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WO2020255361A1 - Accounting processing system, accounting processing method, and accounting processing program - Google Patents

Accounting processing system, accounting processing method, and accounting processing program Download PDF

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Publication number
WO2020255361A1
WO2020255361A1 PCT/JP2019/024611 JP2019024611W WO2020255361A1 WO 2020255361 A1 WO2020255361 A1 WO 2020255361A1 JP 2019024611 W JP2019024611 W JP 2019024611W WO 2020255361 A1 WO2020255361 A1 WO 2020255361A1
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WIPO (PCT)
Prior art keywords
journal
unit
journal element
text
accounting
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PCT/JP2019/024611
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French (fr)
Japanese (ja)
Inventor
葛鴻鵬
松原正和
Original Assignee
ファーストアカウンティング株式会社
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Priority to JP2019534427A priority Critical patent/JPWO2020255361A1/en
Priority to PCT/JP2019/024611 priority patent/WO2020255361A1/en
Publication of WO2020255361A1 publication Critical patent/WO2020255361A1/en

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Definitions

  • the present invention extracts journal elements such as date, business partner, amount, and description from voucher image data such as receipts and receipts, and can automatically journal from the extracted journal elements. Accounting system, accounting method, accounting processing. Regarding the program.
  • journal element information is extracted as text format data. Specifically, it recognizes the character information group recorded in the image data of the voucher such as a receipt and converts it into text data composed of items such as user ID, date, purchase destination name, and purchased product name. .. Then, the product group corresponding to the product name included in the journal element information converted into text data is obtained from the product master, and the recommended journal is shown using the mapping table corresponding to the product group (paragraph of Patent Document 1). 0118 to paragraph 0128).
  • the journal element is extracted from the voucher using an OCR device, but the display format of the voucher is various, and the information described in the voucher is also various, so that the extraction accuracy of the journal element is high. It's not easy to do. For example, if a plurality of company names are described in one voucher, it may not be possible to determine which company name is the issuer of the voucher.
  • journal elements cannot always be extracted accurately in this way, the person in charge will eventually check all the extracted journal elements, and work efficiency cannot be improved.
  • work efficiency cannot be improved.
  • journals, and recommended journals are not always correct and must be checked by the person in charge, so work efficiency cannot be improved.
  • journal elements can be extracted accurately, the extracted journal elements can be entered separately in the journal entry field, or even if the correct recommended journal is output, it can be reported to the superior or the person in charge of other departments. Many simple tasks occur in accounting, such as sending emails.
  • the present invention has been made to solve such a problem, and the purpose of the present invention is to reduce confirmation work and simple work by a person in charge and improve the overall work efficiency of accounting processing.
  • the accounting system extracts the journal element as text from the image data of the voucher by the journal element extraction AI for outputting the journal element as text from the image data of the voucher.
  • the journal element extraction unit that outputs the reliability of the extraction
  • the automatic processing unit that can automatically execute the processing using the text of the journal element by the processing procedure registered in advance
  • the journal element extraction unit output the data. It is provided with a determination unit that determines that the input information is appropriate and executes the processing by the automatic processing unit when the reliability is equal to or higher than a predetermined threshold value.
  • the accounting system extracts the journal element as text from the image data of the voucher by the journal element extraction AI for outputting the journal element as text from the image data of the voucher.
  • the journal element extraction unit, the automatic processing unit that can automatically execute the processing using the text of the journal element by the processing procedure registered in advance, and the voucher input by a means different from the journal element extraction unit. It is stored in the journal element data storage unit that stores the text of the journal element included in the image data, the text of the journal element extracted from the journal element extraction unit, and the journal element data storage unit that corresponds to the journal element. It is provided with a determination unit that determines that the input information is appropriate and executes processing by the automatic processing unit when the texts of the journal elements are matched and matched.
  • the accounting system outputs the journal result to the input journal element by the journal AI for outputting the journal result according to the journal element, and the subject
  • a journal unit that outputs the reliability of the journal result, an automatic processing unit that can automatically execute processing using the journal result by a processing procedure registered in advance, and the reliability output from the journal unit are predetermined.
  • the value is equal to or greater than the threshold value of, it is determined that the input information is appropriate, and a determination unit for executing the process by the automatic processing unit is provided.
  • the determination unit may generate warning display data when it determines that the input information is not valid.
  • the automatic processing unit may be able to automatically execute a process of performing automatic journalizing using the journal element.
  • the automatic processing unit may be able to automatically execute a process of sending the journal entry result by e-mail to a specific destination.
  • the accounting method uses the journal element extraction AI for outputting the journal element as text from the image data of the voucher, and uses the journal element as text from the image data of the voucher.
  • the text of the extracted journal element is appropriate when the journal element extraction step that extracts and outputs the reliability of the extraction and the reliability output from the journal element extraction step are equal to or higher than a predetermined threshold.
  • the process using the text of the journal element is automatically executed by the pre-registered processing procedure. The processing process is performed by the computer.
  • a computer is made to execute the above-mentioned accounting processing method.
  • FIG. 1 is a schematic configuration diagram showing an overall configuration of an accounting processing system according to an embodiment of the present invention, and the configuration of the present embodiment will be described based on the same diagram.
  • the accounting processing system 1 accounts for each device on the user side and accounting processing on the accounting processing service provider side via a communication network 2 such as the Internet and VPN (Virtual Private Network). It is configured by being connected to the device 10. Although only one user is shown in FIG. 1 for simplification of the description, the accounting processing apparatus 10 can connect to a plurality of users via the communication network 2.
  • a communication network 2 such as the Internet and VPN (Virtual Private Network).
  • the user is, for example, an expert such as a tax accountant or an accountant, or a corporation or an individual who directly performs accounting processing, and has at least a reading device 3 and an information terminal 4.
  • the reading device 3 is an optical device such as a scanner or a camera, and is a device that can capture a voucher as image data.
  • the word "voucher" in the present embodiment and claims is used for receipts, receipts, other receipts, invoices, invoices, bankbooks of financial institutions, documents certifying money transfer in accounting, and electronic money. It shall also include transaction information using IC cards such as money.
  • the information terminal 4 is, for example, a personal computer (hereinafter referred to as a PC), a smartphone, a tablet PC, and a mobile terminal such as a mobile phone.
  • the information terminal 4 has an input unit 4a that accepts user operations and a display unit 4b that can display at least web information.
  • the user can acquire the image data of the voucher by the reading device 3 and transmit it to the accounting processing device 10 by the information terminal 4, and can also send and receive information to and from the accounting processing device 10.
  • the reading device 3 and the information terminal 4 are shown as separate bodies in FIG. 1, the reading device 3 and the information terminal 4 may be integrated as in a mobile terminal with a camera. Further, the user does not have to own the reading device 3, and for example, the image data of the voucher read by an external reading device may be acquired via an e-mail or a web.
  • the accounting processing service provider (hereinafter, also simply referred to as a service provider) is a business operator that provides accounting processing services by so-called cloud computing, and is a person who manages the accounting processing device 10.
  • the accounting processing device 10 has one or a plurality of servers (computers) that execute journal processing based on a program, and functionally mainly, a journal element extraction unit 11 that extracts journal elements as text from the image data of a voucher. , The journal element determination unit 12 that determines the validity of the extracted journal element, and the first RPA execution unit that executes the process using the text of the journal element in the pre-registered processing procedure (first RPA workflow). 13 (Automatic processing unit), Journal unit 14 that automatically performs journals based on journal elements, Journal judgment unit 15 that determines the consistency of journal results, Predetermined processing work for journal results (second RPA workflow) It has a second RPA execution unit 16 that executes the above.
  • servers computers
  • the accounting processing device 10 has one or a plurality of servers (computers) that execute journal processing based on a program, and functionally mainly, a journal element extraction unit 11 that extracts journal elements as text from the image data of a voucher.
  • the journal element determination unit 12 that determines the validity of the
  • RPA Robot Process Automation
  • the accounting processing device 10 generates an application database 20 (hereinafter, the database is referred to as “DB”), a journal element extraction AI, and a journal AI in which information for which the user has applied for expenses via the information terminal 4 is stored. It has a learning system 21 and an RPA setting unit 22 for setting a first RPA and a second RPA.
  • the journal element extraction unit 11 has a function of receiving the image data of the voucher from the user and extracting the journal element from the image data. Specifically, the journal element extraction unit 11 has a journal element extraction AI for extracting the journal element from the image data of the voucher, and the journal element can be extracted from the image data of the voucher by the plurality of journal element extraction AIs. Is.
  • Journal element extraction AI specifies the part (position) corresponding to the journal element from the image data of the voucher, and extracts the journal element corresponding to the content of the specified part as text. That is, the journal element extraction AI specifies an area including a portion corresponding to the journal element from the image data by machine learning in the learning system 21, and outputs the journal element corresponding to the content of the specified portion as text. It is AI who learned that. For example, the journal element extraction AI specifies a date part, an amount part, a business partner part, and a description part in the image data of a voucher, and recognizes a number in the date part and the amount part to recognize the date part and the amount amount. The text is output, and the text of the business partner and the description is output by recognizing the characters in the part corresponding to the business partner and the part corresponding to the description.
  • journal element extraction unit 11 not only recognizes characters and numbers by the journal element extraction AI and outputs text, but also, for example, when only a logo mark, an imprint, or a telephone number is extracted, it is not shown. It may be output as the text of the business partner name by searching from the company information DB in which the company information is stored in advance or by searching the information published on the Internet. In addition, when there is no description of the address such as a receipt, the user name that sent the image data may be output as the text of the transaction source, or the company that is the customer of the user is set in advance. The image data transmitted from the user may output the set company name as the text of the transaction source.
  • the journal element extraction AI is an image recognition AI that specifies a part (position) corresponding to the journal element from the image data of the voucher, and a character recognition AI that extracts the journal element corresponding to the content of the specified part as text. It may be composed of two AIs.
  • Journal elements include, for example, date, amount, business partner, description (including proviso and product name), business source (including address), and the corresponding numbers, letters, graphics (for example, logo mark, imprint, and other companies). There is a identifiable pattern) and the appearance of the voucher (eg, the size and color of the passbook or receipt).
  • journal element extraction unit 11 specifies numbers before, after, and above and below characters such as “date”, “year”, “month”, and “day” and symbols such as “/”. Amounts include symbols such as “ ⁇ ”, product names, “amount”, “deposit”, “subtotal”, “total”, “tax”, “change”, “discount”, “yen”, “payment”, “deposit”, “balance”, etc. Identify the numbers before, after, and above and below the characters related to. Then, in the present embodiment, as for the amount of money, a journal element is extracted for each character or number related to the amount of money, for example, “total 1000 yen” or “change 50 yen". The journal element extraction unit 11 can also recognize the meaning of the extracted characters, and for example, the "subtotal” can specify the accounting relationship such as the total amount of the prices of the products.
