Business and financial integrated application system and application method based on business and financial preprocessing

Abstract

The invention provides a business and financial integrated application system and method based on business and financial preprocessing, which can subsequently activate a corresponding settlement module or delivery module according to business attributes, execute corresponding settlement or delivery processing on order business data, and generate and output a corresponding settlement or delivery processing result. And the financial system carries out accounting document and entry processing on the settlement or delivery processing result to generate corresponding financial data and stores the financial data. The method can be used by common business personnel who do not need to understand accounting knowledge, thereby reducing operation difficulty, getting rid of dependence on accountants, and realizing business and financial integration. According to the invention, the settlement or delivery function can be correspondingly activated according to the business attributes, the integrated processing and operation of the business finance and tax places are automatically carried out, the intelligent management and operation of the business finance and tax places are realized, the efficiency is greatly improved, and the cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of business financial management technology, and in particular to a business-finance integrated application method based on business-finance pre-processing, a business-finance integrated application system based on business-finance pre-processing, an electronic device and a computer-readable storage medium. Background Art

[0002] As attached Figure 1 The data processed in the existing "business and finance integration" software on the market mainly includes two core data: one is "business data", such as orders, receipts / delivery orders, etc., which are generally entered according to the company's own management needs; the other is "financial data", mainly accounting vouchers / entries, which need to comply with relevant national financial and tax regulations. Certain rules can be set in the "business and finance integration" software to realize the automatic conversion of "business data" into "financial data", thereby achieving the so-called "business and finance integration".

[0003] The technical principle of achieving "business-finance integration" in the existing "business-finance integration" software on the market is generally to configure different accounting vouchers and entry templates (and accounting reports) according to different business types. In this way, when business personnel enter business data such as "orders" and "payments", the system will regenerate "financial data" based on the template.

[0004] However, the main disadvantage of the application of the above technology is poor flexibility and accuracy. Because the national financial and tax regulations are relatively complex, it is difficult to ensure that the same "business data" generates accurate "financial data" in various business scenarios, so accountants are often required to intervene and modify the "financial data" automatically generated by the system to ensure accuracy, which leads to no real "business and financial integration" and thus flexibility. Manual intervention not only requires the intervention personnel to have professional accounting knowledge, but also takes a long time to intervene, so the application is not intelligent enough, prone to operational errors, and not accurate enough. Summary of the invention

[0005] In order to solve the technical problems existing in the prior art, the present invention provides the following technical solutions: On the one hand, a business-finance integrated application method based on business-finance pre-processing is provided, the method is implemented by an electronic device, and the method includes: S1. Preliminarily construct and deploy a settlement module and a delivery module in a common business operating system, wherein the settlement module is used to confirm the receivables / payables and taxes payable of the order business data, and the delivery module is used to confirm the income / expenditure of the order business data; S2. Obtain order business data from the order system and send it to the common business operating system; S3, the common business operating system identifies the business attributes of the order business data, activates the corresponding settlement module or the delivery module according to the business attributes, performs corresponding settlement or delivery processing on the order business data, and generates and outputs corresponding settlement or delivery processing results; S4. The financial system processes the settlement or delivery results into accounting documents and journal entries, generates corresponding financial data and saves them.

[0006] Preferably, in step S3, if the corresponding settlement module is activated, after performing corresponding settlement processing on the order business data, the method further includes: Sending the settlement processing result to the payment / goods business system; The payment / goods business system performs payment / goods confirmation operations on the settlement processing results to confirm receivable cash flows or confirm inventory; After confirmation, proceed to step S4.

[0007] Preferably, S3, the common business operating system identifies the business attributes of the order business data, and activates the corresponding settlement module or the delivery module according to the business attributes, including: Receiving the order business data and importing the business driver identification model pre-deployed in the common business operating system; The business driver identification model identifies the business attributes of the order business data and outputs a corresponding system activation instruction; The common business operating system responds to the system activation instruction to activate the corresponding settlement module or the delivery module.

