Configuration solution for quickly realizing integration of unmanned retail income exchange and finance

Abstract

The invention discloses a configuration solution for quickly realizing unmanned retail income exchange and financial fusion, which comprises the following steps of: establishing a sales and financial fusion model: establishing the sales and financial fusion model, comprising the steps of establishing a conversion relationship between collection channels and exchange settlement, establishing an association relationship between various collection channels and a fund settlement main body, establishing a mapping relationship between a business region and a financial accounting main body in a time dimension, and supporting multiple business scenes; a profit unit model and a financial data model, each model having a particular data dimension. According to the method, the problems of large data volume, multiple scenes and complexity in unmanned retail of a large amount of sales data and financial fusion are mainly solved, and a related business and financial fusion solution is provided, so that a data model which can be rapidly configured and is low in research and development cost input is built, configuration is supported, and new sales money return business scenes can be rapidly copied and expanded.

Description

Technical Field

[0001] The present invention relates to the field of financial integration technology for unmanned retail, and in particular to a configurable solution for quickly realizing revenue transactions and financial integration for unmanned retail. Background Art

[0002] At present, the unmanned retail industry is developing rapidly. The accounting and management workload involved in retail business accounting, supplier reconciliation and settlement, inventory accounting, accounting file management, etc. is huge. Among them, the monthly sales collection of millions of retail orders and the accounting of internal related transactions require a lot of manual verification and accounting, as well as powerful system functions and performance to process business data. At the same time, the rapid growth of business volume brought by retail-related businesses and the emergence of various business scenarios in the development of new industries have posed new challenges to the company's EPR and other systems, requiring more R&D investment, which is easy to cause repeated investment in R&D costs for the company, and cannot quickly meet the company's operational requirements. These problems have affected the company's operating efficiency and results.

[0003] In order to solve these problems, the current main method is to use BI big data platform, SQL, Python and other tools to group and aggregate large quantities of business data to reduce the amount, and then complete financial accounting, system integration functions or manual accounting. However, there are some problems: (1) Business data is aggregated on the big data platform / tool, and the data grouping and aggregation is completed based on the business dimension, which is inconsistent with the grouping or accounting rule classification standards of financial accounting. This results in the need to re-classify and summarize the data according to the financial accounting standards after grouping and aggregation for accounting; (2) Based on internal business assessment and management, it is impossible to quickly meet the document flow, capital flow and other business online rapid closure of related transactions in the collection scenario; (3) The derivation of new business scenarios cannot be directly completed through a simple and small amount of R&D investment to complete the transformation and adaptation of system functions, and lacks a more general and replicable and configurable system function support. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention provides a configurable solution for quickly realizing the integration of unmanned retail revenue transactions and finance. The present invention mainly solves the problems of large data volume, multiple scenarios and complexity in the integration of large amounts of sales data and finance in unmanned retail, and provides relevant business-finance integration solutions to build a data model that can be quickly configured and has low R&D cost investment, supports configurability, and can quickly replicate and expand new sales collection business scenarios to meet the daily operation and management needs of enterprises and reduce costs and increase efficiency.

[0005] In order to achieve the above-mentioned purpose, the present invention provides a configurable solution for quickly realizing the integration of unmanned retail revenue transactions and finance, including the following steps:

[0006] Step S1: Building a sales and financial integration model: Building a sales and financial integration model, including establishing the conversion relationship between collection channels and current settlements, establishing the association relationship between various collection channels and fund settlement entities, establishing the mapping relationship between business regions and financial accounting entities in the time dimension, and supporting multiple business scenarios:

[0007] Step S2: define business data models: including sales collection data model (AR), profit unit model (Forgs) and financial data model (FL_AR), each model has a specific data dimension;

[0008] Step S3: Define the sales and finance integration model: including the multi-channel payment conversion model (AR_Tre) and the multi-agent conversion model (AR_Torg), each model has a specific data dimension;

[0009] Step S4: Automatically obtain and convert business data: by traversing the sales retail payment collection data set (ar), allocating and matching the profit unit data set (forgs), the multi-channel payment collection conversion data set (ar_tre), and the multi-subject conversion data set (ar_torg), the final fused (converted) financial data set (fl_ar) is automatically generated;

[0010] Step S5: Automated integration: By building an API interface, you can integrate internal transaction documents, integrate the financial system, and complete document flow integration and financial accounting with one click.