  • the characters before and after the characters such as "Co., Ltd.”, “Co., Ltd.” and “(F)", the logo mark, telephone number, and the appearance of the voucher are specified and based on this information. Identify the part that corresponds to your company or personal name. For the abstract, specify the character part following the character such as "However”. For the trading source, specify the part of the character before the character such as "sama”.
  • journal elements are not limited to this, and the numbers, letters, and figures used to extract the journal elements are not limited to this.
  • the quantity may be included as a journal entry factor, and if information such as the names and number of attendees is stated, the attendees and the number of attendees. May be included as a journal element.
  • a number corporate number, business office number set to identify each company may be extracted.
  • journal element extraction unit 11 can also output the reliability of the journal element output by the journal element extraction AI (hereinafter referred to as the journal element reliability Re).
  • the journal element reliability Re is the accuracy of the judgment of the journal element extraction AI, and can be expressed as a percentage, for example. That is, the higher the journal element reliability Re, the higher the validity of the journal element text output by the journal element extraction AI, and the lower the journal element reliability Re, the lower the validity.
  • the journal element reliability Re is not limited to the percentage display, and is displayed in a two-step evaluation in which a predetermined threshold value or more is ⁇ and less than a predetermined threshold value is ⁇ , or two threshold values are set and a three-step evaluation of ⁇ , ⁇ , and ⁇ is performed. It may be displayed.
  • the journal element determination unit 12 connected to the journal element extraction unit 11 has a function of determining the validity of the text output from the journal element extraction unit 11 as a journal element.
  • the journal element determination unit 12 determines the validity of the text of the journal element based on the journal element reliability Re output by the journal element extraction unit 11 and the matching with the information regarding the journal element input by the user.
  • the first threshold value T1 corresponding to the journal element reliability Re is set, and the journal element reliability Re is equal to or higher than the first threshold T1. If so, the extracted journal element is judged to be valid. On the other hand, if the journal element reliability Re is less than the first threshold value T1, it is determined that the extracted journal element is not valid.
  • the journal element extracted by the journal element extraction unit 11 and the information of the journal element stored in the application DB 20 are combined. If they match and match, it is judged to be valid, and if they are inconsistent, it is judged to be invalid.
  • the consistency of this matching is not limited to perfect matching, and for example, the degree of matching may be calculated and determined to be appropriate when the matching is to a certain extent. This degree of agreement may be expressed as a percentage in the same manner as the journal element reliability Re, or may be evaluated on a two-point scale of ⁇ or ⁇ or on a three-point scale of ⁇ , ⁇ , or ⁇ .
  • journal element determination unit 12 generates warning display data different from the normal display for invalid journal elements, and causes the display unit 4b of the user's information terminal 4 to present the warning display data.
  • the application DB 20 stores the image data of the voucher read by the user by the reading device 3 and the information that the user transmits the contents of the voucher to the accounting processing device 10 via the information terminal 4.
  • the image data of the voucher and the content information of the voucher input by the user are associated with each other, and the journal element determination unit 12 collates the image data of the associated voucher with the content information.
  • the first RPA execution unit 13 connected to the journal element determination unit 12 has a function of executing the first RPA workflow registered in the RPA setting unit 22.
  • the first RPA workflow is a processing work for a journal element, and in the present embodiment, input processing for automatic journal is performed.
  • the first RPA execution unit 13 copies the journal elements determined to be valid by the journal element determination unit 12 displayed on the screen of the display unit 4b of the information terminal 4, and is used for automatic journal entry. Repeat the work of pasting into the journal element input field of, and after the input field is filled, select the button to execute automatic journal.
  • the journal unit 14 has a function of outputting an account item according to the input journal element.
  • the output of the account item corresponding to this journal element is performed by, for example, the journal AI.
  • the journal AI is an automatic journal AI that has learned in advance to output an account for a journal element by machine learning in the learning system 21.
  • the account item output in the journal entry unit 14 is output to the journal entry determination unit 15 as a journal entry result together with the journal entry element.
  • journal unit 14 can also output the reliability of the journal result output by the journal AI (hereinafter referred to as the journal reliability).
  • the journal reliability Rj is the accuracy of the judgment of the journal AI, and can be expressed as a percentage, for example. That is, the higher the journal reliability Rj, the higher the validity of the journal result output by the journal AI, and the lower the journal reliability Rj, the lower the validity.
  • the journal determination unit 15 connected to the journal unit 14 has a function of determining the validity of the journal result output from the journal unit 14.
  • the journal determination unit 15 determines the validity of the journal result based on the journal reliability Rj output by the journal unit 14.
  • journal reliability Rj the journal result is Is judged to be valid.
  • the journal reliability Rj is less than the second threshold value T2 if the journal reliability Rj is less than the second threshold value T2, it is determined that the journal result is not valid.
  • journal determination unit 15 generates warning display data different from the normal display for an invalid journal result, and causes the display unit 4b of the user's information terminal 4 to present it.
  • the second RPA execution unit 16 connected to the journal determination unit 15 has a function of executing the second RPA workflow registered in the RPA setting unit 22.
  • the second RPA workflow is a processing work for the journal entry result.
  • the journal entry result determined to be appropriate by the journal entry determination unit 15 displayed on the screen of the display unit 4b of the information terminal 4 is copied and mail software is used. After pasting it in the new e-mail text of, enter a specific e-mail address (for example, the e-mail address of the accounting staff) in the destination and send it.
  • the learning system 21 has a function of learning the above-mentioned journal element extraction AI, journal AI, and the like, and supplying the learned AI. Specifically, the learning system 21 generates a journal element extraction AI by performing machine learning (so-called deep learning) based on teacher data (learning data) consisting of voucher image data and journal elements included in the image data. .. Further, the learning system 21 generates a journal AI by performing machine learning based on teacher data (learning data) composed of a journal element and an account item corresponding to the journal element.
  • the RPA setting unit 22 has a so-called RPA tool, and has a function of storing an operation procedure performed by a worker such as a user as an RPA workflow.
  • a worker such as a user
  • the user executes the operations of the first RPA workflow and the second RPA workflow described above from the information terminal 4 in advance via the RPA setting unit 22, and the first RPA workflow and the first RPA workflow It remembers 2 RPA workflows. Since the RPA setting unit 22 stores the user's operation through the display unit 4b, if it can be displayed on the display unit 4b, the RPA setting unit 22 straddles a plurality of systems or a plurality of applications such as an accounting processing system and mail software. Processing is also feasible.
  • the accounting process starts when the image data of the voucher from the user is received.
  • step S1 the journal element extraction unit 11 extracts the journal element from the received voucher image data by the journal element extraction AI. Then, the journal element extraction unit 11 outputs the text of the extracted journal element and the journal element reliability Re.
  • step S2 the journal element determination unit 12 determines whether or not the extracted journal element is appropriate. Specifically, it is determined whether or not the journal element reliability Re is equal to or higher than the first threshold value T1 and matches with the information regarding the journal element input by the user stored in the application DB 20.
  • the journal element determination unit 12 of the present embodiment makes both a determination based on the journal element reliability Re and a determination based on the matching, but may determine only one of them. If the determination result is false (No), that is, if the journal element reliability Re is less than the first threshold value T1, or if the matching result is inconsistent, the process proceeds to step S3.
  • step S3 the journal element determination unit 12 displays a warning display on the display unit 4b of the user's information terminal 4, and prompts the user (person) to confirm and correct the extracted journal element.
  • step S2 determines whether the journal element reliability Re is equal to or higher than the first threshold value T1 and the matching result is consistent. If the determination result in step S2 is true (Yes), that is, if the journal element reliability Re is equal to or higher than the first threshold value T1 and the matching result is consistent, the process proceeds to step S4.
  • step S4 the first RPA execution unit 13 performs the above-mentioned input processing for automatic journal entry by the first RPA workflow.
  • this input process is manually performed according to the warning display.
  • step S5 the journal unit 14 outputs the journal result for the input journal element and the journal reliability Rj by the journal AI.
  • the journal determination unit 15 determines whether or not the output journal result is valid. Specifically, it is determined whether or not the journal reliability Rj is equal to or higher than the second threshold value T2. If the determination result is false (No), that is, if the journal entry reliability Rj is less than the second threshold value T2, the process proceeds to step S7.
  • step S7 the journal determination unit 15 displays a warning display on the display unit 4b of the user's information terminal 4, and prompts the user (person) to confirm and correct the output journal result.
  • step S6 determines whether the journal reliability Rj is equal to or higher than the second threshold value T2 is equal to or higher than the second threshold value T2.
  • step S8 the second RPA execution unit 16 performs the above-mentioned journal entry completion email transmission process by the second RPA workflow, and ends the routine.
  • this mail transmission process is manually performed according to the warning display.
  • the accounting processing device 10 extracts the journal element from each image data by executing the routine every time the image data of the voucher is acquired, and automatically automatically journals if it is a valid journal element. Is executed, and if this journal result is valid, it is possible to automatically send an email.
  • journal element extraction field A, the journal element input field B, and the journal result field C shown in FIGS. 3 and 4 are display examples displayed on the display unit 4b of the user's information terminal 4.
  • the journal element extraction column A in FIG. 3 is a display example when the journal element is extracted from the image data of the receipt.
  • the original image of the receipt scanned on the left side of the screen and the extraction result of the journal element in the center of the screen are displayed on the screen.
  • the application details applied by the user are displayed on the right side. That is, the journal element extraction column A is a display example at the time of step S2 in FIG.
  • the journal element extraction unit 11 specifies the part 30a corresponding to the date, the part 31a corresponding to the total amount, and the part 32a corresponding to the description. However, these enlarged views 30b, 31b, and 32b are displayed in the extraction result. It should be noted that this dotted line does not have to be actually displayed on the display unit 4b.
  • the extraction results include the date "October 10, 2019", the amount “1,080 yen”, and the description " ⁇ cafe", which are the journal elements converted into text by the journal element extraction AI on the corresponding enlarged view. Is described. Further, next to the journal element, the journal element reliability Re is also written. In FIG. 3, the date journal element is "90%”, the amount journal element is "85%”, and the description journal element is ". 82% "is shown. For example, in FIG. 3, the first threshold value T1 is set to 80%, and the journal element reliability Re is equal to or higher than the first threshold value T1.
  • the date column 30c, the amount column 31c, and the description column 32c are shown as the application contents corresponding to the journal elements of the extraction result, and the date column 30c shows "October 10, 2019", the amount. "1,080 yen” is described in the column 31c, and "OO cafe” is described in the description column 32c.
  • the degree of matching of the matching result is displayed as a percentage.
  • the journal element of the date is "100%” and the journal element of the amount is "98%” (because only ⁇ is inconsistent). ),
  • the journal entry element of the description is shown as "85%” (because only the corporation does not match).
  • the threshold value of the degree of matching is set to 80%, and all the collation results are equal to or higher than this threshold value and are consistent to some extent.
  • the determination result in the journal element determination unit 12 is true (Yes). If any of the journal elements is not valid, the characters of the journal elements that are not valid in the extraction result are displayed in red or a flag is displayed as a warning display. The following flow is the same for FIGS. 3 and 4.