[0008] Preferably, the method for constructing the business driver identification model includes: Based on the LLM large language model, the business attribute recognition results of the common business operating system on the order business data and the settlement / delivery activation records generated according to the business attributes are collected in batches. The records contain corresponding system activation instructions to construct the corresponding order business driver data set M: M={m1,m2......mn}, m={order business data, business attributes, settlement / delivery activation records}; Perform feature engineering on the order business driven data set M, extract the business attribute values ​​of the corresponding order business data and the corresponding settlement / delivery activation type, and construct the corresponding feature set based on the extracted data: Divide the feature set into training set and validation set according to the preset ratio; Input the training set into a preset RF random forest model to perform business-driven training and learning, and construct the business-driven identification model; The business driver performance of the business driver identification model is verified using the validation set: If the verification is successful, deploying and applying the business driver identification model in the common business operating system; If the verification fails, the above steps are repeated to rebuild the business driver identification model.

[0009] Preferably, the batch collection of the business attribute recognition results of the order business data by the common business operating system and the settlement / delivery activation records generated according to the business attributes based on the LLM large language model includes: Deploy an LLMAPI port on the common business operating system to call the LLM large language model; Constructing extraction keywords and batch extraction logic for settlement order business data and delivery order business data, and constructing LLM prompt words in combination with the keywords and logic, and inputting the LLM prompt words into the LLM large language model; The LLM large language model is used to monitor the common business operating system, and the business conversion processing logs of the order business data are collected in batches, including the business attribute recognition results of the order business data and the settlement / delivery activation records generated according to the business attributes.

[0010] On the other hand, a business-finance integrated application system based on business-finance pre-processing is provided, which is used to implement the business-finance integrated application method based on business-finance pre-processing, and the system includes: Order system, used to receive order business data; A common business operating system, used to obtain order business data from the order system, identify the business attributes of the order business data, activate the corresponding settlement module or the delivery module according to the business attributes, perform corresponding settlement or delivery processing on the order business data, and generate and output corresponding settlement or delivery processing results; The payment / goods business system is used to confirm the payment / goods of the settlement processing results, confirm the cash flow receivable or confirm the inventory; The financial system is used to process accounting documents and entries for the settlement or delivery processing results, generate corresponding financial data and save them.

[0011] On the other hand, an electronic device is provided, comprising: a processor; a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, any one of the above-mentioned business-finance integration application methods based on business-finance pre-processing is implemented.

[0012] On the other hand, a computer-readable storage medium is provided, in which at least one instruction is stored. The at least one instruction is loaded and executed by a processor to implement any one of the above-mentioned business-finance integration application methods based on business-finance pre-processing.

[0013] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least: The present invention pre-builds and deploys a settlement module and a delivery module in a common business operating system, wherein the settlement module is used to confirm the receivables / payables and taxes payable of order business data, and the delivery module is used to confirm the income / expenditure of order business data. Subsequently, the corresponding settlement module or the delivery module can be activated according to the business attributes, and the corresponding settlement or delivery processing is performed on the order business data, and the corresponding settlement or delivery processing results are generated and output. The financial system performs accounting voucher and entry processing on the settlement or delivery processing results, generates corresponding financial data and saves them. It is possible to realize the automatic generation of "financial data" from "business data". Since these two modules do not require ordinary business personnel with accounting knowledge to use, the difficulty of operation is reduced, the dependence on accounting is eliminated, and "business and finance integration" is achieved.

[0014] The present invention can activate the settlement or delivery function according to the business attributes, automatically carry out the integrated processing and operation of business, finance, taxation and location, realize the intelligent management and operation of business, finance, taxation and location, greatly improve the efficiency and reduce the cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 It is a schematic diagram of the system architecture structure of business and financial integrated processing in the prior art; Figure 2 This is a flow chart of a business-finance integration application method based on business-finance pre-processing provided by an embodiment of the present invention; Figure 3 It is a block diagram of a business-finance integrated application system based on business-finance pre-processing provided by an embodiment of the present invention; Figure 4 It is a business process diagram of a business-finance integrated application system based on business-finance pre-processing provided by an embodiment of the present invention; Figure 5 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0018] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0019] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0020] In the embodiments of the present invention, sometimes a subscript such as W1 may be mistakenly written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are consistent.