[0011] Preferably, in step S1, a conversion relationship between a payment collection channel and current settlement is established. There are multiple payment collection channels, and each payment collection channel needs to be clearly identified to a specific current settlement object for financial accounting.

[0012] Establish the relationship between various payment channels and fund settlement entities to solve the problem of fund flow accounting when merchant numbers are bound to specific payment collections, and support the establishment of different fund collection entity business scenarios based on regions and payment channels;

[0013] Establish a mapping relationship between business regions and financial accounting entities in the time dimension to adapt to the accounting scenario requirements where the license switch does not affect the income attribution entity;

[0014] .Support multiple business scenarios to support retail revenue, funds and current accounting, and complete functional support through encapsulated programmatic logic and simple configuration.

[0015] Preferably, the data dimensions of the sales collection data model in step S2 include statistical month, sales collection date, business type, region, tax code (tax rate), shelf type, actual collection in the current month, payment in the current month and refund in the current month, payment in previous months and refund in the current month.

[0016] Preferably, in step S2, the data dimensions of the profit unit model (Forgs model) include business entity, profit center, cost center, region, and duration.

[0017] Preferably, in step S2, the financial data model includes financial accounting transaction objects, business entities, and payment entities.

[0018] Preferably, in step S3, the data dimensions of the multi-channel payment conversion model include sales payment channels, financial accounting transaction objects, whether the payment is from multiple entities (0, 1), and payment entities.

[0019] Preferably, in step S3, the data dimensions of the multi-subject conversion model include financial accounting transaction objects, business entities, and payment entities.

[0020] Preferably, the specific steps of automatically acquiring and converting business data in step S4 are as follows:

[0021] Step S401: Classify and group sales payment data: traverse the sales retail payment data set (ar) and classify and group it according to the payment subject, time dimension, and dimension information;

[0022] Step S402, converting business data: matching the classified and grouped data with the profit unit data set (forgs), the multi-channel payment conversion data set (ar_tre), and the multi-subject conversion data set (ar_torg) to automatically generate the final integrated converted financial data set (fl_ar);

[0023] Step S403, automatically generate internal transaction documents: through the sales and financial integration model, complete the conversion of regions in business data into financial accounting entities and cost centers and profit centers, and convert the collection channels into specific transaction objects;

[0024] Step S404, finally generating the transactions between the income attribution entity and the fund collection entity to achieve the integration of income and finance.

[0025] Preferably, in step S401, the payment collection subject is divided into payment collection by the business entity and payment collection on behalf of the business entity; the time dimension is divided into current sales collection, past period collection, past period sales refund, and current sales refund.

[0026] The technical solution of the present invention has the following beneficial effects:

[0027] The present invention mainly solves the problem of large data volume, multiple scenarios and complexity in the integration of large amounts of sales data and finance in unmanned retail, and provides relevant business-finance integration solutions to build a data model that can be quickly configured and has low R&D cost investment, supports configurability, and can quickly replicate and expand new sales collection business scenarios to meet the daily operation and management needs of enterprises and reduce costs and increase efficiency.

[0028] Data model fusion: The present invention integrates multiple data models such as the sales collection data model (AR), profit unit model (Forgs), and financial data model (FL_AR) by constructing a sales and financial fusion model, thereby realizing unified management and analysis of data. This fusion enables financial data to be updated synchronously with sales data, thereby improving the real-time and accuracy of the data.

[0029] Automatic data conversion: Through automated data acquisition and conversion steps, the present invention can automatically classify and group the scattered sales payment data, match it with the profit unit, multi-channel payment conversion data set (AR_Tre), and multi-subject conversion data set (AR_Torg), and automatically generate the final integrated converted financial data set (FL_AR). This process reduces manual intervention, reduces the error rate, and improves data processing efficiency.