  • the first RPA execution unit 13 copies each journal element according to the first RPA workflow, pastes it into the corresponding input field of the journal element input field B, and when each input field is filled, the journal execution button. Select.
  • the debit includes the account "Meeting fee”, amount "1,000", reliability "82%", “temporary consumption tax”, amount "80”, and reliability "90%”.
  • the credit is credited with the account “cash”, the amount "1,080", and the reliability "95%”.
  • the second threshold value T2 is set to 80%
  • the journal entry reliability Rj is equal to or higher than the second threshold value T2.
  • the determination result in the journal entry determination unit 15 is true (Yes). If any of the journal entry results is not valid, for example, the characters of the inappropriate account, amount, or reliability are displayed in red or a flag is displayed as a warning display. Further, a pull-down menu is set for each account, and for example, when the triangle symbols in FIGS. 3 and 4 are selected, other account candidates may be listed.
  • the second RPA execution unit 16 pastes it into a new mail text of the mail software according to the second RPA workflow, and then inputs a specific mail address in the destination and sends it.
  • the accounting processing system 1 extracts the journal element from the image data of the voucher, and if the extracted journal element is highly valid, it automatically shifts to the automatic journal according to the first RPA workflow. Therefore, if the extracted journal element is highly valid, it can be automated including the processing using the journal element, and in the present embodiment, the automatic journal is automatically performed without human check or operation. Can be migrated to.
  • journalizing is performed according to the extracted journalizing elements, and if the journalizing result is highly valid, an email is automatically sent to the person in charge according to the second RPA workflow.
  • the validity of the journal entry result is high, it is possible to automate the process using the journal entry result, and in the present embodiment, an email to the person in charge is automatically sent without human check or operation. You can send.
  • the accounting processing system 1 the accounting processing method, and the accounting processing program in the present embodiment, the confirmation work and the simple work by the accounting staff of the user are reduced, and the overall work efficiency of the accounting processing is improved. be able to.
  • the first RPA workflow performs an input process for automatic journal entry
  • the second RPA workflow performs a process of sending the journal entry result by e-mail to a specific destination
  • the first RPA workflow and the automatic processing set as the second RPA workflow is not limited to this, and other processing procedures may be registered.
  • FIG. 3 an example of this embodiment is described using a receipt as an example, but the voucher is not limited to the receipt, and can be similarly applied to other vouchers such as receipts.
  • the accounting processing system 1 of the above embodiment is a system capable of consistently and automatically processing from the extraction of journal elements to the journals, but can be applied to, for example, a system having only extraction of journal elements and only automatic journals. is there.

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Abstract

An accounting processing system 1 comprises: a sorting element extraction unit 11 which uses a sorting element extraction AI for outputting as text a sorting element from image data of a voucher to extract as text the sorting element from the image data of the voucher and outputs a degree of reliability in the extraction; a first RPA execution unit 13 which can automatically execute a process using the sorting element text in a pre-registered process sequence; and a sorting element determination unit 12 which, if a sorting element degree of reliability Re outputted by the sorting element extraction unit 11 is greater than or equal to a first threshold value T1, determines that the inputted information is valid and causes the execution of the process performed by the first RPA execution unit 13.

Description

会計処理システム、会計処理方法、会計処理プログラムAccounting system, accounting method, accounting program
 本発明は領収書やレシート等の証憑の画像データから日付、取引先、金額、摘要等の仕訳要素を抽出し、抽出した仕訳要素から自動仕訳が可能な会計処理システム、会計処理方法、会計処理プログラムに関する。 The present invention extracts journal elements such as date, business partner, amount, and description from voucher image data such as receipts and receipts, and can automatically journal from the extracted journal elements. Accounting system, accounting method, accounting processing. Regarding the program.
 従来、証憑の会計処理として、税理士や会計士、簿記担当者が証憑に記載の情報を一件一件読み取り、例えば日付、取引先、金額等の仕訳要素を帳簿に入力し、当該仕訳要素に対応した勘定科目を経験的に判断して仕訳の入力を行っていた。 Conventionally, as an accounting process for vouchers, tax accountants, accountants, and bookkeepers read the information on the vouchers one by one, enter journal elements such as date, business partner, and amount in the book, and respond to the journal elements. The journal entry was made by empirically judging the account that was created.
 このように、証憑を人間が一件一件読み取って仕訳を行うのでは作業効率が悪い上、仕訳の精度は担当者の経験に依存するところが大きく、仕訳の精度にばらつきが生じるという問題があった。 In this way, if a human reads the voucher one by one and makes a journal entry, the work efficiency is poor, and the accuracy of the journal entry largely depends on the experience of the person in charge, and there is a problem that the accuracy of the journal entry varies. It was.
 そこで、OCR(Optical Character Reader)装置を用いて、証憑の内容を電子データとして読み取り、インターネットを介して仕訳解析センターシステムに送信するだけで、その証憑に示される簿記上の取引についての仕訳の結果をユーザが参照することが可能となるいわゆるクラウド型の会計処理システムが開発されている(特許文献1参照)。 Therefore, using an OCR (Optical Character Reader) device, simply read the contents of the voucher as electronic data and send it to the journal analysis center system via the Internet, and the result of the journal entry for the bookkeeping transaction shown in the voucher. A so-called cloud-type accounting system has been developed that allows users to refer to (see Patent Document 1).
 詳しくは、特許文献1に記載された技術では、携帯端末等で撮影した証憑データを仕訳要素抽出手段によって解析して仕訳要素情報をテキスト形式のデータとして抽出している。具体的には、レシート等の証憑の画像データに記録されている文字情報群を認識し、ユーザID、日付、購入先名称、購入商品名等の項目から構成されるテキストデータに変換している。そして、テキストデータに変換した仕訳要素情報に含まれる商品名に対応する商品グループを商品マスタから得て、その商品グループに対応するマッピングテーブルを用いて推奨仕訳を示している(特許文献1の段落0118~段落0128参照)。 Specifically, in the technique described in Patent Document 1, voucher data taken with a mobile terminal or the like is analyzed by a journal element extraction means, and journal element information is extracted as text format data. Specifically, it recognizes the character information group recorded in the image data of the voucher such as a receipt and converts it into text data composed of items such as user ID, date, purchase destination name, and purchased product name. .. Then, the product group corresponding to the product name included in the journal element information converted into text data is obtained from the product master, and the recommended journal is shown using the mapping table corresponding to the product group (paragraph of Patent Document 1). 0118 to paragraph 0128).
特開2014-235484号公報Japanese Unexamined Patent Publication No. 2014-235484
 上記特許文献1では、OCR装置を用いて証憑から仕訳要素を抽出しているが、証憑の表示形式は様々であり、証憑に記載されている情報も様々であるため仕訳要素の抽出精度を高くすることは容易ではない。例えば、一つの証憑内に複数の会社名が記載されていると、どの会社名が当該証憑の発行元であるのか、判別できない場合がある。 In Patent Document 1, the journal element is extracted from the voucher using an OCR device, but the display format of the voucher is various, and the information described in the voucher is also various, so that the extraction accuracy of the journal element is high. It's not easy to do. For example, if a plurality of company names are described in one voucher, it may not be possible to determine which company name is the issuer of the voucher.
 このように必ずしも正確に仕訳要素を抽出することができないために、結局は担当者が抽出された仕訳要素と全てチェックすることになり、作業効率の向上が図られない。仕訳に関しても同様であり、推奨仕訳が必ずしも正しいとは限らず、担当者がチェックする必要があるため、作業効率の向上が図られない。 Because the journal elements cannot always be extracted accurately in this way, the person in charge will eventually check all the extracted journal elements, and work efficiency cannot be improved. The same applies to journals, and recommended journals are not always correct and must be checked by the person in charge, so work efficiency cannot be improved.
 さらに、仕訳要素を正確に抽出できた場合でも、抽出した仕訳要素を仕訳用の入力欄に別途入力したり、正しい推奨仕訳が出力された場合でも上長や他部署の担当者へ報告用のメールを送ったり等、会計処理では多くの単純な作業が発生する。 Furthermore, even if the journal elements can be extracted accurately, the extracted journal elements can be entered separately in the journal entry field, or even if the correct recommended journal is output, it can be reported to the superior or the person in charge of other departments. Many simple tasks occur in accounting, such as sending emails.
 本発明はこのような問題点を解決するためになされたもので、その目的とするところは、担当者による確認作業や単純作業を削減し、会計処理の全体的な作業効率を向上させることができる会計処理システム、会計処理方法、及び会計処理プログラムを提供することにある。 The present invention has been made to solve such a problem, and the purpose of the present invention is to reduce confirmation work and simple work by a person in charge and improve the overall work efficiency of accounting processing. To provide an accounting system, accounting method, and accounting program that can be used.
 上記した目的を達成するために本発明に係る会計処理システムは、証憑の画像データから仕訳要素をテキストとして出力するための仕訳要素抽出AIにより、証憑の画像データから仕訳要素をテキストとして抽出し、且つ当該抽出の信頼度を出力する仕訳要素抽出部と、前記仕訳要素のテキストを用いた処理を予め登録された処理手順で自動的に実行可能な自動処理部と、前記仕訳要素抽出部より出力された前記信頼度が所定の閾値以上である場合 に、入力された情報が妥当であると判定し、前記自動処理部による処理を実行させる判定部と、を備える。 In order to achieve the above object, the accounting system according to the present invention extracts the journal element as text from the image data of the voucher by the journal element extraction AI for outputting the journal element as text from the image data of the voucher. Moreover, the journal element extraction unit that outputs the reliability of the extraction, the automatic processing unit that can automatically execute the processing using the text of the journal element by the processing procedure registered in advance, and the journal element extraction unit output the data. It is provided with a determination unit that determines that the input information is appropriate and executes the processing by the automatic processing unit when the reliability is equal to or higher than a predetermined threshold value.
 上記した目的を達成するために本発明に係る会計処理システムは、、証憑の画像データから仕訳要素をテキストとして出力するための仕訳要素抽出AIにより、証憑の画像データから仕訳要素をテキストとして抽出する仕訳要素抽出部と、前記仕訳要素のテキストを用いた処理を予め登録された処理手順で自動的に実行可能な自動処理部と、前記仕訳要素抽出部とは異なる手段で入力された前記証憑の画像データに含まれる仕訳要素のテキストを記憶する仕訳要素データ記憶部と、前記仕訳要素抽出部より抽出された仕訳要素のテキストと、当該仕訳要素に対応する前記仕訳要素データ記憶部に記憶された仕訳要素のテキストとを突合し、整合した場合に、入力された情報が妥当であると判定し、前記自動処理部による処理を実行させる判定部と、を備える。 In order to achieve the above object, the accounting system according to the present invention extracts the journal element as text from the image data of the voucher by the journal element extraction AI for outputting the journal element as text from the image data of the voucher. The journal element extraction unit, the automatic processing unit that can automatically execute the processing using the text of the journal element by the processing procedure registered in advance, and the voucher input by a means different from the journal element extraction unit. It is stored in the journal element data storage unit that stores the text of the journal element included in the image data, the text of the journal element extracted from the journal element extraction unit, and the journal element data storage unit that corresponds to the journal element. It is provided with a determination unit that determines that the input information is appropriate and executes processing by the automatic processing unit when the texts of the journal elements are matched and matched.
