Accounting data processing method and system

Abstract

The embodiment of the invention provides an accounting data processing method and system, and the method is used between at least one transaction data file and an accounting database of a corresponding user, and the transaction data file comprises a plurality of data combinations. The first data combination in the multiple data combinations at least comprises character descriptions and numerical values of non-accounting words. The method comprises the following steps of: importing the transaction data file to a data processing engine; the data processing engine automatically converts the text description of the non-accounting term in the first data combination in the transaction data file into the description of an accounting classification term so as to generate a first processed data combination; and performing content updating on the accounting database of the user by using the first processed data combination. According to the accounting data processing method and system provided by the embodiment of the invention, the billing task can be completed under the condition that the billing skills are not familiar with the billing personnel of small and medium-sized enterprises.

Description

Technical Field

[0001] The present invention relates to an accounting data processing method, in particular to an accounting data processing method with automatic text conversion. Background Art

[0002] Small and medium-sized enterprises usually do not have professional financial accounting staff. Part-time accounting staff often use inappropriate terms in their records due to their unfamiliarity with bookkeeping techniques, which leads to risks such as incorrect accounting, inaccurate financial data and overpayment of taxes when subsequent information is integrated. Summary of the invention

[0003] In order to improve the deficiencies of the above-mentioned common means and reduce the risks of mis-bookkeeping, inaccurate financial data and overpayment of taxes caused by data integration, an embodiment of the present invention discloses an accounting data processing method, which is applied between at least one transaction data file and a corresponding user's accounting database, wherein the transaction data file contains multiple data combinations, and the first data combination in the multiple data combinations at least contains text descriptions and numerical values ​​of non-accounting terms. The method includes the following steps: importing the transaction data file into a data processing engine; the data processing engine automatically converts the text description of the non-accounting terms in the first data combination in the transaction data file into a description of accounting classification terms, thereby generating a first processed data combination; and using the first processed data combination to update the content of the accounting database of the user.

[0004] In one embodiment, the accounting data processing method described in the embodiment of the present invention, wherein the transaction data file includes a text description and the numerical value of the non-accounting terms expressed in text, voice or image, the numerical value in the first data combination is one of a time value and an amount value, and the text description of the non-accounting terms is one of a cost description text and a payment form description text, and the description of the accounting classification term is an accounting code, the transaction data file is first converted into a comma separated value format and then imported into the data processing engine, and the text description of the non-accounting terms is compiled in a specific column, so that the data processing engine can automatically convert the text description of the accounting terms placed in the specific column into the description of the accounting classification term.

[0005] In one embodiment, the accounting data processing method described in the embodiment of the present invention, wherein the data processing engine is an artificial intelligence data processing engine, and the artificial intelligence data processing engine automatically converts the text description of the non-accounting terms in the first data combination into the description of the accounting classification terms based on a language model, and the first processed data combination generated by the data processing engine conforms to the comma separated value format, and the description of the accounting classification terms is placed in a specific field.

[0006] In one embodiment, the accounting data processing method described in the embodiment of the present invention further includes the following steps: performing a checking procedure on the first processed data combination, and when an error is found, the data processing engine will regenerate the first processed data combination based on the transaction data file.

[0007] In one embodiment, the accounting data processing method described in the embodiment of the present invention, wherein the step of using the first processed data combination to update the content of the accounting database of the user includes: an extraction step, extracting the data of the first processed data combination; a step of checking whether there is an error, checking the extracted data to determine whether there is an error; a conversion step, converting the extracted and correct data into a data column that conforms to the format of the accounting database; and a loading step, loading the data column into the accounting database.

[0008] In one embodiment, the accounting data processing method described in the embodiment of the present invention, wherein the step of checking whether there is an error is: using a checker program to confirm whether the output result can run normally, if there is an error, the data processing engine processes the first data combination in the transaction data file again, and then generates another processed data combination.

