Bank T+0 accounting account preprocessing method and financial accounting prediction method and system using same

Abstract

The invention discloses a bank T + 0 accounting account preprocessing method and a financial accounting prediction method and system using the same, and the method comprises the steps: sorting and concluding bank accounting account processing files, and sorting out a universal transaction flow interface corresponding to the accounting transaction of a business system on the T day; the business system uploads a transaction flow to a pre-accounting center in a message queue form according to the general transaction flow interface; after receiving the flow, the pre-accounting center performs accounting preprocessing according to flow elements and verifies debit and credit balance and total score balance; and a result feedback module of the pre-accounting center writes the pre-processing result into a feedback message queue, feeds back the pre-processing result to the service system group, and stores or provides the pre-processing result to the AI prediction model. According to the invention, problems in accounting processing can be found in advance in time, the data quality is improved, the accuracy, integrity and consistency of data are ensured, the system stability is improved, and the problems of timeliness, comprehensiveness and accuracy of enterprise financial accounting prediction are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of bank account processing and financial accounting, and in particular to a method for preprocessing bank T+0 accounting accounts and a financial accounting prediction method and system using the method. Background Art

[0002] Traditional accounting and processing relies on a T+1 data reception and entry model. This means that on T+1, the business system pushes transaction flow files, account balance files, and other files to the accounting center in batches. Upon receipt, the accounting and budgeting center performs a series of checks, including data verification, debit / credit balance verification, and total / subsidiary balance verification, before recording the data. If the verification fails, the accounting center will provide feedback to the business system. After troubleshooting the issue, the business system will upload the batch files to the accounting center again for entry. This model requires all verification to be performed on T+1. If any issues arise, the time delay in discovery not only impacts data entry efficiency but also negatively impacts system stability.

[0003] The traditional financial accounting forecasting process usually relies on financial data, report data, balance sheet data, etc. to predict profit income, cost expenditure, etc. Since the multiple forecasts mentioned above can only be generated on T+1 day, traditional financial accounting forecasts also belong to the T+1 model.

[0004] like Figure 1 The figure shows a traditional financial accounting forecasting system using the above method, which includes: a business system group and an accounting center, and the business system group and the accounting center are data-connected.

[0005] In the traditional financial accounting forecasting process, part of the forecasting process relies on the experience of financial personnel and has a strong subjective problem.

[0006] In the traditional financial accounting and forecasting process, there is insufficient support for massive external data, which makes it difficult to ensure the comprehensiveness and accuracy of the forecast.

[0007] Due to the above three defects, traditional financial accounting forecasts have the problem of being unable to reflect the bank's future financial status in a timely and accurate manner. Summary of the Invention

[0008] The present invention aims to address existing issues in bank accounting and financial forecasting. Specifically, by establishing a method for preprocessing bank T+0 accounting, the present invention can identify problems in accounting processing in a timely manner, improve data quality, ensure data accuracy, completeness, and consistency, and enhance system stability. Furthermore, by constructing a financial accounting forecasting method and system based on T+0 accounting preprocessing data and utilizing AI technology, the present invention achieves a transition from a T+1 to a T+0 forecasting model, enabling a more comprehensive and accurate forecast of a bank's future financial status, thereby addressing the timeliness, comprehensiveness, and accuracy issues of corporate financial accounting forecasting.

[0009] The present invention provides a method for preprocessing bank T+0 accounting transactions. The method comprises the following steps: by sorting and summarizing bank accounting processing files, a general transaction flow interface corresponding to accounting transactions occurring in a business system on day T is compiled; the business system transmits the transaction flow to a pre-accounting center in the form of a message queue based on the general transaction flow interface; after receiving the flow, the pre-accounting center performs account preprocessing according to the flow elements and verifies the debit / credit balance and the total / credit balance.

[0010] The specific process is as follows:

[0011] Step S11: Each business system in the business system group sorts out the accounting transaction flow of the business system on day T;

[0012] Step S12: The general transaction flow interface of the business system group uses a message queue to send the accounting transaction flow to the budget and accounting center;

[0013] Step S13: The budgeting center receives accounting transaction flows from the message queue and organizes the transaction flows of the business system on day T into general transaction flows.