[0021] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0022] The embodiment of the present invention provides a business-finance integrated application method based on business-finance pre-processing, which can be implemented by an electronic device, which can be a terminal or a server. Figure 2 The flowchart of the business-finance integration application method based on business-finance pre-processing is shown, and the processing flow of the method may include the following steps: S1. Preliminarily construct and deploy a settlement module and a delivery module in a common business operating system, wherein the settlement module is used to confirm the receivables / payables and taxes payable of the order business data, and the delivery module is used to confirm the income / expenditure of the order business data; S2. Obtain order business data from the order system and send it to the common business operating system; S3, the common business operating system identifies the business attributes of the order business data, activates the corresponding settlement module or the delivery module according to the business attributes, performs corresponding settlement or delivery processing on the order business data, and generates and outputs corresponding settlement or delivery processing results; S4. The financial system processes the settlement or delivery results into accounting documents and journal entries, generates corresponding financial data and saves them.

[0023] Combination Figure 3 As shown in the figure, this system is mainly composed of order system, general business operation system, payment / goods business system and financial system (accounting vouchers, entries). The corresponding business, finance and taxation processing flow is shown in the attached Figure 4 shown.

[0024] This technical solution mainly involves two functional point operations: "settlement" and "delivery". "Settlement" and "delivery" are innovative functional designs of the present invention. In normal business operations, these two actions do not exist. The present invention realizes the conversion of "business data" to "financial data" by setting up these two functional points as the connection between "business data" and "financial data".

[0025] Combined with Figure 1 As shown, the business management process of existing financial software is generally as follows: first enter the order, then collect and pay the order, and enter and exit the warehouse (or provide services).

[0026] In this system, two special functions, "settlement module" and "delivery module", are designed in the general business operating system. In this invention, after the user enters the order, if he needs to receive or pay, he needs to click "settlement" first to generate a "settlement form" (here the manual mode can be used, that is, the user identifies the corresponding business attributes, manually inputs the business attributes into the general business operating system and activates the corresponding module). After the "settlement form" is generated (or approved), the corresponding "financial data" is generated: Debit: "Accounts Receivable" category, Credit: "Deferred income from advance payments" category, Credit: "Taxes payable" category; If the user sends or receives goods (or provides / receives services), he / she needs to click "Delivery" to generate a "Delivery Order". After the delivery order is generated (or approved), the corresponding "Financial Data" is generated: Debit: "Deferred income from advance payments" category account; Credit: "Income from Profit and Loss Account" type accounts.

[0027] To generate accurate "financial data" from "business data", the key point is mainly to confirm the three core financial data (which must comply with national fiscal and tax regulations): Confirm “A / R”.

[0028] Confirm "income".

[0029] Confirm the “Taxes Payable”.

[0030] In the present invention, settlement means confirming "receivables" and "taxes payable", and delivery means confirming "income". "Confirming income" is completed in the "delivery" function. However, some companies' businesses only have the "settlement" step, and at the same time "confirm receivables", "confirm income" and "confirm taxes payable" in "settlement". The financial data generated at this time is as follows: Debit: "Accounts receivable" category, Credit: "Income in Profit and Loss Account" type account, Credit: “Taxes payable” accounts.

[0031] In addition, when the settlement form is generated, the "financial data" may not be automatically generated immediately, but the user may manually perform a related action, such as "hanging an account" (any name), to trigger the generation of financial data. Whether the "financial data" is automatically generated immediately or triggered by a related action, both fall within the protection scope of the core principle of the present invention.

[0032] These two functional modules realize the connection between business data and financial data, which can convert business data into financial data and comply with national fiscal and taxation regulations. Because the above three types of data cannot be generated by pre-setting templates in advance, accountants are traditionally required to intervene and use their professional knowledge to compile "financial data" based on actual business situations. With these two functional points, for business personnel, he is just doing a normal business operation and does not need professional accounting knowledge. He only needs to trigger these two functions according to the actual situation, and the software will automatically convert it into "financial data" according to his operation.

[0033] In this embodiment, there is no sequential dependency between these two functional modules. Different companies may have different business scenarios. Some may be "delivered" first and then "settled", while others may be "settled" first and then "delivered". This does not affect the correct generation of "financial data". You can choose to use it according to your needs.

[0034] Take the engineering industry as an example: If a renovation engineering company receives a 1 million project (with a 9% special invoice), it needs to enter an "income order (or contract)" into the system. The contract stipulates that the payment will be made in two installments: 30% upon completion of the demolition and the remaining 70% upon completion of the entire project.