[0009] In one embodiment, the accounting data processing method described in the embodiment of the present invention, wherein the step details of the checker program include: checking for multiple obvious errors, wherein the multiple obvious errors include errors in the compilation of entry IDs, errors in the format of comma-separated values, and errors in the content of output data; if all these error checks pass, the checker program will return a success and proceed to the next data for processing; if one of the error checks fails, the data processing engine will generate it again until it returns a success. If this cycle runs more than a preset number of times, the data will be skipped and listed as an error, will not be included in the journal, and the user or background program administrator will be prompted to adjust the error content.

[0010] Another aspect of the present case is an accounting data processing system, which is applied between at least one transaction data file and a corresponding user's accounting database, wherein the transaction data file contains multiple data combinations, and the first data combination in the multiple data combinations at least contains text descriptions and numerical values ​​of non-accounting terms. The accounting data processing system includes: a data service server, which is signal-connected to the accounting database and the user, and is used to receive and export the transaction data file; and a data processing engine, which is signal-connected to the data service server, and is used to receive the transaction data file exported by the data service server, and automatically convert the text description of non-accounting terms in the first data combination in the transaction data file into a description of accounting classification terms, thereby generating a first processed data combination and then transmitting it back to the data service server, and the data service server is used to use the first processed data combination to update the content of the accounting database of the user.

[0011] In one embodiment, the accounting data processing system described in the embodiment of the present invention, wherein the numerical value in the first data combination is one of a time numerical value and an amount numerical value, and the textual description of the non-accounting term is one of a cost description text and a payment form description text, and the description of the accounting classification term is an accounting code, the transaction data file is first converted into a comma separated value format by the data service server and then imported into the data processing engine, and the textual description of the non-accounting term is compiled in a specific field, so that the data processing engine can automatically convert the non-accounting textual description placed in the specific field into the description of the accounting classification term.

[0012] In one embodiment, the accounting data processing system described in the embodiment of the present invention, wherein the data processing engine is an artificial intelligence data processing engine, and the artificial intelligence data processing engine is used to automatically convert the text description of the non-accounting terms in the first data combination into the description of the accounting classification terms based on a language model, and the first processed data combination generated by the data processing engine conforms to the comma separated value format, and the description of the accounting classification terms is placed in a specific field.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: the embodiment of the present invention allows part-time staff of small and medium-sized enterprises to complete accounting tasks even if they are not familiar with accounting techniques and use inappropriate terms, thereby reducing the risk of incorrect financial records and overpayment of taxes caused by data integration. In addition, the embodiment of the present invention also provides functions such as automatic error debugging, depreciation, and generation of cash flow statements.

[0014] In order to provide a clearer understanding of the above concept of the present invention, a number of embodiments are given below and described in detail with reference to the corresponding drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1A A schematic flow chart of the steps of an accounting data processing method provided by an embodiment of the present invention.

[0016] Figure 1B A block diagram of an accounting data processing system provided by an embodiment of the present invention.

[0017] Figure 2 2 is a diagram showing an example of the data format of the processed data combination in an embodiment of the present invention.

[0018] Figure 3 A schematic diagram of the extraction, conversion and loading process steps for enhancing performance is provided for an embodiment of the present invention.

[0019] Explanation of symbols

[0020] 100: transaction data file; 10: user; 13: accounting database; 14: data service server; 15: data processing engine. DETAILED DESCRIPTION

[0021] In order to solve the above problems, the embodiment of the present invention discloses Figure 1A The flowchart of the steps of an accounting data processing method shown in FIG. 1 is a flowchart of the steps of an accounting data processing method of the embodiment of the present invention. The accounting data processing method of the embodiment of the present invention can be operated on a variety of information systems, such as a remote data service server. Figure 1B The block diagram of an accounting data processing system is taken as an example for detailed description. Figure 1B The accounting data processing system shown includes at least a transaction data file 100, a user 10, an accounting database 13 corresponding to the user 10, a data service server 14, and a data processing engine 15. The transaction data file may include the text description and the numerical value of the non-accounting term expressed in text, voice or image, that is, it may be recorded in a variety of formats to form a data file containing the original transaction voucher record, such as: transaction record voice file, transaction record data file, journal, ledger, voucher image, trial balance or accounting report. Through the format conversion program, the voice or image can be converted into text for subsequent processing. Or when the data processing engine 15 is powerful enough, it can also directly interpret the voice or image. However, for the sake of simplicity in the description, the transaction data file is described by taking the journal data file formed by the journal result recorded by the user as an example.