 上記した目的を達成するために本発明に係る会計処理システムは、、入力された仕訳要素に対し、仕訳要素に応じた仕訳結果を出力するための仕訳AIにより、仕訳結果を出力し、且つ当該仕訳結果の信頼度を出力する仕訳部と、前記仕訳結果を用いた処理を予め登録された処理手順で自動的に実行可能な自動処理部と、前記仕訳部より出力された前記信頼度が所定の閾値以上である場合に、入力された情報が妥当であると判定し、前記自動処理部による処理を実行させる判定部と、を備える。 In order to achieve the above object, the accounting system according to the present invention outputs the journal result to the input journal element by the journal AI for outputting the journal result according to the journal element, and the subject A journal unit that outputs the reliability of the journal result, an automatic processing unit that can automatically execute processing using the journal result by a processing procedure registered in advance, and the reliability output from the journal unit are predetermined. When the value is equal to or greater than the threshold value of, it is determined that the input information is appropriate, and a determination unit for executing the process by the automatic processing unit is provided.
 また、上述の会計処理装置において、前記判定部は、入力された情報が妥当でないと判定した場合には、警告表示データを生成してもよい。 Further, in the above-mentioned accounting processing device, the determination unit may generate warning display data when it determines that the input information is not valid.
 また、上述の会計処理装置において、前記自動処理部は、前記仕訳要素を用いた自動仕訳を行う処理を自動的に実行可能であってもよい。 Further, in the above-mentioned accounting processing apparatus, the automatic processing unit may be able to automatically execute a process of performing automatic journalizing using the journal element.
 また、上述の会計処理装置において、前記自動処理部は、前記仕訳結果を特定の宛先にメール送信する処理を自動的に実行可能であってもよい。 Further, in the above-mentioned accounting processing device, the automatic processing unit may be able to automatically execute a process of sending the journal entry result by e-mail to a specific destination.
 また、上記した目的を達成するために、本発明に係る会計処理方法は、証憑の画像データから仕訳要素をテキストとして出力するための仕訳要素抽出AIにより、証憑の画像データから仕訳要素をテキストとして抽出し、且つ当該抽出の信頼度を出力する仕訳要素抽出工程と、前記仕訳要素抽出工程より出力された前記信頼度が所定の閾値以上である場合に、抽出した仕訳要素のテキストが妥当であると判定する判定工程と、前記判定工程にて抽出した仕訳要素が妥当であると判定された場合に、前記仕訳要素のテキストを用いた処理を予め登録された処理手順で自動的に実行する自動処理工程と、をコンピュータが実行する。 Further, in order to achieve the above object, the accounting method according to the present invention uses the journal element extraction AI for outputting the journal element as text from the image data of the voucher, and uses the journal element as text from the image data of the voucher. The text of the extracted journal element is appropriate when the journal element extraction step that extracts and outputs the reliability of the extraction and the reliability output from the journal element extraction step are equal to or higher than a predetermined threshold. When it is determined that the judgment step of determining that the journal element is appropriate and the journal element extracted in the determination step is appropriate, the process using the text of the journal element is automatically executed by the pre-registered processing procedure. The processing process is performed by the computer.
 また、上記した目的を達成するために、本発明に係る会計処理プログラムでは、コンピュータに、上述の会計処理方法を実行させる。 Further, in order to achieve the above-mentioned object, in the accounting processing program according to the present invention, a computer is made to execute the above-mentioned accounting processing method.
 上記手段を用いる本発明によれば、担当者による確認作業や単純作業を削減し、会計処理の全体的な作業効率を向上させることができる。 According to the present invention using the above means, it is possible to reduce the confirmation work and the simple work by the person in charge and improve the overall work efficiency of the accounting process.
本発明の一実施形態に係る会計処理システムの全体構成を示した概略構成図である。It is a schematic block diagram which showed the whole structure of the accounting processing system which concerns on one Embodiment of this invention. 会計処理装置により実行される会計処理の流れを示したフローチャートである。It is a flowchart which showed the flow of the accounting processing executed by the accounting processing apparatus. 会計処理装置により実行される会計処理の遷移の一例を示す説明図である。It is explanatory drawing which shows an example of the transition of the accounting processing executed by the accounting processing apparatus. 会計処理装置により実行される会計処理の遷移の一例を示す説明図である。It is explanatory drawing which shows an example of the transition of the accounting processing executed by the accounting processing apparatus.
 以下、本発明の一実施形態を図面に基づき説明する。 Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
 図1は本発明の一実施形態に会計処理システムの全体構成を示した概略構成図であり、同図に基づき本実施形態の構成について説明する。 FIG. 1 is a schematic configuration diagram showing an overall configuration of an accounting processing system according to an embodiment of the present invention, and the configuration of the present embodiment will be described based on the same diagram.
 図1に示すように、本実施形態に係る会計処理システム1は、インターネット、VPN(Virtual Private Network)等の通信網2を介して、ユーザ側の各装置と会計処理サービス提供者側の会計処理装置10とが接続されて構成されている。なお、説明の簡略化のため図1では一人のユーザのみを示しているが、会計処理装置10は通信網2を介して複数のユーザと接続可能である。 As shown in FIG. 1, the accounting processing system 1 according to the present embodiment accounts for each device on the user side and accounting processing on the accounting processing service provider side via a communication network 2 such as the Internet and VPN (Virtual Private Network). It is configured by being connected to the device 10. Although only one user is shown in FIG. 1 for simplification of the description, the accounting processing apparatus 10 can connect to a plurality of users via the communication network 2.
 ユーザは、例えば税理士及び会計士等の専門家であったり、直接会計処理を行う法人や個人等であり、少なくとも読取装置3と情報端末4を有している。 The user is, for example, an expert such as a tax accountant or an accountant, or a corporation or an individual who directly performs accounting processing, and has at least a reading device 3 and an information terminal 4.
 読取装置3は、例えばスキャナ又はカメラ等の光学機器であり、証憑を画像データとして取り込める装置である。なお、本実施形態及び特許請求の範囲における「証憑」という文言は、領収書やレシート、その他の受領書、請求書、納品書、金融機関の通帳、会計上金銭授受の証明となる書類、電子マネー等のICカードによる取引情報も含むものとする。 The reading device 3 is an optical device such as a scanner or a camera, and is a device that can capture a voucher as image data. The word "voucher" in the present embodiment and claims is used for receipts, receipts, other receipts, invoices, invoices, bankbooks of financial institutions, documents certifying money transfer in accounting, and electronic money. It shall also include transaction information using IC cards such as money.
 情報端末4は、例えばパーソナルコンピュータ(以下、PCという)や、スマートフォン、タブレットPC、及び携帯電話のような携帯端末である。情報端末4は、ユーザの操作を受け付ける入力部4aと、少なくともweb情報を表示可能な表示部4bを有している。 The information terminal 4 is, for example, a personal computer (hereinafter referred to as a PC), a smartphone, a tablet PC, and a mobile terminal such as a mobile phone. The information terminal 4 has an input unit 4a that accepts user operations and a display unit 4b that can display at least web information.
 ユーザは、読取装置3により証憑の画像データを取得して、情報端末4により会計処理装置10に送信可能であるとともに、会計処理装置10に対して情報の送受信が可能である。なお、図1では読取装置3と情報端末4とが別体のように示しているが、カメラ付きの携帯端末のように読取装置3と情報端末4とが一体であってもよい。また、ユーザ自身が読取装置3を所有している必要はなく、例えば外部の読取装置により読み取った証憑の画像データをメールやwebを介して取得してもよい。 The user can acquire the image data of the voucher by the reading device 3 and transmit it to the accounting processing device 10 by the information terminal 4, and can also send and receive information to and from the accounting processing device 10. Although the reading device 3 and the information terminal 4 are shown as separate bodies in FIG. 1, the reading device 3 and the information terminal 4 may be integrated as in a mobile terminal with a camera. Further, the user does not have to own the reading device 3, and for example, the image data of the voucher read by an external reading device may be acquired via an e-mail or a web.
 一方、会計処理サービス提供者(以下、単にサービス提供者ともいう)は、いわゆるクラウドコンピューティングにより会計処理サービスを提供する事業者であり、会計処理装置10を管理する者である。 On the other hand, the accounting processing service provider (hereinafter, also simply referred to as a service provider) is a business operator that provides accounting processing services by so-called cloud computing, and is a person who manages the accounting processing device 10.
 会計処理装置10は、プログラムに基づき仕訳処理を実行する1又は複数のサーバ(コンピュータ)を有し、機能的には主に、証憑の画像データから仕訳要素をテキストとして抽出する仕訳要素抽出部11と、抽出した仕訳要素の妥当性を判定する仕訳要素判定部12と、仕訳要素のテキストを用いた処理を予め登録された処理手順(第1のRPAワークフロー)で実行する第1のRPA実行部13(自動処理部)、仕訳要素に基づき自動仕訳を行う仕訳部14、仕訳結果の整合性を判定する仕訳判定部15、仕訳結果に対して予め定められた処理作業(第2のRPAワークフロー)を実行する第2のRPA実行部16を有している。なお、本実施形態において、RPA(Robotic Process Automation)とは、ソフトウェアロボットにより、情報端末4の表示部4b等の画面上に表示されるアプリケーションやシステム画面を識別し、ユーザの操作と同様の処理手順を自動的に行うことをいう。 The accounting processing device 10 has one or a plurality of servers (computers) that execute journal processing based on a program, and functionally mainly, a journal element extraction unit 11 that extracts journal elements as text from the image data of a voucher. , The journal element determination unit 12 that determines the validity of the extracted journal element, and the first RPA execution unit that executes the process using the text of the journal element in the pre-registered processing procedure (first RPA workflow). 13 (Automatic processing unit), Journal unit 14 that automatically performs journals based on journal elements, Journal judgment unit 15 that determines the consistency of journal results, Predetermined processing work for journal results (second RPA workflow) It has a second RPA execution unit 16 that executes the above. In this embodiment, RPA (Robotic Process Automation) identifies an application or system screen displayed on the screen of the display unit 4b or the like of the information terminal 4 by a software robot, and performs the same processing as the user's operation. It means to perform the procedure automatically.
 また、会計処理装置10は、ユーザが情報端末4を介して経費申請した情報が記憶されている申請データベース20(以下、データベースを「DB」と記す)、仕訳要素抽出AI及び仕訳AIを生成する学習システム21と、第1のRPA及び第2のRPAを設定するRPA設定部22を有している。 Further, the accounting processing device 10 generates an application database 20 (hereinafter, the database is referred to as “DB”), a journal element extraction AI, and a journal AI in which information for which the user has applied for expenses via the information terminal 4 is stored. It has a learning system 21 and an RPA setting unit 22 for setting a first RPA and a second RPA.