[0035] 10 days after the project started, the demolition was completed. At this time, the project manager of the decoration company needs to click "Settlement" in the system, and the settlement amount is "0.3". At this time, the "Financial Data" is generated: Debit: Accounts receivable 300,000, Credit: Deferred income from advance payments of RMB 273,000, Credit: Taxes payable: VAT payable is RMB 27,000. At this time, a "receivable" of 300,000 is generated in the system. Then, you can issue an invoice to the customer and collect the payment at the agreed time.

[0036] Because the project has been completed 30%, 30% of the revenue can be confirmed financially, so the project manager only needs to click "Delivery" and enter a delivery order to confirm 30% of the revenue.

[0037] Debit: Deferred income from advance payments of RMB 273,000, Loan: Main business income: RMB 273,000.

[0038] Therefore, the present invention realizes the automatic generation of "financial data" from "business data" by using "settlement" and "delivery" as bridges between "business data" and "financial data". Since these two functions do not require accounting knowledge, ordinary business personnel can use them. As long as these two functions can be used correctly, the generated "financial data" can be guaranteed to be correct, getting rid of the dependence on accounting, and truly realizing "business and financial integration".

[0039] The present invention solves the problem of the accuracy of automatically generating "financial data" from "business data" in business-finance integration software without relying on manual intervention by accountants, and can ensure that the "financial data" generated in different industries and business scenarios complies with national financial and tax regulations.

[0040] Preferably, in step S3, if the corresponding settlement module is activated, after performing corresponding settlement processing on the order business data, the method further includes: Sending the settlement processing result to the payment / goods business system; The payment / goods business system performs payment / goods confirmation operations on the settlement processing results to confirm receivable cash flows or confirm inventory; After confirmation, proceed to step S4.

[0041] For payment / goods confirmation operations, please refer to the payment / goods confirmation operations in existing business financial operations.

[0042] The above-mentioned specific settlement, tax payment and other rules can be combined with the existing national financial and taxation rules.

[0043] The present invention also adopts a method for automatically driving and activating the settlement module or the delivery module. At the same time, the system identifies the business attributes of the current order business data, automatically activates the corresponding settlement module or the delivery module, and drives the execution of the order business data, thereby improving the system's automated operation level, replacing manual intervention operations, and realizing intelligent integrated management and application of business, finance and taxation, greatly improving the operational processing efficiency of business, finance and taxation.

[0044] Preferably, S3, the common business operating system identifies the business attributes of the order business data, and activates the corresponding settlement module or the delivery module according to the business attributes, including: Receiving the order business data and importing the business driver identification model pre-deployed in the common business operating system; The business driver identification model identifies the business attributes of the order business data and outputs a corresponding system activation instruction; The common business operating system responds to the system activation instruction to activate the corresponding settlement module or the delivery module.

[0045] This solution deploys a business driver identification model in a common business operating system. The business driver identification model can identify the business attributes of the order business data entering the business driver identification model, and automatically match and output the corresponding business driver strategy based on the business attributes of the order business data. The strategy includes a system activation instruction (or control parameter) for activating the corresponding settlement module or the delivery module, thereby automatically realizing the business driver execution of the order business data and avoiding manual intervention.

[0046] In the above application process, the general business operating system will generate a large number of settlement / delivery activation execution logs (activation operation records) of order business data, so the corresponding order business driver big data can be saved in batches, which includes the driver execution behavior data of order business data with different attributes, so it can be used to build a training data set for training the business driver identification model. The following describes how to build the business driver identification model.

[0047] Preferably, the method for constructing the business driver identification model includes: Based on the LLM large language model, the business attribute recognition results of the common business operating system on the order business data and the settlement / delivery activation records generated according to the business attributes are collected in batches. The records contain corresponding system activation instructions to construct the corresponding order business driver data set M: M={m1, m2...mn}, where m1, m2...mn represent the activation execution data groups of each group of order business data, and m={order business data, business attributes, settlement / delivery activation record}; Perform feature engineering on the order business driven data set M, extract the business attribute values ​​of the corresponding order business data and the corresponding settlement / delivery activation type, and construct the corresponding feature set based on the extracted data: Divide the feature set into training set and validation set according to the preset ratio; Input the training set into a preset RF random forest model to perform business-driven training and learning, and construct the business-driven identification model; The business driver performance of the business driver identification model is verified using the validation set: If the verification is successful, deploying and applying the business driver identification model in the common business operating system; If the verification fails, the above steps are repeated to rebuild the business driver identification model.