[0022] Because for small and medium-sized enterprises, the executor of recording the journal data file is usually a part-time bookkeeper or a party requesting payment. The multiple data combinations in the journal data file may still be entered in batches by the bookkeeper or multiple parties requesting payment, so it is very likely that text descriptions using non-accounting terms will be generated. In other words, the content of any data combination in the multiple data combinations may contain at least a text description and at least a numerical value in non-accounting terms. For example, the numerical value or multiple numerical values ​​contained in the data combination may include one or any combination of a time numerical value and an amount numerical value, and the text description in non-accounting terms may be one of a cost description text and a payment form description text. For example, the cost description text is entered as colloquial text descriptions such as "taxi fare" and "high-speed rail ticket", and the payment form description text may be colloquial text descriptions such as "cash" and "transfer", and the time numerical value is 20230920 (representing September 20, 2023) and the amount numerical value is 354 (representing the amount).

[0023] After the daily journal data file (i.e., the transaction data file 100) recorded by the user is completed, there may be text descriptions of non-accounting terms mixed in it, so the accounting data processing method disclosed in the embodiment of the present invention can be used to process it. Figure 1A The accounting data processing method shown mainly includes the following steps: first, the journal data file (i.e., the transaction data file 100) recorded by the user 10 every day can be read through the data service server 14, and then the transaction data file 100 is imported into the data processing engine 15 (step 11). For example, the transaction data file 100 contains multiple data combinations, and the format of the transaction data file 100 can be first converted into a comma-separated value format (Comma-Separated Values, CSV) by the data service server 14 and then sent to the data processing engine 15, and the above-mentioned text description of non-accounting terms is compiled in a specific field.

[0024] The data processing engine 15 can be an artificial intelligence data processing engine with a large language model (such as ChatGPT on the cloud or other similar artificial intelligence engines located at the near end or the far end). Then, by inputting a command (prompt), the data processing engine 15 can automatically convert the text description of non-accounting terms placed in the specific column in the first data combination into a description of accounting classification terms, thereby generating the first processed data combination (step 12). The above-mentioned description of accounting classification terms can be an accounting code. For example, the colloquial expense description text can be automatically converted into an expense description that complies with the IFRS four-code table or complies with small and medium-sized enterprises in Taiwan, China. Then, the first processed data combination can be used to update the content of the user's accounting database 13 (step 13).

[0025] An example of automatically converting colloquial expense descriptions into expense descriptions that comply with accounting standards may be: "taxi fares" are automatically converted into "6114 travel expenses", "cash" is automatically converted into "1111 cash on hand", and "transfers" are automatically converted into "1113 bank deposits". As for the above-mentioned artificial intelligence data processing engine, it can be completed using ChatGPT or a similar large-scale language generation model, and the following prompt instructions can be input into it: [Use the IFRS four-code table or EAS to import the generation model, role-play as an accountant, and export the following fields in CSV format: "entry id, debit accounting code, debit account Chinese name, debit account amount, credit accounting code, credit account Chinese name, credit account amount"]. As a result, the artificial intelligence data processing engine will automatically generate multiple processed data combinations to form a processed journal accounting file, the content of which can be as follows: Figure 2 As shown in the data format example diagram. In this way, after all multiple data combinations have been processed, the content of a processed data combination is "entry id, debit accounting code, debit account Chinese name, debit account amount, credit accounting code, credit account Chinese name, credit account amount", forming a journal result that fully complies with accounting classification terms and the data format complies with the comma-separated values ​​format (CSV).