[0030] Dynamic business scenario support: The present invention supports flexible configuration of multiple business scenarios, such as retail revenue, funds and current accounting, etc. Through encapsulated programmatic logic and simple configuration, the system can quickly adapt to new business needs and market changes without large-scale system reconstruction.

[0031] Conversion relationship between payment channels and current settlement: The present invention establishes a conversion relationship between payment channels and current settlement, clarifies the financial accounting objects corresponding to each payment channel, solves the problem of fund current accounting for merchant numbers bound to specific payments, and supports the establishment of different fund collection entity business scenarios according to region and payment channel dimensions.

[0032] Mapping relationship between business regions and financial accounting entities in the time dimension: The present invention establishes a mapping relationship between business regions and financial accounting entities in the time dimension, so that the accounting scenario requirements of the income attribution entity will not be affected when the license is switched, thereby improving the accuracy and compliance of financial reports.

[0033] API interface integration: The present invention realizes rapid integration with the financial system by building an API interface, completes the integration of internal transaction documents with one click, integrates the financial system, completes document flow integration and financial accounting, and improves the system integration.

[0034] The present invention significantly reduces the workload of manual verification and accounting through automated data acquisition and conversion steps, and improves the efficiency of financial accounting; by establishing a conversion relationship between collection channels and current settlements, the accuracy and consistency of financial data are ensured, and human errors are reduced; and supports a configuration method for multiple business scenarios, so that the system can quickly adapt to new business needs and market changes without large-scale system reconstruction. Automatically generating a fused financial data set helps to quickly generate accurate financial reports, thereby improving the timeliness and reliability of financial reports. Automated financial accounting and integration reduces the investment of enterprises in data processing and management, thereby reducing operating costs. Accurate and timely data provision provides better decision support for management, helping enterprises to make faster and more accurate business decisions. Accurate financial data supports better data analysis and report generation, and provides more reliable information support for enterprise management. Through the support of mapping relationships and business scenarios, the transparency of business operations is improved, and the relationship between financial and business data is clearer. The automated integration steps accelerate the business processing flow, shorten the business cycle, and improve the response speed of the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a flow chart of retail income transactions and financial integration of the present invention;

[0036] Figure 2 This is a diagram of the application process of the sales and finance fusion model of the present invention. DETAILED DESCRIPTION

[0037] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0038] Reference Figure 1 to Figure 2 The present invention provides a configurable solution for quickly realizing unmanned retail revenue transactions and financial integration, including the following steps:

[0039] Step S1: Building a sales and financial integration model: Building a sales and financial integration model, including establishing the conversion relationship between collection channels and current settlements, establishing the association relationship between various collection channels and fund settlement entities, establishing the mapping relationship between business regions and financial accounting entities in the time dimension, and supporting multiple business scenarios:

[0040] Step S2: define business data models: including sales collection data model (AR), profit unit model (Forgs) and financial data model (FL_AR), each model has a specific data dimension;

[0041] Step S3: Define the sales and finance integration model: including the multi-channel payment conversion model (AR_Tre) and the multi-agent conversion model (AR_Torg), each model has a specific data dimension;

[0042] Step S4: Automatically obtain and convert business data: by traversing the sales retail payment collection data set (ar), allocating and matching the profit unit data set (forgs), the multi-channel payment collection conversion data set (ar_tre), and the multi-subject conversion data set (ar_torg), the final fused (converted) financial data set (fl_ar) is automatically generated;

[0043] Step S5: Automated integration: By building an API interface, you can integrate internal transaction documents, integrate the financial system, and complete document flow integration and financial accounting with one click.

[0044] Furthermore, in step S1, a conversion relationship between a payment collection channel and current settlement is established. There are multiple payment collection channels, and each payment collection channel needs to be clearly identified to a specific current settlement object for financial accounting.