[0048] In order to collect the training data set, based on the LLM large language model, the business attribute recognition results of the common business operating system on the order business data and the settlement / delivery activation records generated according to the business attributes are collected in batches, including: Deploy an LLMAPI port on the common business operating system to call the LLM large language model; Constructing extraction keywords and batch extraction logic for settlement order business data and delivery order business data, and constructing LLM prompt words in combination with the keywords and logic, and inputting the LLM prompt words into the LLM large language model; The LLM large language model is used to monitor the common business operating system, and the business conversion processing logs of the order business data are collected in batches, including the business attribute recognition results of the order business data and the settlement / delivery activation records generated according to the business attributes.

[0049] The LLM large language model can be deployed by users themselves or called through the API to call a third-party large language model (such as Baidu's Wenxin Yiyan).

[0050] The following steps can be used to collect batches of business-driven data sets based on LLM: 1. Deploy LLMAPI port Objective: Connect the LLM large language model to the business operating system to support real-time / batch calls.

[0051] Technical implementation: Use the RESTful API or gRPC protocol to open API endpoints (such as ` / llm / datacollect`) in the business operating system.

[0052] Integrated authentication mechanisms (such as APIKey+OAuth2) ensure data security. Example API request: Call LLM to process order log importrequests response = requests.post( url="https: / / api.yoursystem.com / llm / datacollect", headers={"Authorization":"Bearer<API_KEY> "}, json={ "log_data":"Order ID:1001,Customer ID:C789,Amount:2000,Tax rate:0.13", "task_type":"attribute identification" } ).

[0053] 2. Build keywords and batch extraction logic Keyword definitions: Settlement orders: `Customer ID`, `Order amount`, `Tax rate`, `Discount`, `A / R`.

[0054] Delivery orders: `Logistics order number`, `Service agreement ID`, `Logistics fee`, `Service fee`, `Income / Expenditure`.

[0055] Extraction logic: defextract_keywords(log_text:str)>dict: Settlement keyword matching if "Customer ID" inlog_textand "Tax Rate" inlog_text: return{"type":"Settlement","keywords":["Customer ID","Amount","Tax Rate"]} Delivery keyword matching elif "Logistics Order Number" inlog_textor "Service Agreement ID" inlog_text: return{"type":"delivery","keywords":["logistics order number","service fee"]} else: return {"type":"unknown"}.

[0056] 3. Design LLM prompt words Prompt word objective: Guide LLM to identify business attributes and generate structured records.

[0057] Template example: 1). Identify business attributes (sales / purchase).

[0058] 2). Extract key fields: customer ID / supplier ID, order amount, tax rate, discount.

[0059] 3). Generate a settlement activation record in JSON format: { "Business Attribute":"Sales", "Amount receivable": (amount (1 + tax rate) discount), "Tax": amount tax rate, "Activation module": "Settlement" } Log content: {log_text} """ Delivery order prompt words (omitted, similar structure) ```.

[0060] 4.LLM monitoring and log collection Real-time monitoring: Capture the processing logs of the business operating system through log aggregation tools (such as ELK, Fluentd). During the historical operation of the business system, the system will automatically generate the corresponding delivery or settlement drive operation logs and save them in the corresponding log database.

[0061] When monitoring and collecting data, you can also filter log entries containing keywords according to preset filtering and cleaning rules to trigger the LLM processing flow.

[0062] The following is an example of calling LLMAPI to process logs: defcall_llm_api(log): Generate dynamic prompt words prompt=generate_prompt(log) Calling the LLM interface response=llm_client.generate(prompt) returnparse_response(response).

[0063] 5. Data storage and output storage design: Structured storage in a database (such as MySQL, MongoDB), the table structure includes: ```sql CREATE TABLE order_records( idINTPRIMARYKEY, order_id VARCHAR(50), attributeVARCHAR(20), business attribute (sales / purchase / logistics / service) amountDECIMAL(10,2), amount taxDECIMAL(10,2), tax activated_moduleVARCHAR(20)Activated module (settlement / delivery) ); Query by time range, business attributes, amount range, etc.