[0014] Step S14: The data checking module of the budget and accounting center verifies the legitimacy of the general transaction flow. If an error is found, the process proceeds to step S18.

[0015] Step S15: The accounting pre-processing module of the accounting center performs accounting pre-processing according to the configured accounting model. If an error occurs during the pre-processing process, the process proceeds to step S18.

[0016] Step S16: The credit and debit balance verification module of the budget and accounting center performs a credit and debit balance check. If the credit and debit are not balanced, the process proceeds to step S18.

[0017] Step S17: The total score balance verification module of the budget and accounting center performs a total score balance check;

[0018] Step S18: The result feedback module of the pre-calculation center writes the pre-processing result into the feedback message queue, feeds it back to the business system group, and also stores or provides the pre-processing result to the AI ​​prediction model;

[0019] In step S19, after receiving the feedback message, the business system group conducts problem troubleshooting, and then pushes the correct transaction flow to the budgeting center through the message queue again, and re-executes step S12.

[0020] The method for preprocessing bank T+0 accounting transactions of the present invention realizes the transmission of transaction flows of accounting types through a universal transaction flow interface and a message queue, and performs account preprocessing and multiple verification processes on the T+0 day.

[0021] Preferably, the validity of the general transaction flow is verified, including checking whether the data is not empty, whether the dictionary items are correct, whether there are unilateral accounts, etc.

[0022] The present invention establishes a method for preprocessing bank T+0 accounting transactions, thereby promptly discovering problems in accounting processing, improving data quality, ensuring data accuracy, completeness and consistency, and enhancing system stability.

[0023] The present invention also provides a financial accounting forecasting method using a bank T+0 accounting preprocessing method, the specific process of which includes:

[0024] S21 data collection and processing: collect massive data, including enterprise data and related market data, clean the collected massive data, exclude abnormal data, supplement missing values, and standardize the massive data to improve data quality;

[0025] S22 model establishment, select appropriate financial forecast analysis methods and combine them with actual business needs to establish an AI forecast model;

[0026] S23 parameter variable selection: select variable values ​​that affect financial accounting forecasts from massive data, input historical data into the AI ​​forecast model, and through model learning and analysis, enable it to understand the financial accounting forecast rules and select new parameter variables;

[0027] S24 model training and validation uses massive data to train and validate the established AI prediction model: the data is divided into training sets and validation sets, and the cross-validation method is used to continuously optimize the model to improve its accuracy and stability;

[0028] S25 forecast result output, using the AI ​​forecast model that has completed training and verification. On T+0 day, the AI ​​forecast model obtains corporate data processed by the bank's T+0 accounting preprocessing method to obtain financial forecast analysis results.

[0029] This method is based on the T+0 accounting pre-processing data method, combined with the company's historical data and relevant market data, and uses AI technology to achieve financial accounting forecasts.

[0030] Preferably, step S26 model optimization is also included. With the continuous iteration of business analysis and changes in data, the AI ​​prediction model is adjusted and improved in a timely manner to continuously improve the stability and accuracy of the prediction.

[0031] Preferably, the enterprise data includes current data and historical data.

[0032] Preferably, the financial forecasting analysis method utilizes regression analysis, time series analysis, neural network and other methods.

[0033] Preferably, the financial forecast analysis results include profit income, cost expenditure, etc. Enterprises can make corresponding decisions based on these analysis results to achieve sustainable development and competitive advantage.

[0034] The present invention also provides a financial accounting forecasting system that applies a bank T+0 accounting preprocessing method, comprising a financial accounting center and a business system group. The financial accounting center and the business system group are data-connected. The business system group includes multiple business systems and a universal transaction flow interface. The universal transaction flow interface uses a message queue to send accounting transaction flows to the financial accounting center.

[0035] The pre-accounting center includes: file access module, data verification module, accounting pre-processing module, credit and debit balance verification module, total balance verification module, result feedback module, data collection and processing module, model building module, model training and verification module, and prediction result output module.

[0036] A data collection and processing module is used to collect massive amounts of data, clean the collected massive amounts of data, exclude abnormal data, supplement missing values, and standardize the massive amounts of data to improve data quality. The massive amounts of data include enterprise data and related market data.

