 240 allows the data integrity manager 120 to communicate with the enterprise system 130, the database 140, the web sources 150, or a combination of, for the purpose of, for example, collecting metadata, retrieving data, storing data, and the like.
• Fig. 3 is an example flowchart 300 illustrating a method for automatically monitoring a request indicated in an electronic document according to an embodiment.
• the method may be performed by a request verifier (e.g., the request verifier 120).
• a dataset is created based on an electronic document including information of a request related to a transaction.
• the electronic document may include, but is not limited to, unstructured data, semi-structured data, structured data with structure that is unanticipated or unannounced, or a combination thereof.
• S310 may further include analyzing the electronic document using optical character recognition (OCR) to determine data in the electronic document, identifying key fields in the data, identifying values in the data, or a combination thereof.
• OCR optical character recognition
• analyzing the created dataset may include, but is not limited to, determining request parameters such as, but not limited to, a date of submission of the request, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction that the request is based on (e.g., a date, a time, a price, a type of good or service sold, etc.), or a combination thereof.
• request parameters such as, but not limited to, a date of submission of the request, at least one entity identifier (e.g., a consumer enterprise identifier, a merchant enterprise identifier, or both), information related to the transaction that the request is based on (e.g., a date, a time, a price, a type of good or service sold, etc.), or a combination thereof.
• a request template is created based on the dataset.
• the request template may be, but is not limited to, a data structure including a plurality of fields.
• the fields may include the identified request parameters.
• the fields may be predefined.
• Creating templates from electronic documents allows for faster processing due to the structured nature of the created templates. For example, query and manipulation operations may be performed more efficiently on structured datasets than on datasets lacking such structure. Further, organizing information from electronic documents into structured datasets, the amount of storage required for saving information contained in electronic documents may be significantly reduced. Electronic documents are often images that require more storage space than datasets containing the same information. For example, datasets representing data from 100,000 image electronic documents can be saved as data records in a text file. A size of such a text file would be significantly less than the size of the 100,000 images.
• a value for a timer is determined based on the created request template.
• the timer may be utilized to indicate when a status of the request should be checked.
• the timer may be set to expire after 30 days have passed since submission of the request.
• the timer value may be determined based on, but not limited to, a time of submission of the request, a request processing authority to which the request is sent (i.e., different request processing authorities may have different average wait periods for granting requests depending upon, e.g., staffing, number of requests in a queue, etc.), a seller indicated in the request (i.e., a request related to a transaction involving a newly registered seller may take longer to process than a request related to a transaction involving a longtime registered seller), combinations thereof, and the like.
• the timer value may be determined based on at least one timer setting rule.
• S340 may include querying, in real-time, a data source associated with the request processing authority to which the request was sent based on information in the created request template (e.g., a request identifier, a transaction identifier, etc.). Querying the data source in real-time may allow for more accurate values for the timer based on current information related to time for processing requests (e.g., a current number of requests in a queue may be utilized to more accurately determine an expected time for processing a newly received request).
• S350 when the timer has expired, it is determined whether the request was granted and, if so, execution continues with S370, otherwise, execution continues with S360.
• S350 includes determining a status of the request.
• S350 may include querying at least one data source (e.g., a tax authority server) based on the created request template.
• a transaction identifier e.g., a transaction identification number
• S350 may include determining the at least one data source to be queried based on the created request template.
• the determined data source may be a server of a German tax authority.
• the status of the request may indicate, but is not limited to, that the request was granted, that the request was declined, that the request was not received, that the request has been received but has not yet been processed, and the like.
• execution may return to S340, at which a new value for the timer may be determined and the timer may be set using the new value.
• the new value for the timer may be based further on an amount of time elapsed since the submission of the request.
• a first value for the timer may be determined to be 21 days based on an average value for the tax reclaim agency the request was sent to.
• a second value for the timer may be set such that the timer expires after a subsequent 9-day period (e.g., 30 days after submission of the request).
• a threshold amount of time may be predetermined or may be determined based on, e.g., the determined value for the timer (for example, the threshold time period may be, e.g., double the determined value for the timer).
• At optional S360 when it is determined that the request has not been granted, at least one cause of the lack of granting may be determined.