[0064] 6. Unit Testing Test case: Test settlement order processing log="Order ID:1002, Customer ID:C888, Amount:3000, Tax rate:0.13, Discount:300" expected_output={ "Business Attribute":"Sales", "Amount Receivable":30001.13300, "Tax":30000.13, "Activation module": "Settlement" } assertprocess_log(log)==expected_output.

[0065] 7. Stress Testing Scenario: Simulate the concurrent processing of 100,000 logs to evaluate LLMAPI throughput and system stability.

[0066] index: Average response time ≤ 500ms Error rate ≤ 0.1% 8. Data consistency check Methods: Random sampling was performed from the original logs, and the LLM output results were manually checked.

[0067] tool: Comparison of LLM processing results and manual annotation results SELECT llm_output,human_label FROMvalidation_samples WHEREllm_output!=human_label.

[0068] This solution can efficiently realize the automated collection and structured storage of business-driven data sets, providing a high-quality data foundation for subsequent data analysis, model training, and system optimization.

[0069] After the corresponding order business data-driven training samples are collected, model training can be performed. The present invention preferably uses the RF model for model training, and its model architecture and training process can be understood in combination with the existing RF application principles.

[0070] The training and deployment steps for building a business driver identification model based on the RF random forest model are as follows: 1. Definition of goals and input and output Objective: Based on the order business driving dataset M, train an RF random forest model to identify business attributes and predict settlement / delivery activation instructions.

[0071] enter: Order business driven data set , where each set of data Include: Order business data (such as amount, cost, tax rate, etc.); Business attributes (such as sales, procurement, logistics, services); Settlement / delivery activation records (such as settlement module, delivery module).

[0072] Output: The trained RF model supports outputting business attributes and activation instructions after inputting order data.

[0073] 2. Implementation steps 1. Dataset Construction Data format: Each set of data The structure is as follows (taking the settlement module as an example): { "Order business data":{ "Order ID":"1001", "Amount":2000, "Cost":1500, "Tax rate":0.13, "discount":100, "Logistics cost":0, "Service Fee":0 }, "Business Attribute":"Sales", "Activation Record":"Settlement Module" }.

[0074] 2. Feature Engineering Feature extraction: The following features are extracted from the order business data: Numerical features: amount, cost, tax rate, discount, logistics cost, service fee.

[0075] Category characteristics: business attributes (encoded as numerical values, such as sales = 1, procurement = 2, logistics = 3, service = 4).

[0076] Target variable: Activation record (coded as a numeric value, such as settlement module = 1, delivery module = 2).

[0077] Since most order data is numerical data, the feature processing method of numerical feature standardization can be used: Use `LabelEncoder` or `OneHotEncoder` to process categorical features (categorical feature encoding).

[0078] Example: Loading the dataset data=pd.read_json("order_data.json") Feature extraction features=data["Order business data"].apply(pd.Series) features["Business attributes"]=LabelEncoder().fit_transform(data["Business attributes"]) features["activation record"]=LabelEncoder().fit_transform(data["activation record"]) Feature set and target variable X=features.drop("activation record",axis=1) y=features["Activation Record"].

[0079] 3. Dataset Division Division ratio: training set: 70%, validation set: 30% 4.RF model training Model parameters: Number of trees (`n_estimators`): 100, Maximum depth (`max_depth`): 10, Random seed (`random_state`): 42.

[0080] After multiple iterations of training, the business driver identification model is obtained. Next, verification is performed.

[0081] 5. Model Validation Verification indicators: Accuracy Confusion Matrix, F1 score (F1Score).

[0082] In this process, the user uses the validation set to input the business-driven identification model and verifies it based on indicators such as accuracy. If the performance verification is qualified, the model is deployed. Deployment conditions: The validation set accuracy is ≥ 95%, or F1 score ≥ 0.95.

[0083] Deployment method: Save the trained RF model as a file (such as `rf_model.pkl`). Integrate the model inference API in the business operating system.

[0084] 7. Model optimization and iteration Optimization strategy: Adjust RF model parameters (e.g. increase the number of trees, adjust the maximum depth).