[0045] Establishing the association between various payment channels and fund settlement entities is used to solve the problem of fund transactions accounting for merchant numbers bound to specific payments, and supports the establishment of different fund collection entity business scenarios according to the dimensions of regions and payment channels; establishing a mapping relationship between business regions and financial accounting entities in the time dimension, which is used to adapt the switching of licenses without affecting the accounting scenario requirements of the income attribution entity; supporting a variety of business scenarios to support retail income, funds and transactions accounting, and completing functional support through encapsulated programmatic logic and simple configuration; in this embodiment, the conversion relationship between payment channels and transactions is established: by clarifying the financial accounting objects corresponding to each payment channel, the present invention can ensure the accuracy and consistency of financial data, thereby improving the efficiency and reliability of financial accounting. Establishing the association between various payment channels and fund settlement entities: This step solves the problem of fund transactions accounting for merchant numbers bound to specific payments, supports the establishment of different fund collection entity business scenarios according to the dimensions of regions and payment channels, and enhances the flexibility and adaptability of financial management. Establishing a mapping relationship between business regions and financial accounting entities in the time dimension: By adapting the license switch without affecting the accounting scenario requirements of the entity to which the income is attributed, the present invention improves the accuracy and compliance of financial reports. Supporting multiple business scenarios: The present invention supports multiple business scenarios such as retail income, funds and current accounting through encapsulated programmatic logic and simple configuration, so that the system can quickly adapt to new business needs and market changes without large-scale system reconstruction. Improving data processing speed: Automated data acquisition and conversion steps reduce manual operations, speed up data processing, and enable enterprises to respond to market changes more quickly. Reducing operating costs and risks: Through automated financial accounting and integration, human errors and potential financial risks are reduced, while reducing the operating costs of enterprises in data processing and management. Enhanced data analysis and reporting capabilities: Accurate financial data supports better data analysis and report generation, providing more reliable information support for enterprise management, and helping to make more informed business decisions.

[0046] Further, in step S2, the data dimensions of the sales collection data model include statistical month, sales collection date, business type, region, tax code (tax rate), shelf type, actual collection in the current month, payment in the current month and refund in the current month, payment in the previous month and refund in the current month. In this embodiment, the statistical month and sales collection date: the definition of these dimensions enables the enterprise to track and analyze the sales collection data in time series, so as to better understand the revenue trend and seasonal fluctuations, and provide data support for financial planning and forecasting. Business type and region: By distinguishing different business types and regions, enterprises can conduct financial analysis for specific markets and business lines, optimize resource allocation, and formulate more accurate financial strategies for specific regions. Tax code (tax rate): The dimensions of tax code and tax rate ensure the accuracy of tax data, help enterprises correctly calculate the tax payable, avoid tax risks, and optimize tax planning. Shelf type: The data dimension of shelf type allows enterprises to subdivide the sales collection of different product lines, so as to more accurately evaluate the financial performance and market competitiveness of each product line. Actual receipts for the month: Data in this dimension helps companies track actual receipts and compare them with expected revenue, thereby promptly identifying and resolving revenue recognition issues. Payments and refunds for the month: Data in this dimension enables companies to accurately track payments and refunds for the month, adjust cash flow forecasts in a timely manner, and optimize cash flow management.

[0047] Payments made in previous months and refunds made in current month: Data in this dimension helps companies track payments and refunds across periods, which is helpful for understanding and improving the financial health of the company.

[0048] Further, in step S2, the data dimensions of the profit unit model (Forgs model) include business entities, profit centers, cost centers, regions, and durations; in this embodiment, business entities: by clarifying the data dimensions of business entities, enterprises can track and aggregate the financial performance of specific business entities, and provide accurate data for independent accounting and performance evaluation of business units. Profit center: The definition of the profit center dimension enables enterprises to analyze the financial contribution of each profit center, optimize the financial decision of the profit center, and conduct effective financial monitoring on it. Cost center: The data dimension of the cost center helps enterprises track the cost occurrence of the cost center, providing a basis for cost control and cost optimization, thereby improving cost-effectiveness. Region: The data of the regional dimension enables enterprises to analyze financial performance according to geographical regions, and provide financial support for regional market strategies and resource allocation. Duration: The data dimension of the duration allows enterprises to evaluate the benefits of long-term and short-term financial activities, which is crucial for the return analysis of long-term investments and the management of short-term financial liquidity. Through the definition of these data dimensions, the present invention can provide enterprises with in-depth business and financial analysis, so that enterprises can better understand the financial performance of each business unit, optimize resource allocation, improve financial efficiency, and provide a solid data foundation for strategic decision-making. In addition, data from these dimensions can also help companies meet their compliance and transparency requirements and improve their overall financial management level.