 仕訳要素抽出部11は、ユーザから証憑の画像データを受信し、当該画像データから仕訳要素を抽出する機能を有している。具体的には、仕訳要素抽出部11は、証憑の画像データから仕訳要素を抽出するための仕訳要素抽出AIを有し、当該複数の仕訳要素抽出AIにより証憑の画像データから仕訳要素を抽出可能である。 The journal element extraction unit 11 has a function of receiving the image data of the voucher from the user and extracting the journal element from the image data. Specifically, the journal element extraction unit 11 has a journal element extraction AI for extracting the journal element from the image data of the voucher, and the journal element can be extracted from the image data of the voucher by the plurality of journal element extraction AIs. Is.
 仕訳要素抽出AIは、証憑の画像データ内から仕訳要素に対応する部分(位置)を特定し、特定された部分の内容に対応する仕訳要素をテキストとして抽出する。つまり、仕訳要素抽出AIは、学習システム21において、機械学習により画像データ内から仕訳要素に対応する部分を含む領域を指定し、当該指定された部分の内容に対応する仕訳要素をテキストとして出力することを学習したAIである。例えば、仕訳要素抽出AIは、証憑の画像データ内おいて、日付部分、金額部分、取引先部分、摘要部分を指定し、日付部分や金額部分においては数字を認識して年月日や金額のテキストを出力し、取引先に対応する部分や摘要に対応する部分においては文字を認識して取引先や摘要のテキストを出力する。 Journal element extraction AI specifies the part (position) corresponding to the journal element from the image data of the voucher, and extracts the journal element corresponding to the content of the specified part as text. That is, the journal element extraction AI specifies an area including a portion corresponding to the journal element from the image data by machine learning in the learning system 21, and outputs the journal element corresponding to the content of the specified portion as text. It is AI who learned that. For example, the journal element extraction AI specifies a date part, an amount part, a business partner part, and a description part in the image data of a voucher, and recognizes a number in the date part and the amount part to recognize the date part and the amount amount. The text is output, and the text of the business partner and the description is output by recognizing the characters in the part corresponding to the business partner and the part corresponding to the description.
 また、仕訳要素抽出部11は、仕訳要素抽出AIにより文字や数字を認識してテキストを出力するだけでなく、例えば、ロゴマークや印影又は電話番号のみが抽出された場合には、図示しないが予め企業情報を記憶した企業情報DBより検索して、又はインターネットに公開されている情報を検索することで、取引先名のテキストとして出力してもよい。また、レシート等のように宛名の記載がない場合には、画像データを送信してきたユーザ名を取引元のテキストとして出力してもよいし、ユーザの顧客である企業を予め設定しておき当該ユーザから送信された画像データはその設定された企業名を取引元のテキストとして出力してもよい。 Further, the journal element extraction unit 11 not only recognizes characters and numbers by the journal element extraction AI and outputs text, but also, for example, when only a logo mark, an imprint, or a telephone number is extracted, it is not shown. It may be output as the text of the business partner name by searching from the company information DB in which the company information is stored in advance or by searching the information published on the Internet. In addition, when there is no description of the address such as a receipt, the user name that sent the image data may be output as the text of the transaction source, or the company that is the customer of the user is set in advance. The image data transmitted from the user may output the set company name as the text of the transaction source.
 なお、仕訳要素抽出AIは、証憑の画像データ内から仕訳要素に対応する部分(位置)を特定する画像認識AIと、特定された部分の内容に対応する仕訳要素をテキストとして抽出する文字認識AIの2つのAIで構成してもよい。 The journal element extraction AI is an image recognition AI that specifies a part (position) corresponding to the journal element from the image data of the voucher, and a character recognition AI that extracts the journal element corresponding to the content of the specified part as text. It may be composed of two AIs.
 仕訳要素としては、例えば日付、金額、取引先、摘要(但し書き、商品名含む)、取引元(宛名含む)があり、これらに対応する数字、文字、図形(例えばロゴマーク、印影、その他企業を特定可能な図柄)、及び証憑の外観(例えば通帳や領収書の大きさ、色)がある。 Journal elements include, for example, date, amount, business partner, description (including proviso and product name), business source (including address), and the corresponding numbers, letters, graphics (for example, logo mark, imprint, and other companies). There is a identifiable pattern) and the appearance of the voucher (eg, the size and color of the passbook or receipt).
 仕訳要素抽出部11は、例えば日付については、「日付」「年」「月」「日」等の文字や「/」等の記号の前後や上下の数字部分を特定する。金額については「¥」等の記号や商品名、「金額」「預り金」「小計」「合計」「税」「お釣り」「割引」「円」「支払い」「預り」「残高」等の金額に関係する文字の前後や上下の数字部分を特定する。そして、本実施形態では金額については、例えば「合計 1000円」「お釣り 50円」等、金額に関係する文字や数字毎に仕訳要素を抽出する。なお、仕訳要素抽出部11は、抽出された文字の意味についても認識可能であり、例えば「小計」は商品の価格を合算した金額である等の会計上の関係性まで特定可能である。 For example, for a date, the journal element extraction unit 11 specifies numbers before, after, and above and below characters such as "date", "year", "month", and "day" and symbols such as "/". Amounts include symbols such as "¥", product names, "amount", "deposit", "subtotal", "total", "tax", "change", "discount", "yen", "payment", "deposit", "balance", etc. Identify the numbers before, after, and above and below the characters related to. Then, in the present embodiment, as for the amount of money, a journal element is extracted for each character or number related to the amount of money, for example, "total 1000 yen" or "change 50 yen". The journal element extraction unit 11 can also recognize the meaning of the extracted characters, and for example, the "subtotal" can specify the accounting relationship such as the total amount of the prices of the products.
 また、取引先については、「株式会社」「(株)」「(カ)」等の文字の前後の文字部分や、ロゴマーク、電話番号、証憑の外観を特定して、これらの情報に基づく会社名や個人名に対応する部分を特定する。摘要については、「但」等の文字に続く文字部分を特定する。取引元については、「様」等の文字の前にある文字の部分を特定する。 For business partners, the characters before and after the characters such as "Co., Ltd.", "Co., Ltd." and "(F)", the logo mark, telephone number, and the appearance of the voucher are specified and based on this information. Identify the part that corresponds to your company or personal name. For the abstract, specify the character part following the character such as "However". For the trading source, specify the part of the character before the character such as "sama".
 なお、仕訳要素はこれに限られるものではなく、また仕訳要素の抽出に用いる数字、文字、図形もこれに限られるものではない。例えば、証憑に、購入品の数量が記載されている場合には数量を仕訳要素として含めてもよいし、同席者の名前や人数等の情報が記載されている場合には、同席者及び人数を仕訳要素として含めてもよい。また、各企業を特定するために設定された番号(法人番号、事業所番号)を抽出してもよい。 Note that the journal elements are not limited to this, and the numbers, letters, and figures used to extract the journal elements are not limited to this. For example, if the voucher contains the quantity of purchased items, the quantity may be included as a journal entry factor, and if information such as the names and number of attendees is stated, the attendees and the number of attendees. May be included as a journal element. In addition, a number (corporate number, business office number) set to identify each company may be extracted.
 また、仕訳要素抽出部11は、仕訳要素抽出AIにより出力した仕訳要素の信頼度(以下、仕訳要素信頼度Reという)も出力可能である。この仕訳要素信頼度Reとは、仕訳要素抽出AIの判断の確度であり、例えばパーセントで表すことが可能である。つまり、仕訳要素信頼度Reが高いほど仕訳要素抽出AIにより出力された仕訳要素のテキストは仕訳要素として妥当性が高く、仕訳要素信頼度Reが低いほど妥当性が低くなる。なお、仕訳要素信頼度Reはパーセント表示に限られず、所定の閾値以上を○、未満を×とする2段階評価で表示したり、閾値を2つ設定し○、△、×の3段階評価で表示したりしてもよい。 In addition, the journal element extraction unit 11 can also output the reliability of the journal element output by the journal element extraction AI (hereinafter referred to as the journal element reliability Re). The journal element reliability Re is the accuracy of the judgment of the journal element extraction AI, and can be expressed as a percentage, for example. That is, the higher the journal element reliability Re, the higher the validity of the journal element text output by the journal element extraction AI, and the lower the journal element reliability Re, the lower the validity. The journal element reliability Re is not limited to the percentage display, and is displayed in a two-step evaluation in which a predetermined threshold value or more is ○ and less than a predetermined threshold value is ×, or two threshold values are set and a three-step evaluation of ○, △, and × is performed. It may be displayed.
 仕訳要素抽出部11と接続されている仕訳要素判定部12は、仕訳要素抽出部11より出力されたテキストの仕訳要素としての妥当性を判定する機能を有している。仕訳要素判定部12は、仕訳要素のテキストの妥当性を、仕訳要素抽出部11が出力する仕訳要素信頼度Reや、ユーザが入力した仕訳要素に関する情報との突合に基づいて判定する。 The journal element determination unit 12 connected to the journal element extraction unit 11 has a function of determining the validity of the text output from the journal element extraction unit 11 as a journal element. The journal element determination unit 12 determines the validity of the text of the journal element based on the journal element reliability Re output by the journal element extraction unit 11 and the matching with the information regarding the journal element input by the user.
 仕訳要素判定部12の仕訳要素信頼度Reに基づく判定は、例えば、仕訳要素信頼度Reに対応する第1の閾値T1が設定されており、仕訳要素信頼度Reが第1の閾値T1以上であれば抽出された仕訳要素は妥当と判定する。一方、仕訳要素信頼度Reが第1の閾値T1未満であれば抽出された仕訳要素は妥当でないと判定する。 In the determination based on the journal element reliability Re of the journal element determination unit 12, for example, the first threshold value T1 corresponding to the journal element reliability Re is set, and the journal element reliability Re is equal to or higher than the first threshold T1. If so, the extracted journal element is judged to be valid. On the other hand, if the journal element reliability Re is less than the first threshold value T1, it is determined that the extracted journal element is not valid.
 また、仕訳要素判定部12のユーザが入力した仕訳要素に関する情報との突合に基づく判定は、仕訳要素抽出部11にて抽出された仕訳要素と、申請DB20に記憶された仕訳要素の情報とを突合し、整合した場合には妥当と判定し、不整合である場合は妥当でないと判定する。この突合の整合性は完全一致に限られず、例えば一致度合いを算出し、一定程度整合している場合に妥当と判定してもよい。この一致度合いは仕訳要素信頼度Reと同様にパーセント表示としたり、○や×の2段階評価、○、△、×の3段階評価としたりしてもよい。 Further, in the determination based on the matching with the information about the journal element input by the user of the journal element determination unit 12, the journal element extracted by the journal element extraction unit 11 and the information of the journal element stored in the application DB 20 are combined. If they match and match, it is judged to be valid, and if they are inconsistent, it is judged to be invalid. The consistency of this matching is not limited to perfect matching, and for example, the degree of matching may be calculated and determined to be appropriate when the matching is to a certain extent. This degree of agreement may be expressed as a percentage in the same manner as the journal element reliability Re, or may be evaluated on a two-point scale of ○ or × or on a three-point scale of ○, Δ, or ×.