[0037] The model building module is used to select appropriate financial forecasting analysis methods and build AI forecasting models based on actual business needs;

[0038] The model training and validation module is used to select variable values ​​that affect financial accounting forecasts from massive data. Historical data is input into the AI ​​prediction model. Through model learning and analysis, it understands the financial accounting forecast rules and selects new parameter variables.

[0039] Use massive amounts of data to train and validate the established AI prediction model: divide the data into training and validation sets, and use cross-validation methods to continuously optimize the model to improve its accuracy and stability;

[0040] The prediction result output module uses the AI ​​prediction model that has completed training and verification. On T+0 day, the AI ​​prediction model obtains the enterprise data processed by the bank's T+0 accounting preprocessing method using the file access module, data verification module, accounting preprocessing module, debit and credit balance verification module, total and branch balance verification module and result feedback module of the budget accounting center to obtain the financial forecast analysis results.

[0041] The financial accounting forecasting system of the present invention realizes financial accounting forecasting under the T+0 mode based on the T+0 accounting preprocessing method.

[0042] Preferably, a model optimization module is also included to timely adjust and improve the AI ​​prediction model as business analysis continues to iterate and data changes, thereby continuously improving the stability and accuracy of the prediction.

[0043] The system is based on the T+0 accounting pre-processing data method, combined with the company's historical data and relevant market data, and uses AI technology to achieve financial accounting forecasts.

[0044] The present invention also provides a financial accounting forecasting system, comprising: a business system group and an accounting center, wherein the business system group and the accounting center are data-connected; the business system group includes a plurality of business systems;

[0045] On T+1, the business system group pushes transaction flow files and account balance files to the accounting center in batch file mode. After receiving the files, the accounting center verifies the data, credit and debit balance, and total balance before recording them in the accounts. For files that fail verification, the accounting center feeds the verification results back to the business system. After the business system conducts problem investigation, it uploads the files to the accounting center again in batch file mode for recording.

[0046] The financial accounting forecasting system also includes a budget accounting center, wherein the business system group is also connected to the budget accounting center through data;

[0047] The business system group also includes a general transaction flow interface, which uses a message queue to send accounting transaction flows to the budget and accounting center;

[0048] On T+0 day, the budget and accounting center uses AI prediction models to obtain corporate data that has been processed using the bank's T+0 accounting preprocessing method to obtain financial forecast analysis results.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] In terms of accounting processing, the T+0 accounting preprocessing method is used to advance the time for problem discovery from T+1 to T day, which can promptly detect problems such as missing data and illegality, and quickly feed back to the business system for correction through the message queue, greatly improving data quality, ensuring data accuracy, completeness and consistency, and effectively improving system stability.

[0051] In terms of financial accounting forecasting, we've achieved a shift from a T+1 to a T+0 forecasting model based on pre-processed T+0 accounting data, combined with AI technology and massive amounts of data. This reduces reliance on the experience of financial personnel and reduces the subjectivity of forecasts. Furthermore, through the analysis and processing of massive amounts of data, we've comprehensively improved the comprehensiveness and accuracy of financial accounting forecasts, enabling a more timely and accurate reflection of a bank's future financial status and providing strong support for corporate decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] To better understand the above and other objects, features, advantages, and functions of the present invention, reference may be made to the embodiments shown in the accompanying drawings. Like reference numerals in the accompanying drawings refer to like components. Those skilled in the art should understand that the accompanying drawings are intended to schematically illustrate preferred embodiments of the present invention and have no limiting effect on the scope of the present invention. The components in the drawings are not drawn to scale.

[0053] Figure 1 Shown is a traditional financial accounting forecasting system structure diagram.

[0054] Figure 2 Shown is a structural diagram of the financial accounting forecasting system of the present invention.

[0055] Figure 3 Shown is another structural diagram of the financial accounting forecasting system of the present invention.

[0056] Figure 4 Shown is the workflow diagram of the budget and accounting center.