[0049] Further, in step S2, the financial data model includes financial accounting intercourse objects, business entities, and collection entities; in this embodiment, financial accounting intercourse objects: by clarifying the data dimensions of financial accounting intercourse objects, the enterprise can accurately track and manage financial transactions with external entities to ensure the accuracy and completeness of financial data. Business entity: The data dimension of the business entity enables the enterprise to collect the financial data of a specific business entity, provide support for the financial performance evaluation and independent accounting of the business unit, and enhance the financial basis of business decisions. Collection entity: The data of the collection entity dimension helps the enterprise identify and manage collection responsibilities, which is crucial for cash flow management and the formulation of collection strategies, and also provides key information for financial analysis and reporting. The data definitions of these dimensions enable the enterprise to more accurately reflect business activities when conducting financial accounting and reporting, and improve the transparency and reliability of financial data. In addition, the data of these dimensions also help the enterprise to better understand the financial performance of different business units and collection entities when conducting financial analysis, thereby providing solid data support for the enterprise's financial planning and strategic decision-making. Through these detailed data dimension definitions, the present invention can provide enterprises with a comprehensive and detailed view of financial data, enabling enterprises to more accurately monitor and manage financial activities and improve the accuracy and transparency of financial reports. It also provides strong data support for management to make more informed business decisions.

[0050] Furthermore, in step S3, the data dimensions of the multi-channel collection conversion model include sales collection channels, financial accounting transaction objects, whether the collection is from multiple entities (0, 1), and collection entities; in this embodiment, sales collection channels: by clarifying the data dimensions of sales collection channels, enterprises can track sales performance and collection status of different channels, and provide data support for channel management and optimization.

[0051] Financial accounting transaction objects: Data in this dimension ensures the accuracy of financial accounting, enables enterprises to correctly collect and allocate financial transactions, and improves the transparency and reliability of financial reports. Whether there are multiple entities for collection (0, 1): This data dimension allows enterprises to identify whether there are multiple entities involved in the collection, which is crucial for handling complex financial transactions and multi-level corporate structures, and ensures the correct processing of financial data. Collection entity: Data in the collection entity dimension helps enterprises identify and manage collection responsibilities, which is crucial for cash flow management and the formulation of collection strategies, and also provides key information for financial analysis and reporting. Data in these dimensions also help enterprises better understand the financial performance of different collection channels and collection entities when conducting financial analysis, thereby providing solid data support for the company's financial planning and strategic decision-making. This refined data management helps improve the company's financial efficiency, optimize financial processes, and ultimately improve the overall financial health of the company.

[0052] Further, in step S3, the data dimensions of the multi-subject conversion model include financial accounting transaction objects, business entities, and collection entities; in this embodiment, financial accounting transaction objects: by clarifying the data dimensions of financial accounting transaction objects, enterprises can ensure the accuracy and consistency of financial data, thereby correctly reflecting all financial transactions in financial reports. Business entities: The data dimensions of business entities enable enterprises to track and evaluate the financial performance of each business entity, provide data support for the independent accounting and performance evaluation of business units, and enhance the financial basis of business decisions. Collection entity: The data of the collection entity dimension helps enterprises identify and manage collection responsibilities, which is crucial for cash flow management and the formulation of collection strategies, and also provides key information for financial analysis and reporting. The data definitions of these dimensions enable enterprises to more accurately reflect business activities when conducting financial accounting and reporting, and improve the transparency and reliability of financial data. In addition, the data of these dimensions also help enterprises better understand the financial performance of different business entities and collection entities when conducting financial analysis, thereby providing solid data support for the financial planning and strategic decision-making of enterprises.

[0053] Furthermore, the specific steps of automatically acquiring and converting business data in step S4 are as follows:

[0054] Step S401: Classify and group sales collection data: traverse the sales retail collection data set (ar), classify and group according to the collection entity, time dimension, and dimension information; the present invention can ensure the organization and manageability of the data, and provide a clear data foundation for subsequent data processing and analysis.