[0026] As for the details of using the processed data combination or multiple processed data combinations to update the content of the user's accounting database in step 13, the data service server 14 can use the extract, transform, load (ETL) program to process the journal results containing multiple processed data combinations, extract (extract), transform (transform) the processed data combination data, and finally load (load) to the destination (such as the corresponding user's cloud accounting database). However, the traditional extract, transform, load program (ETL) cannot properly handle the errors that may be generated by the artificial intelligence data processing engine.

[0027] Therefore, an extraction conversion loading program that can enhance the performance of this case is proposed and can be executed by the data service server 14. The process steps are shown in the figure below: Figure 3 As shown, it mainly includes four steps: the first is the extraction step (step 31), an example of which can be [using a search algorithm to extract only complete journal results], and its details can include the following steps: (A) first find the "entry id" column, and then find the last entry id number that should appear in this journal. (B) Find whether there is a "\n" symbol from the position of the entry id number. If there is no "\n" symbol, extract all of them. If there is, only extract the content of the index before \n.

[0028] Next is the step of checking whether there is an error (step 32): An example of checking whether there is an error can be [using a checker program (checker) to confirm that the output result is normal and can be run, and to handle common errors]. If there is an error, return to step 12 in Figure 1 and let the data processing engine regenerate the journal file for the original data. The details of the steps of the checker program may include: checking various obvious errors, such as entry ID compilation errors, comma separated value format (CSV) format errors, output data content errors, etc. If these error checks are passed, the checker program will return a success and enter the next data for processing. If one of the error checks fails, the data processing engine will be generated again until the return is successful, or if this cycle runs more than 3 times, the data will be skipped and listed as an error, and will not be included in the journal, and the user or backend program administrator will be prompted to adjust the error content.

[0029] As for the transformation step (step 33), an example may be [using an algorithm to transform the journal results into a data column in a database format], which may include the following steps: (A) transforming each journal data generated by the generative AI into an accounting subject, wherein each journal entry is a data column to match the database column. (B) obtaining basic information (transaction time, company ID, original transaction data ID, transaction data remarks).

[0030] The example of the loading step (step 34) can be [fill in each journal ID, entry ID, and account ID in the entry]. After loading, the following steps can be used to handle three situations: (A) normal situation: the number of debit accounts is equal to the number of credit accounts, (B) asymmetric account number situation: the number of accounts on both sides is not equal, (C) error situation: the amount and number of accounts on one or both sides of the debit or credit side are not symmetrical, so regenerate. When (B) the asymmetric account number situation occurs, it means that the generated account number is asymmetric, such as the following three situations: (1) the "name" and "amount" of the credit or debit account are inconsistent, (2) the "name" of the credit or debit account is inconsistent with the number of "four-level accounting account code" and (3) the "amount" of the credit or debit account is inconsistent with the number of "four-level accounting account code". When the result generated by step 12 appears in the three situations of the above (B) asymmetric account number situation, special processing will be performed. Special processing can be to fill in "0000" for the item content that should appear but does not appear, so that the back-end engineer knows that the content is wrong and displays it to the front-end for manual processing.

[0031] Let's take another example to explain the above steps in detail: Under normal circumstances, step 12 automatically generates: Debit account name: social expenses, transportation expenses, debit account level 4 accounting code: 5012, 5013, and debit account amount: 2000, 500. However, if the content automatically generated by step 12 is: Debit account name: social expenses, transportation expenses, debit account level 4 accounting code: 5012, and debit account amount: 2000, 500. It can be seen from the above that the automatically generated accounting code is one less, which is an error, so we will fill in the item content that should appear but does not appear with "0000" to let the back-end engineer know that this content is wrong, and display it to the front-end engineer so that he knows and can handle it manually.