 さらに、仕訳要素判定部12は、妥当でない仕訳要素については通常表示と異なる警告表示データを生成し、ユーザの情報端末4の表示部4bに提示させる。 Further, the journal element determination unit 12 generates warning display data different from the normal display for invalid journal elements, and causes the display unit 4b of the user's information terminal 4 to present the warning display data.
 なお、申請DB20は、ユーザが読取装置3により読み取った証憑の画像データとともに、当該証憑の内容をユーザが情報端末4を介して会計処理装置10に送信した情報が記憶されている。この証憑の画像データとユーザが入力した証憑の内容情報とは紐づけされており、仕訳要素判定部12では、この紐づけされた証憑の画像データと内容情報とから突合を行う。 The application DB 20 stores the image data of the voucher read by the user by the reading device 3 and the information that the user transmits the contents of the voucher to the accounting processing device 10 via the information terminal 4. The image data of the voucher and the content information of the voucher input by the user are associated with each other, and the journal element determination unit 12 collates the image data of the associated voucher with the content information.
 仕訳要素判定部12と接続されている第1のRPA実行部13は、RPA設定部22にて登録された第1のRPAワークフローを実行する機能を有している。第1のRPAワークフローは、仕訳要素に対する処理作業であり、本実施形態では自動仕訳のための入力処理を行う。具体的には、第1のRPA実行部13は、情報端末4の表示部4bの画面上に表示された、仕訳要素判定部12により妥当と判定された仕訳要素をコピーして、自動仕訳用の仕訳要素入力欄に貼り付ける作業を繰り返し、入力欄が埋まった後には、自動仕訳を実行するボタンを選択する。 The first RPA execution unit 13 connected to the journal element determination unit 12 has a function of executing the first RPA workflow registered in the RPA setting unit 22. The first RPA workflow is a processing work for a journal element, and in the present embodiment, input processing for automatic journal is performed. Specifically, the first RPA execution unit 13 copies the journal elements determined to be valid by the journal element determination unit 12 displayed on the screen of the display unit 4b of the information terminal 4, and is used for automatic journal entry. Repeat the work of pasting into the journal element input field of, and after the input field is filled, select the button to execute automatic journal.
 仕訳部14は、入力された仕訳要素に応じた勘定科目を出力する機能を有している。この仕訳要素に応じた勘定科目の出力は、例えば仕訳AIにより行う。仕訳AIは、学習システム21において、予め機械学習により仕訳要素に対する勘定科目を出力することを学習した自動仕訳のAIである。当該仕訳部14において出力された勘定科目は、仕訳要素とともに、仕訳結果として仕訳判定部15に出力される。 The journal unit 14 has a function of outputting an account item according to the input journal element. The output of the account item corresponding to this journal element is performed by, for example, the journal AI. The journal AI is an automatic journal AI that has learned in advance to output an account for a journal element by machine learning in the learning system 21. The account item output in the journal entry unit 14 is output to the journal entry determination unit 15 as a journal entry result together with the journal entry element.
 また、仕訳部14は、仕訳AIにより出力した仕訳結果の信頼度(以下、仕訳信頼度という)も出力可能である。この仕訳信頼度Rjとは、仕訳AIの判断の確度であり、例えばパーセントで表すことが可能である。つまり、仕訳信頼度Rjが高いほど仕訳AIにより出力された仕訳結果は仕訳として妥当性が高く、仕訳信頼度Rjが低いほど妥当性が低くなる。 In addition, the journal unit 14 can also output the reliability of the journal result output by the journal AI (hereinafter referred to as the journal reliability). The journal reliability Rj is the accuracy of the judgment of the journal AI, and can be expressed as a percentage, for example. That is, the higher the journal reliability Rj, the higher the validity of the journal result output by the journal AI, and the lower the journal reliability Rj, the lower the validity.
 仕訳部14と接続されている仕訳判定部15は、仕訳部14より出力された仕訳結果の妥当性を判定する機能を有している。仕訳判定部15は、仕訳結果の妥当性を、仕訳部14が出力する仕訳信頼度Rjに基づいて判定する。 The journal determination unit 15 connected to the journal unit 14 has a function of determining the validity of the journal result output from the journal unit 14. The journal determination unit 15 determines the validity of the journal result based on the journal reliability Rj output by the journal unit 14.
 仕訳判定部15の仕訳信頼度Rjに基づく判定は、例えば、仕訳信頼度Rjに対応する第2の閾値T2が設定されており、仕訳信頼度Rjが第2の閾値T2以上であれば仕訳結果は妥当と判定する。一方、仕訳信頼度Rjが第2の閾値T2未満であれば仕訳結果は妥当でないと判定する。 In the determination based on the journal reliability Rj of the journal determination unit 15, for example, if the second threshold value T2 corresponding to the journal reliability Rj is set and the journal reliability Rj is equal to or higher than the second threshold T2, the journal result is Is judged to be valid. On the other hand, if the journal reliability Rj is less than the second threshold value T2, it is determined that the journal result is not valid.
 さらに、仕訳判定部15は、妥当でない仕訳結果については通常表示と異なる警告表示データを生成し、ユーザの情報端末4の表示部4bに提示させる。 Further, the journal determination unit 15 generates warning display data different from the normal display for an invalid journal result, and causes the display unit 4b of the user's information terminal 4 to present it.
 仕訳判定部15と接続されている第2のRPA実行部16は、RPA設定部22にて登録された第2のRPAワークフローを実行する機能を有している。第2のRPAワークフローは、仕訳結果に対する処理作業であり、例えば情報端末4の表示部4bの画面上に表示された、仕訳判定部15により妥当と判定された仕訳結果をコピーして、メールソフトの新規のメール文に貼り付けた後、宛先に特定のメールアドレス(例えば経理担当者のメールアドレス)を入力して、送信を行う。 The second RPA execution unit 16 connected to the journal determination unit 15 has a function of executing the second RPA workflow registered in the RPA setting unit 22. The second RPA workflow is a processing work for the journal entry result. For example, the journal entry result determined to be appropriate by the journal entry determination unit 15 displayed on the screen of the display unit 4b of the information terminal 4 is copied and mail software is used. After pasting it in the new e-mail text of, enter a specific e-mail address (for example, the e-mail address of the accounting staff) in the destination and send it.
 学習システム21は、上述した仕訳要素抽出AI、及び仕訳AI等を学習させ、学習済みのAIを供給する機能を有している。詳しくは、学習システム21は、証憑の画像データと当該画像データに含まれる仕訳要素からなる教師データ(学習用データ)に基づき機械学習(いわゆるディープラーニング)させることで、仕訳要素抽出AIを生成する。また、学習システム21は、仕訳要素と当該仕訳要素に対応する勘定科目からなる教師データ(学習用データ)に基づき機械学習させることで、仕訳AIを生成する。 The learning system 21 has a function of learning the above-mentioned journal element extraction AI, journal AI, and the like, and supplying the learned AI. Specifically, the learning system 21 generates a journal element extraction AI by performing machine learning (so-called deep learning) based on teacher data (learning data) consisting of voucher image data and journal elements included in the image data. .. Further, the learning system 21 generates a journal AI by performing machine learning based on teacher data (learning data) composed of a journal element and an account item corresponding to the journal element.
 RPA設定部22は、いわゆるRPAツールを有し、ユーザ等の作業者が行った操作手順をRPAワークフローとして記憶する機能を有する。例えば、本実施形態では、上述した第1のRPAワークフロー及び第2のRPAワークフローの操作を、ユーザが事前に情報端末4からRPA設定部22を介して実行して、第1のRPAワークフロー及び第2のRPAワークフローを記憶している。RPA設定部22は、表示部4bを通したユーザの操作を記憶するため、表示部4bに表示可能であれば、例えば会計処理システムとメールソフト等の、複数のシステムや複数のアプリケーションを跨った処理も実行可能である。 The RPA setting unit 22 has a so-called RPA tool, and has a function of storing an operation procedure performed by a worker such as a user as an RPA workflow. For example, in the present embodiment, the user executes the operations of the first RPA workflow and the second RPA workflow described above from the information terminal 4 in advance via the RPA setting unit 22, and the first RPA workflow and the first RPA workflow It remembers 2 RPA workflows. Since the RPA setting unit 22 stores the user's operation through the display unit 4b, if it can be displayed on the display unit 4b, the RPA setting unit 22 straddles a plurality of systems or a plurality of applications such as an accounting processing system and mail software. Processing is also feasible.
 ここで図2を参照すると、会計処理装置10により実行される会計処理の流れを示したフローチャートが示されており、以下同フローチャートに沿って、本実施形態に係る会計処理方法について詳しく説明する。なお、当該会計処理は、ユーザからの証憑の画像データを受信すると、スタートする。 Here, with reference to FIG. 2, a flowchart showing the flow of accounting processing executed by the accounting processing apparatus 10 is shown, and the accounting processing method according to the present embodiment will be described in detail below with reference to the same flowchart. The accounting process starts when the image data of the voucher from the user is received.
 まず、ステップS1として、仕訳要素抽出部11は、仕訳要素抽出AIにより、受信した証憑の画像データから仕訳要素を抽出する。そして、仕訳要素抽出部11は抽出した仕訳要素のテキストと、その仕訳要素信頼度Reを出力する。 First, as step S1, the journal element extraction unit 11 extracts the journal element from the received voucher image data by the journal element extraction AI. Then, the journal element extraction unit 11 outputs the text of the extracted journal element and the journal element reliability Re.
 ステップS2において、仕訳要素判定部12は、抽出された仕訳要素が妥当であるか否かを判定する。具体的には、仕訳要素信頼度Reが第1の閾値T1以上であり、且つ申請DB20に記憶されているユーザが入力した仕訳要素に関する情報と突合して整合しているか否かを判定する。なお、本実施形態の仕訳要素判定部12は、仕訳要素信頼度Reに基づく判定と、突合に基づく判定の両方を行っているが、どちらか一方の判定のみを行うものであってもよい。当該判定結果が偽(No)である場合、即ち仕訳要素信頼度Reが第1の閾値T1未満、又は突合結果が不整合であった場合は、ステップS3に進む。 In step S2, the journal element determination unit 12 determines whether or not the extracted journal element is appropriate. Specifically, it is determined whether or not the journal element reliability Re is equal to or higher than the first threshold value T1 and matches with the information regarding the journal element input by the user stored in the application DB 20. The journal element determination unit 12 of the present embodiment makes both a determination based on the journal element reliability Re and a determination based on the matching, but may determine only one of them. If the determination result is false (No), that is, if the journal element reliability Re is less than the first threshold value T1, or if the matching result is inconsistent, the process proceeds to step S3.
 ステップS3において、仕訳要素判定部12は、警告表示をユーザの情報端末4の表示部4bに表示させて、抽出した仕訳要素に対してユーザ(人)による確認と修正を促す。 In step S3, the journal element determination unit 12 displays a warning display on the display unit 4b of the user's information terminal 4, and prompts the user (person) to confirm and correct the extracted journal element.