[0055] Step S402, converting business data: matching the classified and grouped data with the profit unit data set (forgs), the multi-channel payment collection conversion data set (ar_tre), and the multi-subject conversion data set (ar_torg) to automatically generate the final fused and converted financial data set (fl_ar); the present invention can automatically generate the final fused and converted financial data set (fl_ar), reducing manual intervention and improving the efficiency and accuracy of data processing.

[0056] Step S403, automatically generate internal transaction documents: through the sales and financial integration model, complete the conversion of regions in business data into financial accounting entities and cost centers and profit centers, and convert the collection channels into specific objects of transactions; through the sales and financial integration model, the present invention can automatically complete the conversion of regions in business data into financial accounting entities and cost centers and profit centers, and convert the collection channels into specific objects of transactions, which helps to ensure the accuracy and completeness of financial data, and also provides convenience for the management of internal transactions.

[0057] The details are as follows:

[0058] Assume that ar is the sales retail collection dataset, forgs is the profit unit dataset, ar_tre is the multi-channel collection conversion dataset, ar_torg is the multi-subject conversion dataset, and fl_ar is the final fused (converted) financial dataset.

[0059] Traverse the ar dataset and assign matching forgs, ar_tre, and ar_torg datasets to automatically generate the fl_ar dataset

[0060] (1) When a4=n4 and a1 is between n5, then

[0061] b1=a1,

[0062] b2=n1,

[0063] b3=n2,

[0064] b5=n3,

[0065] b6=a5,

[0066] b7=a6,

[0067] b8=a7-a8-a9

[0068] If a4=n4 and a1 is between n5 and does not satisfy it, the Financial Early Warning Assistant pushes a message reminder;

[0069] When a3=c1 and c3=0, then b4=c4.

[0070] When a3=c1, and c3=1, if b2=d2, then b4=d3

[0071] If a3=c1 or b2=d2 does not exist, the Financial Early Warning Assistant will push a message to remind you

[0072] After the above calculation process, the internal related transaction document set, namely the fl_ar data set, can be automatically generated.

[0073] Step S404, finally generating the transactions between the income attribution entity and the fund collection entity to achieve the integration of income and finance. The present invention can achieve the integration of income and finance, ensure the correct attribution of income data, and optimize the transaction management of the fund collection entity, thereby improving the transparency and reliability of financial reports.

[0074] In general, the automatic acquisition and conversion steps in step S4 not only improve the processing speed and accuracy of financial data through efficient data processing processes, but also enhance the company's control over financial data, providing strong data support for the company's financial management and decision-making. In addition, this automated data processing process also helps reduce the company's operating costs and improve its operating efficiency.

[0075] Furthermore, in step S401, the payment collection subject is divided into payment collection by the business subject and payment collection on behalf of the business subject; the time dimension is divided into current sales collection, past period collection, past period sales refund, and current sales refund.

[0076] In this embodiment, the subdivision of the collection subject is as follows: Collection of the business subject: By distinguishing the collection of the business subject, the present invention can ensure that the income directly related to the internal business activities of the enterprise is accurately tracked and recorded, thereby improving the accuracy of business accounting. Collection on behalf of others: For collection on behalf of others, that is, collection by non-business subjects, the present invention can ensure that these incomes are properly identified and classified, which is convenient for enterprises to conduct cash flow management and financial analysis. Subdivision of the time dimension: Current sales collection: The data in this dimension helps enterprises track the collection of current sales activities and provide instant information for short-term cash flow management. Past collection: By analyzing the past collection data, enterprises can evaluate historical sales performance and plan future sales strategies. Past sales refunds: The data in this dimension helps enterprises monitor and manage sales refunds, reduce financial losses, and improve customer satisfaction. Current sales refunds: By tracking current sales refunds, enterprises can adjust sales strategies in a timely manner and reduce the occurrence of future refunds, thereby improving sales efficiency and customer loyalty. Through these subdivided data dimensions, the present invention can provide enterprises with more accurate and comprehensive financial data, enabling enterprises to better understand and manage their revenue streams. This refined data management helps enterprises make more informed decisions in financial planning and analysis, while also improving their ability to control financial risks. In addition, these dimensional data also help enterprises better understand the financial performance of different business entities and payment entities when conducting financial analysis, thereby providing solid data support for the company's financial planning and strategic decision-making. This automated data processing process also helps reduce the company's operating costs and improve its operating efficiency.