[0057] Figure 5 Shown is a flow chart of the bank T+0 accounting preprocessing method used by the pre-accounting center. DETAILED DESCRIPTION

[0058] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0059] As used herein, the term "including" and its variations represent open inclusion, i.e., "including but not limited to." Unless otherwise stated, the term "or" means "and / or." The term "based on" means "based at least in part on." The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment." The term "another embodiment" means "at least one additional embodiment." The terms "first," "second," etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0060] In order to at least partially solve one or more of the above problems and other potential problems, an embodiment of the present disclosure proposes a calculation prediction system.

[0061] like Figure 2 As shown, the accounting and forecasting system of the present invention includes: a business system group and a budget accounting center, and the business system group and the budget accounting center are connected through data.

[0062] The business system group includes multiple business systems, such as a deposit system, a loan system, a bill system, a capital system, and a general transaction flow interface.

[0063] The pre-accounting center uses the following bank T+0 accounting pre-processing method of the present invention to perform the accounting operation:

[0064] Step S11: Each business system in the business system group sorts out the accounting transaction flow of the business system on day T;

[0065] Step S12: The general transaction flow interface of the business system group uses a message queue to send the accounting transaction flow to the budget and accounting center;

[0066] Step S13: The budgeting center receives accounting transaction flows from the message queue and organizes the transaction flows of the business system on day T into general transaction flows.

[0067] Step S14: The data checking module of the budget and accounting center verifies the legitimacy of the general transaction flow. If an error is found, the process proceeds to step S18.

[0068] Step S15: The accounting pre-processing module of the accounting center performs accounting pre-processing according to the configured accounting model. If an error occurs during the pre-processing process, the process proceeds to step S18.

[0069] Step S16: The credit and debit balance verification module of the budget and accounting center performs a credit and debit balance check. If the credit and debit are not balanced, the process proceeds to step S18.

[0070] Step S17: The total score balance verification module of the budget and accounting center performs a total score balance check;

[0071] Step S18: The result feedback module of the pre-calculation center writes the pre-processing result into the feedback message queue, feeds it back to the business system group, and also stores or provides the pre-processing result to the AI ​​prediction model;

[0072] In step S19, after receiving the feedback message, the business system group conducts problem troubleshooting, and then pushes the correct transaction flow to the budgeting center through the message queue again, and re-executes step S12.

[0073] Afterwards, the budget and accounting center used the AI ​​prediction model to obtain corporate data processed by the bank's T+0 accounting preprocessing method to obtain financial forecast analysis results.

[0074] like Figure 3 Figure 2 shows another structural diagram of a financial accounting and forecasting system. The accounting and forecasting system includes a business system cluster and an accounting center, with the business system cluster and the accounting center connected to each other. The business system cluster includes multiple business systems, such as a deposit system, a loan system, a bill system, a funding system, and a general transaction flow interface.

[0075] The working principle and process of the accounting system are the same as those of the existing technology: on T+1 day, the business system group pushes the transaction flow files and account balance files to the accounting center in batch file mode. After receiving the files, the accounting center records them after data verification, debit and credit balance verification, and total and branch balance verification. For files that fail the verification, the accounting center will feedback the verification results to the business system. After the business system conducts problem troubleshooting, it will upload them to the accounting center again in batch file mode for accounting operations.

[0076] The improvement of the accounting and forecasting system of the present invention is that it also includes a budget accounting center, and the business system group is also connected to the budget accounting center through data; the general transaction flow interface uses a message queue to send the accounting transaction flow to the budget accounting center.

[0077] On T+0 day, the budget and accounting center uses AI prediction models to obtain corporate data processed by the bank's T+0 accounting preprocessing method to obtain financial forecast analysis results.

[0078] This example adds the pre-accounting center to the existing accounting system, retaining the original T+1 accounting center. This allows for fast and immediate forecast analysis while also retaining the stable T+4 accounting center and accounting methods in the original system, minimizing changes and impacts to the existing system.

[0079] like Figure 4 The figure shows a workflow diagram of the pre-accounting center of a financial accounting forecasting system that applies the bank T+0 accounting pre-processing method.

[0080] The financial accounting forecasting system can be as follows Figure 2The individual systems shown can also be Figure 3 The shown one is added to the existing financial accounting system.