[0085] Introduce more features (such as timestamp, customer category).

[0086] Use GridSearch for hyperparameter tuning.

[0087] Iteration process: If the verification fails, return to step 4 to retrain the model.

[0088] Through this solution, an efficient and accurate business-driven identification model can be built and successfully deployed to the business operating system to achieve automated processing and decision-making of order data.

[0089] Please understand the above model deployment and application in conjunction with the previous description.

[0090] Figure 3 is a block diagram of a business-finance integrated application system based on business-finance pre-processing according to an exemplary embodiment, and the system is used to implement the business-finance integrated application method based on business-finance pre-processing. Figure 3 , the system comprising: Order system, used to receive order business data; A common business operating system, used to obtain order business data from the order system, identify the business attributes of the order business data, activate the corresponding settlement module or the delivery module according to the business attributes, perform corresponding settlement or delivery processing on the order business data, and generate and output corresponding settlement or delivery processing results; The payment / goods business system is used to confirm the payment / goods of the settlement processing results, confirm the cash flow receivable or confirm the inventory; The financial system is used to process accounting documents and entries for the settlement or delivery processing results, generate corresponding financial data and save them.

[0091] Please understand the functions and interactions of each system in conjunction with the corresponding method steps above, and will not be repeated here.

[0092] Figure 5 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, such as Figure 5 As shown, the electronic device 410 may include a first processor 2001 .

[0093] Optionally, the electronic device 410 may further include a memory 2002 and a transceiver 2003 .

[0094] The first processor 2001, the memory 2002 and the transceiver 2003 may be connected via a communication bus.

[0095] Combine the following Figure 5 The components of the electronic device 410 are described in detail: The first processor 2001 is the control center of the electronic device 410, and may be a processor or a general term for multiple processing elements. For example, the first processor 2001 is one or more central processing units (CPUs), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention, such as one or more microprocessors (digital signal processors, DSPs), or one or more field programmable gate arrays (field programmable gate arrays, FPGAs).

[0096] Optionally, the first processor 2001 can perform various functions of the electronic device 410 by running or executing a software program stored in the memory 2002 and calling data stored in the memory 2002 .

[0097] In a specific implementation, as an embodiment, the first processor 2001 may include one or more CPUs, such as Figure 5 CPU0 and CPU1 are shown in FIG.

[0098] In a specific implementation, as an embodiment, the electronic device 410 may also include multiple processors, such as Figure 5The first processor 2001 and the second processor 2004 are shown in FIG. Each of these processors may be a single-core processor (singleCPU) or a multi-core processor (multiCPU). The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0099] The memory 2002 is used to store the software program for executing the solution of the present invention, and is controlled to be executed by the first processor 2001. The specific implementation method can refer to the above method embodiment, which will not be repeated here.

[0100] Optionally, the memory 2002 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CDROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 2002 may be integrated with the first processor 2001, or may exist independently and access the first processor 2001 through the interface circuit ( Figure 5 (not shown) is coupled to the first processor 2001, which is not specifically limited in this embodiment of the present invention.

[0101] The transceiver 2003 is used to communicate with a network device or a terminal device.

[0102] Optionally, the transceiver 2003 may include a receiver and a transmitter ( Figure 5 The receiver is used to implement a receiving function, and the transmitter is used to implement a sending function.

[0103] Optionally, the transceiver 2003 may be integrated with the first processor 2001, or may exist independently and communicate with the first processor 2001 through the interface circuit ( Figure 5 (not shown) is coupled to the first processor 2001, which is not specifically limited in this embodiment of the present invention.

[0104] It should be noted that Figure 5The structure of the electronic device 410 shown in the figure does not constitute a limitation on the router, and the actual knowledge structure recognition device may include more or fewer components than those shown in the figure, or combine certain components, or arrange the components differently.

[0105] In addition, the technical effects of the electronic device 410 can refer to the technical effects of the business-finance integrated application method based on business-finance pre-processing described in the above method embodiment, and will not be repeated here.

[0106] It should be understood that the first processor 2001 in the embodiment of the present invention may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0107] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct memory bus random access memory (DRRAM).

[0108] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable system. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0109] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0110] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0111] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0112] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0113] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0114] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of the system or unit, which can be electrical, mechanical or other forms.