[0077] It can be seen from the above embodiments that the present invention mainly solves the problem of large data volume, multiple scenarios and complexity in the integration of large amounts of sales data and finance in unmanned retail, and provides relevant business-finance integration solutions to build a data model that can be quickly configured and has low R&D cost investment, supports configurability, and can quickly replicate and expand new sales collection business scenarios to meet the daily operation and management needs of the enterprise and reduce costs and increase efficiency.

[0078] Data model fusion: The present invention integrates multiple data models such as the sales collection data model (AR), profit unit model (Forgs), and financial data model (FL_AR) by constructing a sales and financial fusion model, thereby realizing unified management and analysis of data. This fusion enables financial data to be updated synchronously with sales data, thereby improving the real-time and accuracy of the data.

[0079] Automatic data conversion: Through automated data acquisition and conversion steps, the present invention can automatically classify and group the scattered sales payment data, match it with the profit unit, multi-channel payment conversion data set (AR_Tre), and multi-subject conversion data set (AR_Torg), and automatically generate the final integrated converted financial data set (FL_AR). This process reduces manual intervention, reduces the error rate, and improves data processing efficiency.

[0080] Dynamic business scenario support: The present invention supports flexible configuration of multiple business scenarios, such as retail revenue, funds and current accounting, etc. Through encapsulated programmatic logic and simple configuration, the system can quickly adapt to new business needs and market changes without large-scale system reconstruction.

[0081] Conversion relationship between payment channels and current settlement: The present invention establishes a conversion relationship between payment channels and current settlement, clarifies the financial accounting objects corresponding to each payment channel, solves the problem of fund current accounting for merchant numbers bound to specific payments, and supports the establishment of different fund collection entity business scenarios according to region and payment channel dimensions.

[0082] Mapping relationship between business regions and financial accounting entities in the time dimension: The present invention establishes a mapping relationship between business regions and financial accounting entities in the time dimension, so that the accounting scenario requirements of the income attribution entity will not be affected when the license is switched, thereby improving the accuracy and compliance of financial reports.

[0083] API interface integration: The present invention realizes rapid integration with the financial system by building an API interface, completes the integration of internal transaction documents with one click, integrates the financial system, completes document flow integration and financial accounting, and improves the system integration.

[0084] The present invention significantly reduces the workload of manual verification and accounting through automated data acquisition and conversion steps, and improves the efficiency of financial accounting; by establishing a conversion relationship between collection channels and current settlements, the accuracy and consistency of financial data are ensured, and human errors are reduced; and supports a configuration method for multiple business scenarios, so that the system can quickly adapt to new business needs and market changes without large-scale system reconstruction. Automatically generating a fused financial data set helps to quickly generate accurate financial reports, thereby improving the timeliness and reliability of financial reports. Automated financial accounting and integration reduces the investment of enterprises in data processing and management, thereby reducing operating costs. Accurate and timely data provision provides better decision support for management, helping enterprises to make faster and more accurate business decisions. Accurate financial data supports better data analysis and report generation, and provides more reliable information support for enterprise management. Through the support of mapping relationships and business scenarios, the transparency of business operations is improved, and the relationship between financial and business data is clearer. The automated integration steps accelerate the business processing flow, shorten the business cycle, and improve the response speed of the enterprise.