[0032] In addition, the embodiment of the present invention can also add a "depreciation processing" step, the details of which can be: when obtaining the transaction data of the fixed asset sales record table regarding the sale and purchase this month, and the transaction data of the status of holding last month. The user can enter the fixed asset recommendation table of the item according to the fixed asset number recommendation table of the administrative management agency in Taiwan. The accounting data processing system disclosed in the embodiment of the present invention can use the prepared comparison table to map to the corresponding IFRS accounting level 4 account or EAS account, and automatically fill in the accounting account name and accounting code. The example can have the following steps:

[0033] Step 1, process the data column of the purchase status: store the original value, residual value, depreciation period, and depreciation method entered by the user into the database. The status of the item is changed to holding, the accumulated depreciation is 0, and the net value is equal to the original value. Determine the purchase time: if it is purchased before the 15th of this month, a depreciation process is required; if it is purchased after the 15th, no depreciation process is required. Depreciation process required for purchase: confirm that the depreciation period has not expired; use the user's depreciation method for depreciation Determine the selling time: if it is sold after the 15th of this month, a depreciation process is required; if it is sold before the 15th, no depreciation process is required for this month. Depreciation process required for sale: confirm that the depreciation period has not expired; use the user's depreciation method to calculate depreciation and update the accumulated depreciation and net value of the data this month. Enter the accumulated depreciation corresponding to the depreciation expense generated in this month into the journal. Take out the latest data column of the item, take out the accumulated depreciation, residual value, net value, etc., sell it, and include it in the journal. Exclude the holding data column and do not retain it in the holding status column of the next month.

[0034] Step 3, perform depreciation processing for the data in the holding status: check whether the depreciation period has expired, if not, perform depreciation processing; inherit to the fixed asset record table of the next month, and recognize the depreciation result in the journal. After completing the above three steps, the depreciation calculation and data update can be completed accurately and automatically.

[0035] In addition, in order to automatically convert the journal into the profit and loss statement, the embodiment of the present invention also provides the following method steps: using the IFRS coding rules or the EAS coding rules, the first code of the accounting code is 5 to 8 from the journal to recognize the profit and loss account. In order to automatically convert the journal into the balance sheet, the embodiment of the present invention also provides the following method steps: taking the balance sheet of the previous month as the base for modification; using the IFRS coding rules or the EAS coding rules, taking the first code of the accounting code is 1 to 3 from the journal to recognize the balance sheet account; taking out the depreciation result of the current period; and recognizing.

[0036] Furthermore, the embodiment of the present invention can also generate a cash flow statement from an income statement and a balance sheet using an indirect method, and the steps include: preparing a subject conversion table for the cash flow statement, the income statement, and the balance sheet; self-numbering the accounting subjects of the cash flow statement, starting with 9; listing the IFRS level 4 accounting subjects required for the cash flow statement starting with 1 to 8 and the required accounting subject codes and names and their calculation methods in the cash flow statement (preset as assets are subtracted, liabilities and equity are added); capturing the required subject amounts in the income statement and the balance sheet; and aggregating the subjects according to the cash flow statement number and the preset calculation method.

[0037] As for the details of "pre-processing", you can: convert to database format or convert to output PDF format. The following steps: Convert to database format: 1. Fill in the basic information of the cash flow statement (company ID, start date of this statement, end date of this statement); 2. Fill in the cash flow statement code, account name, amount. Convert to output PDF format: Indent specific accounts according to the formal cash flow style.

[0038] As mentioned above, the technical means provided by the embodiments of the present invention can allow part-time staff of small and medium-sized enterprises to complete accounting tasks without being particularly familiar with formal terms, and avoid the problem of incorrect financial data through the technical means developed in this case. In addition, this case also provides functions such as automatic debugging, depreciation, and generation of cash flow statements. Although the present invention is disclosed as above by implementation cases, it is not intended to limit the present invention. Those with ordinary knowledge in the technical field to which the present invention belongs can make various changes and modifications without departing from the technical spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be defined by the scope of the attached patent application claims.

Claims

1. A method for processing accounting data, characterized in that: The method is applied between at least one transaction data file and an accounting database of a corresponding user, wherein the transaction data file includes multiple data combinations, wherein a first data combination of the multiple data combinations includes at least a colloquial text description of non-accounting terms and a numerical value, wherein the colloquial text description of non-accounting terms and the numerical value are recorded by the user, and comprises the following steps: Importing the transaction data file into the artificial intelligence data processing engine; The artificial intelligence data processing engine automatically converts the colloquial text description of the non-accounting terms in the specific column of the first data combination in the transaction data file into a description of accounting classification terms, thereby generating a first processed data combination; as well as The first processed data combination is used to update the content of the accounting database of the user.