[0081] In this example, the financial accounting forecasting system includes a budgeting center and a business system group. The budgeting center and the business system group are connected for data. The business system group includes multiple business systems and a general transaction flow interface. The general transaction flow interface uses a message queue to send accounting transaction flows to the budgeting center.

[0082] The pre-accounting center includes: file access module, data verification module, accounting pre-processing module, credit and debit balance verification module, total balance verification module, result feedback module, data collection and processing module, model building module, model training and verification module, and prediction result output module.

[0083] S21 data collection and processing module, collects massive data, cleans the collected massive data, eliminates abnormal data, supplements missing values, and standardizes the massive data to improve data quality. The massive data includes enterprise data and related market data;

[0084] S22 model building module, selects appropriate financial forecast analysis methods and combines them with actual business needs to establish an AI forecast model;

[0085] The S23 model training and verification module selects variable values ​​that affect financial accounting forecasts from massive data, inputs historical data into the AI ​​forecasting model, and through model learning and analysis, enables it to understand the financial accounting forecasting rules and select new parameter variables;

[0086] The S24 model training and validation module uses massive data to train and validate the established AI prediction model: the data is divided into training sets and validation sets, and the cross-validation method is used to continuously optimize the model to improve its accuracy and stability;

[0087] The S25 prediction result output module uses the AI ​​prediction model that has completed training and verification. On T+0 day, the AI ​​prediction model obtains the enterprise data processed by the bank's T+0 accounting preprocessing method using the file access module, data verification module, accounting preprocessing module, loan balance verification module, total balance verification module and result feedback module of the budget accounting center to obtain the financial forecast analysis results.

[0088] The financial accounting forecasting system of the present invention realizes financial accounting forecasting under the T+0 mode based on the T+0 accounting preprocessing method.

[0089] exist Figure 2 or Figure 3 and Figure 4Based on these examples, the budgeting center can also incorporate a model optimization module to adjust and improve the AI ​​prediction model in a timely manner as business analysis continues to iterate and data changes. For example, this could include adjusting and optimizing the AI ​​prediction model at a preset frequency or based on a preset amount of processed data. Adding a model optimization module can continuously improve the stability and accuracy of predictions.

[0090] The enterprise data in step S21 includes but is not limited to current data and historical data.

[0091] The financial forecast analysis method in step S22 includes but is not limited to regression analysis, time series analysis, neural network and other methods.

[0092] The financial forecast analysis results in step S25 include but are not limited to profit income, cost expenditure, etc. The enterprise can make corresponding decisions based on these analysis results to achieve the data or results required for sustainable development and competitive advantage.

[0093] In the bank's financial accounting and forecasting system in the above example, when collecting massive amounts of data, the S21 data acquisition and processing module can first build an AI data acquisition platform. By connecting to internal enterprise systems and accessing external market data interfaces, it can collect massive amounts of enterprise data and related market data. After acquisition, data cleaning algorithms and tools are used to process the data. For example, statistical analysis methods are used to identify and eliminate abnormal data, interpolation methods are used to supplement missing values, and normalization methods are used to standardize the data.

[0094] During parameter variable selection, the AI ​​model's feature selection algorithm can be used to filter out variables with significant impact on financial accounting forecasts from massive amounts of data. Simultaneously, historical data is fed into the AI ​​forecasting model for training, allowing the model to learn the rules and patterns of financial accounting forecasting, enabling it to automatically discover new parameter variables. During the model development phase, appropriate AI forecasting models are developed based on the bank's specific financial forecasting needs. For example, for short-term profit and revenue forecasts, time series analysis methods can be used, while for long-term cost and expenditure forecasts, regression analysis and neural network methods can be combined. During model training and validation, the training and validation sets are rationally divided, and the model is trained and evaluated multiple times using cross-validation, continuously adjusting model parameters and optimizing model performance. Once model training and validation achieve the desired results, relevant data, such as real-time T+0 accounting preprocessing data, is fed to generate accurate financial forecast analysis results, such as profit and revenue, cost and expenditure data for the future period. As business evolves and data becomes available, the model is regularly optimized and adjusted to ensure the accuracy and stability of the forecast results.