[0085] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A configurable solution for quickly realizing unmanned retail revenue transactions and financial integration, characterized by: The following steps are involved: Step S1: Building a sales and financial integration model: Building a sales and financial integration model, including establishing the conversion relationship between collection channels and current settlements, establishing the association relationship between various collection channels and fund settlement entities, establishing the mapping relationship between business regions and financial accounting entities in the time dimension, and supporting multiple business scenarios: Step S2: define the business data model: including the sales payment data model, profit unit model and financial data model, each model has a specific data dimension; Step S3: define the sales and finance integration model: including the multi-channel payment conversion model and the multi-subject conversion model, each model has a specific data dimension; Step S4: Automatically obtain and convert business data: by traversing the sales and retail payment collection data set, allocating and matching the profit unit data set, the multi-channel payment collection conversion data set, and the multi-subject conversion data set, to automatically generate the final integrated and converted financial data set; Step S5: Automated integration: By building an API interface, you can integrate internal transaction documents, integrate the financial system, and complete document flow integration and financial accounting with one click.

2. The configurable solution for rapidly realizing unmanned retail revenue transactions and financial integration according to claim 1 is characterized in that: In step S1, a conversion relationship between a payment collection channel and current settlement is established. There are multiple payment collection channels, and each payment collection channel needs to be clearly identified to a specific current settlement object for financial accounting. Establish the relationship between various payment channels and fund settlement entities to solve the problem of fund flow accounting when merchant numbers are bound to specific payment collections, and support the establishment of different fund collection entity business scenarios based on regions and payment channels; Establish a mapping relationship between business regions and financial accounting entities in the time dimension to adapt to the accounting scenario requirements where the license switch does not affect the income attribution entity; Supports multiple business scenarios to support retail revenue, funds and current accounting, and completes functional support through encapsulated programmatic logic and simple configuration.

3. The configurable solution for rapidly realizing unmanned retail revenue transactions and financial integration according to claim 1 is characterized in that: The data dimensions of the sales collection data model in step S2 include statistical month, sales collection date, business type, region, tax code, shelf type, actual collection in the current month, payment in the current month and refund in the current month, payment in previous months and refund in the current month.

4. The configurable solution for rapidly realizing unmanned retail revenue transactions and financial integration according to claim 3 is characterized in that: In step S2, the data dimensions of the profit unit model include business entity, profit center, cost center, region, and duration.

5. The configurable solution for rapidly realizing unmanned retail revenue transactions and financial integration according to claim 4 is characterized in that: In step S2, the financial data model includes financial accounting transaction objects, business entities, and payment entities.

6. The configurable solution for rapidly realizing unmanned retail revenue transactions and financial integration according to claim 1 is characterized in that: In step S3, the data dimensions of the multi-channel payment conversion model include sales payment channels, financial accounting transaction objects, whether the payment is from multiple entities, and the payment entity.

7. The configurable solution for rapidly realizing unmanned retail revenue transactions and financial integration according to claim 6 is characterized in that: In step S3, the data dimensions of the multi-subject conversion model include financial accounting transaction objects, business entities, and payment entities.

8. The configurable solution for rapidly realizing unmanned retail revenue transactions and financial integration according to claim 1 is characterized in that: The specific steps of automatically acquiring and converting business data in step S4 are as follows: Step S401: Classify and group sales payment data: traverse the sales retail payment data set and classify and group it according to the payment subject, time dimension, and dimension information; Step S402, converting business data: matching the classified and grouped data with the profit unit data set, the multi-channel payment conversion data set, and the multi-subject conversion data set to automatically generate the final integrated converted financial data set; Step S403, automatically generate internal transaction documents: through the sales and financial integration model, complete the conversion of regions in business data into financial accounting entities and cost centers and profit centers, and convert the collection channels into specific transaction objects; Step S404, finally generating the transactions between the income attribution entity and the fund collection entity to achieve the integration of income and finance.

9. The configurable solution for rapidly realizing unmanned retail revenue transactions and financial integration according to claim 8 is characterized in that: When the data matching condition is not met in step S402, a message reminder is pushed through the financial early warning assistant to help the enterprise discover and solve financial problems in a timely manner.

10. The configurable solution for rapidly realizing unmanned retail revenue transactions and financial integration according to claim 8, characterized in that: In step S401, the payment collection subject is divided into payment collection by the business subject and payment collection on behalf of the business subject; the time dimension is divided into current sales collection, past period collection, past period sales refund, and current sales refund.

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