 一方、ステップS2の判定結果が真(Yes)であった場合、即ち仕訳要素信頼度Reが第1の閾値T1以上であり、且つ突合結果して整合していた場合は、ステップS4に進む。 On the other hand, if the determination result in step S2 is true (Yes), that is, if the journal element reliability Re is equal to or higher than the first threshold value T1 and the matching result is consistent, the process proceeds to step S4.
 ステップS4において、第1のRPA実行部13は、第1のRPAワークフローにより、上述した自動仕訳のための入力処理を行う。なお、上記ステップS3では、警告表示に従い、この入力処理を人手で行うものとする。 In step S4, the first RPA execution unit 13 performs the above-mentioned input processing for automatic journal entry by the first RPA workflow. In step S3, this input process is manually performed according to the warning display.
 そして、ステップS5において、仕訳部14は仕訳AIにより、入力された仕訳要素に対する仕訳結果と、仕訳信頼度Rjを出力する。 Then, in step S5, the journal unit 14 outputs the journal result for the input journal element and the journal reliability Rj by the journal AI.
 次のステップS6において、仕訳判定部15は、出力された仕訳結果が妥当であるか否かを判定する。具体的には、仕訳信頼度Rjが第2の閾値T2以上であるか否かを判定する。当該判定結果が偽(No)である場合、即ち仕訳信頼度Rjが第2の閾値T2未満であった場合は、ステップS7に進む。 In the next step S6, the journal determination unit 15 determines whether or not the output journal result is valid. Specifically, it is determined whether or not the journal reliability Rj is equal to or higher than the second threshold value T2. If the determination result is false (No), that is, if the journal entry reliability Rj is less than the second threshold value T2, the process proceeds to step S7.
 ステップS7において、仕訳判定部15は、警告表示をユーザの情報端末4の表示部4bに表示させて、出力された仕訳結果に対してユーザ(人)による確認と修正を促す。 In step S7, the journal determination unit 15 displays a warning display on the display unit 4b of the user's information terminal 4, and prompts the user (person) to confirm and correct the output journal result.
 一方、ステップS6の判定結果が真(Yes)であった場合、即ち仕訳信頼度Rjが第2の閾値T2以上であった場合は、ステップS8に進む。 On the other hand, if the determination result in step S6 is true (Yes), that is, if the journal reliability Rj is equal to or higher than the second threshold value T2, the process proceeds to step S8.
 ステップS8において、第2のRPA実行部16は、第2のRPAワークフローにより、上述した仕訳完了のメール送信処理を行い、当該ルーチンを終了する。なお、ステップS7では、警告表示に従い、このメール送信処理を人手で行うものとする。 In step S8, the second RPA execution unit 16 performs the above-mentioned journal entry completion email transmission process by the second RPA workflow, and ends the routine. In step S7, this mail transmission process is manually performed according to the warning display.
 このように、会計処理装置10は、証憑の画像データを取得する毎に、当該ルーチンを実行することで、各画像データから仕訳要素を抽出し、妥当な仕訳要素であれば自動的に自動仕訳を実行し、この仕訳結果が妥当であれば自動的にメール送信まで実行可能である。 In this way, the accounting processing device 10 extracts the journal element from each image data by executing the routine every time the image data of the voucher is acquired, and automatically automatically journals if it is a valid journal element. Is executed, and if this journal result is valid, it is possible to automatically send an email.
 次に図3、図4を参照すると、いずれも本発明の一実施形態に係る会計処理装置により実行される会計処理の遷移の一例を示す説明図が示されており、これらの図に基づき証憑の画像データから仕訳完了のメール送信までの具体的な遷移について説明する。なお、図3、図4に示す仕訳要素抽出欄A、仕訳要素入力欄B、仕訳結果欄Cは、ユーザの情報端末4の表示部4bに表示される表示例である。 Next, with reference to FIGS. 3 and 4, explanatory diagrams showing an example of the transition of accounting processing executed by the accounting processing apparatus according to the embodiment of the present invention are shown, and the voucher is based on these figures. The specific transition from the image data of the above to the sending of the journal entry completion email will be described. The journal element extraction field A, the journal element input field B, and the journal result field C shown in FIGS. 3 and 4 are display examples displayed on the display unit 4b of the user's information terminal 4.
 図3の仕訳要素抽出欄Aは、レシートの画像データから仕訳要素を抽出した場合の表示例であり、画面左側にスキャンされたレシートの元画像が、画面中央に仕訳要素の抽出結果が、画面右側にユーザが申請した申請内容がそれぞれ表示されている。つまり仕訳要素抽出欄Aは、図2のステップS2時点の表示例である。 The journal element extraction column A in FIG. 3 is a display example when the journal element is extracted from the image data of the receipt. The original image of the receipt scanned on the left side of the screen and the extraction result of the journal element in the center of the screen are displayed on the screen. The application details applied by the user are displayed on the right side. That is, the journal element extraction column A is a display example at the time of step S2 in FIG.
 詳しくは、レシートの元画像において点線の枠で示されているように、仕訳要素抽出部11は日付に対応する部分30aと、合計金額に対応する部分31aと、摘要に対応する部分32aを特定し、これらの拡大図30b、31b、32bが抽出結果に表示されている。なお、この点線は実際には表示部4bに表示されていなくてもよい。 Specifically, as shown by the dotted line frame in the original image of the receipt, the journal element extraction unit 11 specifies the part 30a corresponding to the date, the part 31a corresponding to the total amount, and the part 32a corresponding to the description. However, these enlarged views 30b, 31b, and 32b are displayed in the extraction result. It should be noted that this dotted line does not have to be actually displayed on the display unit 4b.
 抽出結果には、対応する拡大図の上に、仕訳要素抽出AIによりテキスト化された仕訳要素である日付「2019年10月10日」、金額「1,080円」、摘要「〇〇カフェ」が記載されている。さらに仕訳要素の横には、その仕訳要素信頼度Reが併記されており、図3では、日付の仕訳要素は「90%」、金額の仕訳要素は「85%」、摘要の仕訳要素は「82%」が示されている。例えば、図3では第1の閾値T1が80%に設定されており、いずれの仕訳要素信頼度Reも第1の閾値T1以上である。 The extraction results include the date "October 10, 2019", the amount "1,080 yen", and the description "○○ Cafe", which are the journal elements converted into text by the journal element extraction AI on the corresponding enlarged view. Is described. Further, next to the journal element, the journal element reliability Re is also written. In FIG. 3, the date journal element is "90%", the amount journal element is "85%", and the description journal element is ". 82% "is shown. For example, in FIG. 3, the first threshold value T1 is set to 80%, and the journal element reliability Re is equal to or higher than the first threshold value T1.
 また図4では、申請内容として、抽出結果の仕訳要素と対応して日付欄30c、金額欄31c、摘要欄32cが示されており、日付欄30cには「2019年10月10日」、金額欄31cには「1,080円」、摘要欄32cには「〇〇カフェ」が記載されている。そして仕訳要素の横には、突合結果の一致度合いがパーセントで表示されており、図4では、日付の仕訳要素は「100%」、金額の仕訳要素は「98%」(¥のみ不一致のため)、摘要の仕訳要素は「85%」(株式会社のみ不一致のため)が示されている。例えば、図4では一致度合いの閾値が80%に設定されており、いずれの突合結果もこの閾値以上であり一定程度整合している。 Further, in FIG. 4, the date column 30c, the amount column 31c, and the description column 32c are shown as the application contents corresponding to the journal elements of the extraction result, and the date column 30c shows "October 10, 2019", the amount. "1,080 yen" is described in the column 31c, and "OO cafe" is described in the description column 32c. Next to the journal element, the degree of matching of the matching result is displayed as a percentage. In FIG. 4, the journal element of the date is "100%" and the journal element of the amount is "98%" (because only ¥ is inconsistent). ), The journal entry element of the description is shown as "85%" (because only the corporation does not match). For example, in FIG. 4, the threshold value of the degree of matching is set to 80%, and all the collation results are equal to or higher than this threshold value and are consistent to some extent.
 このように図3、図4の仕訳要素抽出欄Aに示す表示例では、仕訳要素判定部12における判定結果は真(Yes)となる。なお、いずれかの仕訳要素が妥当でなかった場合には、警告表示として、例えば抽出結果において妥当でない仕訳要素の文字を赤字としたり、フラグ表示を行う。なお、以下の流れは図3、図4とも同様となる。 As described above, in the display example shown in the journal element extraction column A of FIGS. 3 and 4, the determination result in the journal element determination unit 12 is true (Yes). If any of the journal elements is not valid, the characters of the journal elements that are not valid in the extraction result are displayed in red or a flag is displayed as a warning display. The following flow is the same for FIGS. 3 and 4.
 次に、第1のRPA実行部13が、第1のRPAワークフローに従って、各仕訳要素をコピーして、仕訳要素入力欄Bの対応する入力欄に貼り付け、各入力欄が埋まったら仕訳実行ボタンを選択する。 Next, the first RPA execution unit 13 copies each journal element according to the first RPA workflow, pastes it into the corresponding input field of the journal element input field B, and when each input field is filled, the journal execution button. Select.
 すると、入力された仕訳要素に基づき、仕訳部14の仕訳AIが仕訳した結果と各勘定科目に対応した仕訳信頼度が、図3、図4の仕訳結果欄Cのように表示される。具体的には、借方には勘定科目「会議費」、金額「1,000」、信頼度「82%」と、「仮払消費税」、金額「80」、信頼度「90%」が記載され、貸方には勘定科目「現金」、金額「1,080」、信頼度「95%」が記載されている。例えば、図3、図4では第2の閾値T2が80%に設定されており、いずれの仕訳信頼度Rjも第2の閾値T2以上である。 Then, based on the entered journal element, the result of journal entry by the journal AI of the journal unit 14 and the journal reliability corresponding to each account are displayed as shown in the journal result column C of FIGS. 3 and 4. Specifically, the debit includes the account "Meeting fee", amount "1,000", reliability "82%", "temporary consumption tax", amount "80", and reliability "90%". The credit is credited with the account "cash", the amount "1,080", and the reliability "95%". For example, in FIGS. 3 and 4, the second threshold value T2 is set to 80%, and the journal entry reliability Rj is equal to or higher than the second threshold value T2.
 したがって、図3、図4の仕訳結果欄Cに示す表示例では、仕訳判定部15における判定結果は真(Yes)となる。なお、いずれかの仕訳結果が妥当でなかった場合には、警告表示として、例えば妥当でない勘定科目、金額、又は信頼度の文字を赤字としたり、フラグ表示を行う。また、各勘定科目にはプルダウンメニューが設定されており、例えば図3、図4の三角記号を選択すると、その他の勘定科目候補がリストアップされてもよい。 Therefore, in the display example shown in the journal entry result column C of FIGS. 3 and 4, the determination result in the journal entry determination unit 15 is true (Yes). If any of the journal entry results is not valid, for example, the characters of the inappropriate account, amount, or reliability are displayed in red or a flag is displayed as a warning display. Further, a pull-down menu is set for each account, and for example, when the triangle symbols in FIGS. 3 and 4 are selected, other account candidates may be listed.