[0095] like Figure 5The following is a method for pre-processing bank T+0 accounting transactions. The specific process is as follows:

[0096] Step S11: Each business system in the business system group sorts out the accounting transaction flow of the business system on day T;

[0097] Step S12: The general transaction flow interface of the business system group uses a message queue to send the accounting transaction flow to the budget and accounting center;

[0098] Step S13: The budgeting center receives accounting transaction flows from the message queue and organizes the transaction flows of the business system on day T into general transaction flows.

[0099] Step S14: The data checking module of the budget and accounting center verifies the legitimacy of the general transaction flow, including but not limited to checking whether the data is non-empty, whether the dictionary items are correct, whether there are unilateral accounts, etc. If an error is found, the process proceeds to step S18;

[0100] Step S15: The accounting pre-processing module of the accounting center performs accounting pre-processing according to the configured accounting model. If an error occurs during the pre-processing process, the process proceeds to step S18.

[0101] Step S16: The credit and debit balance verification module of the budget and accounting center performs a credit and debit balance check. If the credit and debit are not balanced, the process proceeds to step S18.

[0102] Step S17: The total score balance verification module of the budget and accounting center performs a total score balance check;

[0103] In step S18, the result feedback module of the pre-calculation center writes the pre-processing results into the feedback message queue and feeds them back to the business system group; the pre-processing results are also stored or provided to the AI ​​prediction model. The pre-processing results include but are not limited to enterprise data;

[0104] In step S19, after receiving the feedback message, the business system group conducts problem troubleshooting, and then pushes the correct transaction flow to the budgeting center through the message queue again, and re-executes step S12.

[0105] The method for preprocessing bank T+0 accounting transactions of the present invention realizes the transmission of transaction flows of accounting types through a universal transaction flow interface and a message queue, and performs account preprocessing and multiple verification processes on the T+0 day.

[0106] The above patent application documents are for reference only. The actual patent application documents must be drafted in strict compliance with the Patent Law and relevant regulations. It is recommended that when formally applying for a patent, they should be further improved and reviewed by a professional patent agency or lawyer to ensure the success rate of the patent application and the effectiveness of the rights protection.

Claims

1. A method for pre-processing bank T+0 accounting transactions, characterized in that: The specific process is as follows: Step S11: Each business system in the business system group sorts out the accounting transaction flow of the business system on day T; Step S12: The general transaction flow interface of the business system group uses a message queue to send the accounting transaction flow to the budget and accounting center; Step S13: The budgeting center receives accounting transaction flows from the message queue and organizes the transaction flows of the business system on day T into general transaction flows. Step S14: The data checking module of the budget and accounting center verifies the legitimacy of the general transaction flow. If an error is found, the process proceeds to step S18. Step S15: The accounting pre-processing module of the accounting center performs accounting pre-processing according to the configured accounting model. If an error occurs during the pre-processing process, the process proceeds to step S18. Step S16: The credit and debit balance verification module of the budget and accounting center performs a credit and debit balance check. If the credit and debit are not balanced, the process proceeds to step S18. Step S17: The total score balance verification module of the budget and accounting center performs a total score balance check; Step S18: The result feedback module of the pre-calculation center writes the pre-processing result into the feedback message queue, feeds it back to the business system group, and also stores or provides the pre-processing result to the AI ​​prediction model; In step S19, after receiving the feedback message, the business system group conducts problem troubleshooting, and then pushes the correct transaction flow to the budgeting center through the message queue again, and re-executes step S12.

2. A method for pre-processing bank T+0 accounting transactions as claimed in claim 1, characterized in that: Verify the legitimacy of general transaction flows, including checking whether the data is non-empty, whether the dictionary items are correct, and whether there are unilateral accounts.

3. A financial accounting forecasting method using a bank T+0 accounting preprocessing method, characterized in that: The process includes: S21 data collection and processing: collect massive data, including enterprise data and related market data, clean the collected massive data, exclude abnormal data, supplement missing values, and standardize the massive data to improve data quality; S22 model establishment, select appropriate financial forecast analysis methods and combine them with actual business needs to establish an AI forecast model; S23 parameter variable selection: select variable values ​​that affect financial accounting forecasts from massive data, input historical data into the AI ​​forecast model, and through model learning and analysis, enable it to understand the financial accounting forecast rules and select new parameter variables; S24 model training and validation uses massive data to train and validate the established AI prediction model: the data is divided into training sets and validation sets, and the cross-validation method is used to continuously optimize the model to improve its accuracy and stability; S25 outputs the prediction results. Using the AI ​​prediction model that has completed training and verification, on T+0 day, the AI ​​prediction model obtains the enterprise data processed by the bank T+0 accounting preprocessing method as described in any one of claims 1 or 2, and obtains the financial forecast analysis results.

