Intelligent customer account checking system

Abstract

The invention relates to an intelligent customer reconciliation system which comprises the following steps: extracting data related to customer transaction from each data source, storing original data and forming a single data source; the account period automatic operation module automatically operates and generates account period information of the customer according to the customer information and a preset account period rule, and the account period information comprises an annual account period and a monthly account period; the automatic reconciliation processing module is used for automatically finishing the processing of reconciliation information of the client, including reconciliation information input, reconciliation information checking, difference analysis and result generation; and the initial balance management module is used for managing initial balance information of the customer. According to the invention, the system depends on an integrated platform to realize standardized processing and integration of data; according to the system, key function modules such as cost management, data analysis and statistics and the like are optimized by using automatic and intelligent technologies; in this way, the system can improve the efficiency and quality of enterprise decision making, and it is ensured that the decision is based on latest and most accurate data.

Description

Technical Field

[0001] The present invention relates to the technical field of financial data management, and specifically to an intelligent customer reconciliation system. Background Art

[0002] In the financial management of enterprises, customer reconciliation is a crucial link. Traditional customer reconciliation methods mainly rely on manual operations, including steps such as collecting customer transaction data, reconciling accounts, and adjusting differences. However, with the expansion of enterprise business scale and the increase in the number of customers, traditional reconciliation methods gradually expose problems such as low efficiency, error-proneness, and high costs.

[0003] First of all, traditional reconciliation methods require a large amount of human resources for data collection and reconciliation work, which not only increases the operating costs of enterprises but also may lead to an extension of the reconciliation cycle.

[0004] Secondly, it is inevitable to have negligence and errors in the manual reconciliation process, especially when dealing with a large amount of complex data, the risk of such errors will further increase.

[0005] Finally, traditional reconciliation methods are difficult to achieve real-time monitoring and tracking of the reconciliation process, and it is difficult to detect and solve problems in a timely manner once they occur.

[0006] In the reconciliation work, the following deficiencies need to be concerned and solved:

[0007] Data standardization and integration issues: There are differences in data formats and standards between different customers and enterprises. How to standardize and effectively integrate these data is a major challenge for intelligent customer reconciliation systems.

[0008] Optimization of algorithms and models: Intelligent customer reconciliation systems rely on advanced algorithms and models for data processing and analysis. However, with the development and changes of enterprise business, the original algorithms and models may not be able to meet new reconciliation requirements. Therefore, how to continuously optimize algorithms and models to improve their adaptability and accuracy is a key problem that the system needs to solve.

[0009] Intelligent customer reconciliation systems involve the processing and transmission of a large amount of sensitive data. How to ensure the security and stability of the system and prevent data leakage and illegal access is an important factor that must be considered in the system design and operation process.

[0010] The information disclosed in this background art section is only intended to deepen the understanding of the overall background art of the present invention, and should not be regarded as an admission or any form of implication that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0011] Aiming at the defects existing in the prior art, the purpose of the present invention is to provide an intelligent customer reconciliation system. The system relies on an integrated platform to achieve standardized processing and integration of data. The system uses automation and intelligent technologies to optimize key functional modules such as expense management, data analysis and statistics. In this way, the system can improve the efficiency and quality of enterprise decision-making and ensure that decisions are based on the latest and most accurate data.

[0012] To achieve the above purpose, the technical solution adopted by the present invention is:

[0013] An intelligent customer reconciliation system, characterized by comprising:

[0014] A data extraction module, which is used to extract data related to customer transactions from various data sources based on the Extract, Transform, Load (ETL) technology, perform format conversion, data cleaning and standardization processing to ensure the consistency and accuracy of the data;

[0015] The data sources include, for example, bank systems, sales systems, and logistics systems;

[0016] A data management platform, which is used to build a unified data warehouse based on the big data framework, store and manage the original data from the data extraction module to form a single data source;

[0017] An account period automatic calculation module, which automatically calculates and generates the account period information of customers according to customer information and preset account period rules, including annual account period and monthly account period, reducing errors and time costs of manual calculation;

[0018] An automatic reconciliation processing module, which automatically completes the processing of customer reconciliation information, including entry, verification, difference analysis and result generation of reconciliation information, improving the accuracy and efficiency of reconciliation;

[0019] An opening balance management module, which manages the opening balance information of customers, including rebate balance and cash balance, and supports import, query and update of balances.

[0020] On the basis of the above technical solution, in the data extraction process, a tagging process and a unique identification mechanism are introduced to assign a unique transaction identifier to each transaction data and add relevant tags for subsequent quick retrieval and processing;

[0021] The tags include: transaction type tag, transaction status tag, transaction object tag.