• the at least one cause of the lack of granting may be determined when a status of the request indicates that the request was declined or not received.
• determining the cause of the lack of granting may be based on the status of the request. For example, if the status of the request indicates that the request was not received, a cause of the lack of granting may be failure to send the request to the correct entity.
• determining the at least one cause of the lack of granting may include comparing information of the request to information of the transaction for which the request was submitted.
• S360 may further include creating a transaction template for an evidencing electronic document including information related to the transaction and comparing the created transaction template to the request template.
• a name of a buyer of the transaction included in a "Buyer Name" field of a request template created based on a scanned request form does not match a name included in the corresponding field of a transaction template created based on a scanned invoice, the at least one cause of the lack of granting may be determined to include an incorrect name of the buyer.
• S360 may include determining if one or more required request parameters is missing or otherwise incomplete based on one or more request requirements. As a non-limiting example, if there is no tax identification number in a "Tax ID" field of the request template, the at least one cause of the lack of granting may be determined to include a missing tax identification number.
• additional data, replacement data, or both may be retrieved from at least one data source and included in the request template.
• additional or replacement data upon retrieving the additional or replacement data, a new request may be generated and sent.
• S360 may further include generating at least one recommendation for correcting the at least one cause of the lack of granting. In a further embodiment, S360 may further include comparing the determined at least one cause to at least one previously determined cause of lack of granting of a request associated with a recommendation for correction.
• a notification may be generated.
• the notification may indicate the status of the request.
• the notification may include the determined at least one cause of the lack of granting.
• Fig. 4 is an example flowchart S310 illustrating a method for creating a dataset based on an electronic document according to an embodiment.
• the electronic document is obtained.
• Obtaining the electronic document may include, but is not limited to, receiving the electronic document (e.g., receiving a scanned image) or retrieving the electronic document (e.g., retrieving the electronic document from a consumer enterprise system, a merchant enterprise system, or a database).
• the electronic document is analyzed.
• the analysis may include, but is not limited to, using optical character recognition (OCR) to determine characters in the electronic document.
• OCR optical character recognition
• the key field may include, but are not limited to, merchant's name and address, date, currency, good or service sold, a transaction identifier, an invoice number, and so on.
• An electronic document may include unnecessary details that would not be considered to be key values. As an example, a logo of the merchant may not be required and, thus, is not a key value.
• a list of key fields may be predefined, and pieces of data that may match the key fields are extracted. Then, a cleaning process is performed to ensure that the information is accurately presented. For example, if the OCR would result in a data presented as "121 1212005", the cleaning process will convert this data to 12/12/2005. As another example, if a name is presented as "Mo$den”, this will change to "Mosden”.
• the cleaning process may be performed using external information resources, such as dictionaries, calendars, and the like.
• S430 results in a complete set of the predefined key fields and their respective values.
• a structured dataset is generated.
• the generated dataset includes the identified key fields and values.
• any reference to an element herein using a designation such as "first,” “second,” and so forth does not generally limit the quantity or order of those elements. Rather, these designations are generally used herein as a convenient method of distinguishing between two or more elements or instances of an element. Thus, a reference to first and second elements does not mean that only two elements may be employed there or that the first element must precede the second element in some manner. Also, unless stated otherwise, a set of elements comprises one or more elements.
• the phrase "at least one of” followed by a listing of items means that any of the listed items can be utilized individually, or any combination of two or more of the listed items can be utilized. For example, if a system is described as including "at least one of A, B, and C," the system can include A alone; B alone; C alone; A and B in combination; B and C in combination; A and C in combination; or A, B, and C in combination.
• the various embodiments disclosed herein can be implemented as hardware, firmware, software, or any combination thereof.
• the software is preferably implemented as an application program tangibly embodied on a program storage unit or computer readable medium consisting of parts, or of certain devices and/or a combination of devices.
• the application program may be uploaded to, and executed by, a machine comprising any suitable architecture.
• the machine is implemented on a computer platform having hardware such as one or more central processing units (“CPUs"), a memory, and input/output interfaces.
• CPUs central processing units
• the computer platform may also include an operating system and microinstruction code.

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