4. A financial accounting forecasting method using a bank T+0 accounting preprocessing method as claimed in claim 3, characterized in that: It also includes step S26 model optimization. With the continuous iteration of business analysis and changes in data, the AI ​​prediction model is adjusted and improved in a timely manner to continuously improve the stability and accuracy of the prediction.

5. The financial accounting forecasting method using the bank T+0 accounting preprocessing method according to claim 3, characterized in that: The enterprise data includes current data and historical data.

6. A financial accounting forecasting method using a bank T+0 accounting preprocessing method as claimed in claim 3, characterized in that: The financial forecast analysis method utilizes regression analysis, time series analysis, or neural network.

7. A financial accounting forecasting method using a bank T+0 accounting preprocessing method as claimed in claim 3, characterized in that: The financial forecast analysis results include profit income and cost expenditure.

8. A financial accounting forecasting system using a bank T+0 accounting preprocessing method, characterized in that: It includes the budget and accounting center and the business system group. The budget and accounting center and the business system group are connected to each other. The business system group includes multiple business systems and a general transaction flow interface. The general transaction flow interface uses a message queue to send accounting transaction flows to the budget and accounting center. The pre-accounting center includes: file access module, data verification module, accounting pre-processing module, credit and debit balance verification module, total balance verification module, result feedback module, data collection and processing module, model building module, model training and verification module, and prediction result output module. A data collection and processing module is used to collect massive amounts of data, clean the collected massive amounts of data, exclude abnormal data, supplement missing values, and standardize the massive amounts of data to improve data quality. The massive amounts of data include enterprise data and related market data. The model building module is used to select appropriate financial forecasting analysis methods and build AI forecasting models based on actual business needs; The model training and validation module is used to select variable values ​​that affect financial accounting forecasts from massive data. Historical data is input into the AI ​​prediction model. Through model learning and analysis, it understands the financial accounting forecast rules and selects new parameter variables. Use massive amounts of data to train and validate the established AI prediction model: divide the data into training and validation sets, and use cross-validation methods to continuously optimize the model to improve its accuracy and stability; The prediction result output module uses the AI ​​prediction model that has completed training and verification. On T+0 day, the AI ​​prediction model obtains the enterprise data of the pre-accounting center's file access module, data verification module, accounting preprocessing module, debit and credit balance verification module, total and branch balance verification module and result feedback module using the bank T+0 accounting preprocessing method as described in any one of claims 1 or 2 to obtain financial forecast analysis results.

9. A financial accounting forecasting system using a bank T+0 accounting preprocessing method as claimed in claim 8, characterized in that: It also includes a model optimization module, which is used to timely adjust and improve the AI ​​prediction model as business analysis continues to iterate and data changes, thereby continuously improving the stability and accuracy of the prediction.

10. Financial accounting forecasting system, characterized by: include: A business system group and an accounting center, wherein the business system group and the accounting center are data-connected; the business system group includes multiple business systems; On T+1, the business system group pushes transaction flow files and account balance files to the accounting center in batch file mode. After receiving the files, the accounting center verifies the data, credit and debit balance, and total balance before recording them in the accounts. For files that fail verification, the accounting center feeds the verification results back to the business system. After the business system conducts problem investigation, it uploads the files to the accounting center again in batch file mode for recording. The financial accounting forecasting system further comprises a forecasting center of the financial accounting forecasting system according to any one of claims 8 or 9, wherein the business system group is also connected to the forecasting center via data; The business system group also includes a general transaction flow interface, which uses a message queue to send accounting transaction flows to the budget and accounting center; On T+0 day, the budget and accounting center uses AI prediction models to obtain corporate data that has been processed using the bank's T+0 accounting preprocessing method to obtain financial forecast analysis results.

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