[0115] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0116] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0117] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0118] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A business-finance integrated application method based on business-finance pre-processing, characterized in that: The method comprises: S1. Preliminarily construct and deploy a settlement module and a delivery module in a common business operating system, wherein the settlement module is used to confirm the receivables / payables and taxes payable of the order business data, and the delivery module is used to confirm the income / expenditure of the order business data; S2. Obtain order business data from the order system and send it to the common business operating system; S3, the common business operating system identifies the business attributes of the order business data, activates the corresponding settlement module or the delivery module according to the business attributes, performs corresponding settlement or delivery processing on the order business data, and generates and outputs corresponding settlement or delivery processing results; S4. The financial system processes the settlement or delivery results into accounting documents and journal entries, generates corresponding financial data and saves them.

2. The business-finance integrated application method based on business-finance pre-processing according to claim 1 is characterized in that: In step S3, if the corresponding settlement module is activated, after executing the corresponding settlement processing on the order business data, the following is further included: Sending the settlement processing result to the payment / goods business system; The payment / goods business system performs payment / goods confirmation operations on the settlement processing results to confirm receivable cash flows or confirm inventory; After confirmation, proceed to step S4.

3. The business-finance integrated application method based on business-finance pre-processing according to claim 1 is characterized in that: S3, the common business operating system identifies the business attributes of the order business data, and activates the corresponding settlement module or the delivery module according to the business attributes, including: Receiving the order business data and importing the business driver identification model pre-deployed in the common business operating system; The business driver identification model identifies the business attributes of the order business data and outputs a corresponding system activation instruction; The common business operating system responds to the system activation instruction to activate the corresponding settlement module or the delivery module.

4. The business-finance integrated application method based on business-finance pre-processing according to claim 3 is characterized in that: The method for constructing the business driver identification model includes: Based on the LLM large language model, the business attribute recognition results of the common business operating system on the order business data and the settlement / delivery activation records generated according to the business attributes are collected in batches. The records contain corresponding system activation instructions to construct the corresponding order business driver data set M: M={m1,m2......mn}, m={order business data, business attributes, settlement / delivery activation records}; Perform feature engineering on the order business driven data set M, extract the business attribute values ​​of the corresponding order business data and the corresponding settlement / delivery activation type, and construct the corresponding feature set based on the extracted data: Divide the feature set into training set and validation set according to the preset ratio; Input the training set into a preset RF random forest model to perform business-driven training and learning, and construct the business-driven identification model; The business driver performance of the business driver identification model is verified using the validation set: If the verification is successful, deploying and applying the business driver identification model in the common business operating system; If the verification fails, the above steps are repeated to rebuild the business driver identification model.

5. The business-finance integrated application method based on business-finance pre-processing according to claim 4 is characterized in that: The batch collection of the business attribute recognition results of the order business data by the common business operating system and the settlement / delivery activation records generated according to the business attributes based on the LLM large language model includes: Deploy an LLMAPI port on the common business operating system to call the LLM large language model; Constructing extraction keywords and batch extraction logic for settlement order business data and delivery order business data, and constructing LLM prompt words in combination with the keywords and logic, and inputting the LLM prompt words into the LLM large language model; The LLM large language model is used to monitor the common business operating system, and the business conversion processing logs of the order business data are collected in batches, including the business attribute recognition results of the order business data and the settlement / delivery activation records generated according to the business attributes.

6. A business-finance integrated application system based on business-finance pre-processing, used to implement the business-finance integrated application method based on business-finance pre-processing as described in any one of claims 1 to 5, characterized in that: The system comprises: Order system, used to receive order business data; A common business operating system, used to obtain order business data from the order system, identify the business attributes of the order business data, activate the corresponding settlement module or the delivery module according to the business attributes, perform corresponding settlement or delivery processing on the order business data, and generate and output corresponding settlement or delivery processing results; The payment / goods business system is used to confirm the payment / goods of the settlement processing results, confirm the cash flow receivable or confirm the inventory; The financial system is used to process accounting documents and entries for the settlement or delivery processing results, generate corresponding financial data and save them.

7. An electronic device, characterized in that: The electronic device comprises: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, which can be called by a processor to execute the method according to any one of claims 1 to 5.

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