 次に、第2のRPA実行部16が、第2のRPAワークフローに従って、メールソフトの新規のメール文に貼り付けた後、宛先に特定のメールアドレスを入力して、送信を行う。 Next, the second RPA execution unit 16 pastes it into a new mail text of the mail software according to the second RPA workflow, and then inputs a specific mail address in the destination and sends it.
 このように会計処理システム1は、証憑の画像データから仕訳要素を抽出し、抽出した仕訳要素の妥当性が高い場合は、第1のRPAワークフローに従って自動的に自動仕訳に移行する。したがって、抽出された仕訳要素の妥当性の高い場合には、当該仕訳要素を用いた処理も含めて自動化でき、本実施形態であれば、人のチェックや操作を介さずに自動的に自動仕訳に移行することができる。 In this way, the accounting processing system 1 extracts the journal element from the image data of the voucher, and if the extracted journal element is highly valid, it automatically shifts to the automatic journal according to the first RPA workflow. Therefore, if the extracted journal element is highly valid, it can be automated including the processing using the journal element, and in the present embodiment, the automatic journal is automatically performed without human check or operation. Can be migrated to.
 また、抽出した仕訳要素に応じた自動仕訳を行い、その仕訳結果の妥当性が高い場合は、第2のRPAワークフローに従って自動的に担当者へのメール送信を行う。これにより、仕訳結果の妥当性が高い場合には、仕訳結果を用いた処理も含めて自動化でき、本実施形態であれば、人のチェックや操作を介さずに自動的に担当者へのメール送信を行うことができる。 In addition, automatic journalizing is performed according to the extracted journalizing elements, and if the journalizing result is highly valid, an email is automatically sent to the person in charge according to the second RPA workflow. As a result, when the validity of the journal entry result is high, it is possible to automate the process using the journal entry result, and in the present embodiment, an email to the person in charge is automatically sent without human check or operation. You can send.
 さらに、抽出した仕訳要素の妥当性が低い場合や、仕訳結果の妥当性が低い場合には、ユーザにその旨を警告し、確認及び修正を促す。このように情報の妥当性が低い場合に限って警告表示を出すことで、人によるチェックを最小限に抑えつつ、情報の正確性を確保することができる。 Furthermore, if the validity of the extracted journal element is low or the validity of the journal result is low, the user is warned to that effect and urged to confirm and correct it. By issuing a warning display only when the validity of the information is low in this way, it is possible to ensure the accuracy of the information while minimizing the checks by humans.
 以上のことから本実施形態における会計処理システム1、会計処理方法、会計処理プログラムによれば、ユーザの経理担当者による確認作業や単純作業を削減し、会計処理の全体的な作業効率を向上させることができる。 From the above, according to the accounting processing system 1, the accounting processing method, and the accounting processing program in the present embodiment, the confirmation work and the simple work by the accounting staff of the user are reduced, and the overall work efficiency of the accounting processing is improved. be able to.
 以上で本発明の実施形態の説明を終えるが、本発明の態様はこの実施形態に限定されるものではない。 The description of the embodiment of the present invention is completed above, but the aspect of the present invention is not limited to this embodiment.
 例えば、上記実施形態では、第1のRPAワークフローは自動仕訳のための入力処理を、第2のRPAワークフローは仕訳結果を特定の宛先にメール送信する処理を行っているが、第1のRPAワークフロー及び第2のRPAワークフローとして設定される自動処理はこれに限られるものではなく、他の処理手順を登録してもよい。 For example, in the above embodiment, the first RPA workflow performs an input process for automatic journal entry, and the second RPA workflow performs a process of sending the journal entry result by e-mail to a specific destination, but the first RPA workflow And the automatic processing set as the second RPA workflow is not limited to this, and other processing procedures may be registered.
 また、図3ではレシートを例に本実施形態の一例を説明したが、証憑はレシートに限られるものではなく、領収書等の他の証憑にも同様に適用可能である。 Further, in FIG. 3, an example of this embodiment is described using a receipt as an example, but the voucher is not limited to the receipt, and can be similarly applied to other vouchers such as receipts.
 また、上記実施形態の会計処理システム1は、仕訳要素の抽出から仕訳まで一貫して自動処理可能なシステムであるが、例えば、仕訳要素の抽出のみ、自動仕訳のみを有するシステムにも適用可能である。 Further, the accounting processing system 1 of the above embodiment is a system capable of consistently and automatically processing from the extraction of journal elements to the journals, but can be applied to, for example, a system having only extraction of journal elements and only automatic journals. is there.
 1 会計処理システム
 2 通信網
 3 読取装置
 4 情報端末
 4a 入力部
 4b 表示部
 10 会計処理装置
 11 仕訳要素抽出部
 12 仕訳要素判定部
 13 第1のRPA実行部
 14 仕訳部
 15 仕訳判定部
 16 第2のRPA実行部
 20 申請データベース
 21 学習システム
 22 RPA設定部
1 Accounting processing system 2 Communication network 3 Reading device 4 Information terminal 4a Input unit 4b Display unit 10 Accounting processing device 11 Journal element extraction unit 12 Journal element judgment unit 13 1st RPA execution unit 14 Journal unit 15 Journal judgment unit 16 2nd RPA Execution Department 20 Application Database 21 Learning System 22 RPA Setting Department

Claims (8)

  1.  証憑の画像データから仕訳要素をテキストとして出力するための仕訳要素抽出AIにより、証憑の画像データから仕訳要素をテキストとして抽出し、且つ当該抽出の信頼度を出力する仕訳要素抽出部と、
     前記仕訳要素のテキストを用いた処理を予め登録された処理手順で自動的に実行可能な自動処理部と、
     前記仕訳要素抽出部より出力された前記信頼度が所定の閾値以上である場合に、入力された情報が妥当であると判定し、前記自動処理部による処理を実行させる判定部と、
     を備える会計処理システム。
    Journal element extraction for outputting journal elements as text from voucher image data A journal element extraction unit that extracts journal elements as text from voucher image data and outputs the reliability of the extraction.
    An automatic processing unit that can automatically execute processing using the text of the journal element by a processing procedure registered in advance, and
    When the reliability output from the journal element extraction unit is equal to or higher than a predetermined threshold value, a determination unit that determines that the input information is valid and executes processing by the automatic processing unit, and a determination unit.
    Accounting system with.
  2.  証憑の画像データから仕訳要素をテキストとして出力するための仕訳要素抽出AIにより、証憑の画像データから仕訳要素をテキストとして抽出する仕訳要素抽出部と、
     前記仕訳要素のテキストを用いた処理を予め登録された処理手順で自動的に実行可能な自動処理部と、
     前記仕訳要素抽出部とは異なる手段で入力された前記証憑の画像データに含まれる仕訳要素のテキストを記憶する仕訳要素データ記憶部と、
     前記仕訳要素抽出部より抽出された仕訳要素のテキストと、当該仕訳要素に対応する前記仕訳要素データ記憶部に記憶された仕訳要素のテキストとを突合し、整合した場合に、入力された情報が妥当であると判定し、前記自動処理部による処理を実行させる判定部と、
     を備える会計処理システム。
    Journal element extraction unit for extracting journal elements as text from image data of vouchers, and a journal element extraction unit that extracts journal elements as text from image data of vouchers by AI.
    An automatic processing unit that can automatically execute processing using the text of the journal element by a processing procedure registered in advance, and
    A journal element data storage unit that stores the text of the journal element included in the image data of the voucher input by a means different from the journal element extraction unit.
    When the text of the journal element extracted from the journal element extraction unit and the text of the journal element stored in the journal element data storage unit corresponding to the journal element are matched and matched, the input information is valid. A determination unit that determines that the data is true and executes processing by the automatic processing unit.
    Accounting system with.
  3.  入力された仕訳要素に対し、仕訳要素に応じた仕訳結果を出力するための仕訳AIにより、仕訳結果を出力し、且つ当該仕訳結果の信頼度を出力する仕訳部と、
     前記仕訳結果を用いた処理を予め登録された処理手順で自動的に実行可能な自動処理部と、
     前記仕訳部より出力された前記信頼度が所定の閾値以上である場合に、入力された情報が妥当であると判定し、前記自動処理部による処理を実行させる判定部と、
     を備える会計処理システム。
    For the input journal element, the journal unit that outputs the journal result and outputs the reliability of the journal result by the journal AI for outputting the journal result according to the journal element.
    An automatic processing unit that can automatically execute processing using the journal results by a processing procedure registered in advance, and
    When the reliability output from the journal entry unit is equal to or higher than a predetermined threshold value, a determination unit that determines that the input information is valid and executes processing by the automatic processing unit, and a determination unit.
    Accounting system with.
  4.  前記判定部は、入力された情報が妥当でないと判定した場合には、警告表示データを生成する請求項1から3のいずれか一項に記載の会計処理システム。 The accounting system according to any one of claims 1 to 3, which generates warning display data when the determination unit determines that the input information is not valid.
  5.  前記自動処理部は、前記仕訳要素を用いた自動仕訳を行う処理を自動的に実行可能である請求項1又は2記載の会計処理システム。 The accounting processing system according to claim 1 or 2, wherein the automatic processing unit can automatically execute a process of performing automatic journalizing using the journal element.
  6.  前記自動処理部は、前記仕訳結果を特定の宛先にメール送信する処理を自動的に実行可能である請求項3記載の会計処理システム。 The accounting processing system according to claim 3, wherein the automatic processing unit can automatically execute a process of sending the journal entry result by e-mail to a specific destination.
  7.  証憑の画像データから仕訳要素をテキストとして出力するための仕訳要素抽出AIにより、証憑の画像データから仕訳要素をテキストとして抽出し、且つ当該抽出の信頼度を出力する仕訳要素抽出工程と、
     前記仕訳要素抽出工程より出力された前記信頼度が所定の閾値以上である場合に、抽出した仕訳要素のテキストが妥当であると判定する判定工程と、
     前記判定工程にて抽出した仕訳要素が妥当であると判定された場合に、前記仕訳要素のテキストを用いた処理を予め登録された処理手順で自動的に実行する自動処理工程と、
    をコンピュータが実行する会計処理方法。
    Journal element extraction process for outputting journal elements as text from voucher image data A journal element extraction process that extracts journal elements as text from voucher image data and outputs the reliability of the extraction.
    A determination step of determining that the text of the extracted journal element is appropriate when the reliability output from the journal element extraction step is equal to or higher than a predetermined threshold value.
    An automatic processing step that automatically executes a process using the text of the journal element according to a pre-registered processing procedure when it is determined that the journal element extracted in the determination step is appropriate.
    The accounting method that the computer performs.
  8.  コンピュータに、請求項7に記載の会計処理方法を実行させるための会計処理プログラム。

     
    An accounting program for causing a computer to execute the accounting method according to claim 7.

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