2. The accounting data processing method according to claim 1, characterized in that: The transaction data file includes the colloquial text description of the non-accounting terms and the numerical values ​​expressed in text, voice or image, the numerical value in the first data combination is one of a time value and an amount value, and the colloquial text description of the non-accounting terms is one of a cost description text and a payment form description text, and the description of the accounting classification term is an accounting code. The transaction data file is first converted into a comma separated value format and then imported into the artificial intelligence data processing engine.

3. The accounting data processing method according to claim 1, characterized in that: The artificial intelligence data processing engine automatically converts the colloquial text description of the non-accounting terms in the first data combination into the description of the accounting classification terms based on a language model. The first processed data combination generated by the artificial intelligence data processing engine conforms to the comma separated value format, and the description of the accounting classification terms is placed in a specific field.

4. The accounting data processing method according to claim 1, characterized in that: The method further comprises the following steps: performing a check procedure on the first processed data combination, and when an error is found, causing the data processing engine to regenerate the first processed data combination according to the transaction data file.

5. The accounting data processing method according to claim 1, characterized in that The step of updating the content of the accounting database of the user by using the first processed data combination comprises: An extraction step, extracting the first processed data combination data; The step of checking whether there is an error is to check the extracted data to determine whether there is an error; A conversion step, converting the extracted and correct data into a data column that conforms to the accounting database format; as well as The loading step is to load the data row into the accounting database.

6. The accounting data processing method according to claim 5, characterized in that: The step of checking whether there is an error is: using a checker program to confirm whether the output result can run normally. If there is an error, the data processing engine will process the first data combination in the transaction data file again, and then generate another processed data combination.

7. The accounting data processing method according to claim 6, characterized in that: The details of the steps of the checker program include: checking for multiple obvious errors, including errors in the compilation of entry IDs, errors in the format of comma-separated values, and errors in the content of output data; if all these error checks pass, the checker program will return a success and proceed to the next data for processing; if one of the error checks fails, the data processing engine will generate it again until it returns a success. If this cycle runs more than a preset number of times, the data will be skipped and listed as an error, and will not be included in the journal, and the user or back-end program administrator will be prompted to adjust the error content.

8. An accounting data processing system, characterized in that: Applied between at least one transaction data file and an accounting database of a corresponding user, the transaction data file includes a plurality of data combinations, a first data combination of the plurality of data combinations includes at least a colloquial text description and a numerical value of non-accounting terms, the colloquial text description of accounting terms is recorded by the user, and the accounting data processing system includes: a data service server, signal-connected to the accounting database and the user, for receiving and exporting the transaction data file, wherein the colloquial text description of the non-accounting term is compiled in a specific column; as well as An artificial intelligence data processing engine, signal-connected to the data service server, is used to receive the transaction data file exported by the data service server, and automatically convert the colloquial text description of the non-accounting terms compiled in the specific column in the first data combination in the transaction data file into a description of accounting classification terms, thereby generating a first processed data combination and then transmitting it back to the data service server. The data service server is used to use the first processed data combination to update the content of the user's accounting database.

9. The accounting data processing system according to claim 8, characterized in that: The transaction data file includes the colloquial text description of the non-accounting terms and the numerical values ​​expressed in text, voice or image, the numerical value in the first data combination is one of a time value and an amount value, and the colloquial text description of the non-accounting terms is one of a cost description text and a payment form description text, and the description of the accounting classification term is an accounting code. The transaction data file is first converted into a comma separated value format by the data service server and then imported into the data processing engine.

10. The accounting data processing system according to claim 8, characterized in that: The artificial intelligence data processing engine is used to automatically convert the colloquial text description of the non-accounting terms in the first data combination into the description of the accounting classification terms based on a language model. The first processed data combination generated by the data processing engine conforms to the comma separated value format, and the description of the accounting classification terms is placed in the specific field.

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