[0022] On the basis of the above technical solution, the data extraction module includes an Electronic Data Interchange (EDI) interface, which is used to receive real-time transmitted electronic data, reducing the time and errors of data entry;

[0023] The data extraction module includes an Optical Character Recognition (OCR) interface for receiving paper documents and converting them into electronic data for easy processing by the reconciliation software.

[0024] Based on the above technical solution, the customer sends the account period setting information from the remote end as needed, and the system maintains its basic information according to the customer input, including customer name, contract number, and settlement cycle.

[0025] The customer flexibly sets the account period rules in the system according to business needs, which by default include monthly settlement and quarterly settlement.

[0026] The system automatically calculates the account period for each customer based on the customer's settlement cycle and account period rules, and generates an account period report for subsequent reconciliation processing.

[0027] Based on the above technical solution, the automatic reconciliation processing module reads the customer transaction data and the enterprise's financial data from the data management platform and automatically enters the reconciliation information.

[0028] Automatically check the entered reconciliation information and compare the differences between the customer transaction data and the enterprise's financial data; the differences include: amount mismatch, transaction time inconsistency, and transaction type error.

[0029] For the discrepant data identified, the system automatically analyzes it, generates a discrepancy report, and provides suggestions on the reasons for the discrepancies and solutions.

[0030] The system automatically generates a reconciliation report based on the results of the check and discrepancy analysis for the financial personnel to review and confirm.

[0031] Based on the above technical solution, the automatic reconciliation processing module first determines the reconciliation objects and time range, and the reconciliation objects include bank accounts, customer accounts, and supplier accounts.

[0032] Successively compare and match the internal financial data with the external unit transaction records item by item. When the match is successful, generate a reconciliation node and record the data information of each successful match; when the match fails, generate a doubtful node and record the data information of each unsuccessful match.

[0033] The contents of the check include transaction object, transaction amount, transaction date, transaction item, payment method, and transaction status.

[0034] Based on the above technical solution, the automatic reconciliation processing module generates the following reconciliation reports according to the reconciliation results:

[0035] Bank reconciliation report, where the transaction records of the enterprise's bank account are reconciled with the bank statements provided by the bank.

[0036] Accounts receivable reconciliation report, where the enterprise's sales records are reconciled with the customer's payment records.

[0037] Accounts payable reconciliation report, which reconciles the enterprise's purchase records with the supplier's invoice records;

[0038] Inventory reconciliation report, which reconciles the enterprise's inventory records with the actual inventory quantity;

[0039] Financial statement reconciliation report, which reconciles the data between different financial statements, such as the balance sheet and the income statement;

[0040] Department account reconciliation report, which reconciles the financial transactions between different departments or projects within the enterprise. For example, for the expenses incurred when the R & D department provides products for the sales department, it is necessary to check whether the records of both parties are consistent.

[0041] Based on the above technical solution, the automatic reconciliation processing module analyzes all parties involved in the reconciliation and sends the reconciliation results to all parties for review. After all parties have passed the review, blockchain technology is used for evidence storage to avoid tampering, improving the transparency and trust of the reconciliation.

[0042] Based on the above technical solution, it further includes:

[0043] Virtual reconciliation module, which is used to verify the availability of the original data in a single data source, to test and verify the effectiveness of the reconciliation algorithm, to simulate and train the reconciliation operation, and to evaluate the accuracy and impact of the reconciliation results.

[0044] Based on the above technical solution, it further includes:

[0045] Document management pool, which is used to store the original documents that have been preliminarily reconciled and are correct;

[0046] After double-checking by the document submitter and the financial personnel, the original documents are stored in a single data source and recorded in the document management pool. The automatic reconciliation processing module preferentially processes the original documents recorded in the document management pool. For the original documents not in the document management pool, it is prompted that preliminary reconciliation is required.

[0047] An intelligent customer reconciliation system according to the present invention has the following beneficial effects:

[0048] 1. Data standardization and integration optimization:

[0049] Through the integrated platform, the system realizes the standardized processing and integration of data from different sources and formats, improves the availability and accuracy of the data, and reduces the errors and losses caused by inconsistent data.

[0050] Data integration helps to break information silos, realize cross-departmental and cross-system data sharing, and improve the overall operation efficiency.

[0051] 2. Automation and Intelligence Improve Efficiency:

[0052] The system applies automation and intelligence technologies, significantly improving the processing efficiency of key functional modules such as expense management, data analysis, and statistics. The automated processes reduce the need for manual operations and lower the risk of human errors.

[0053] The application of intelligence technologies enables the system to identify and process data more quickly and accurately, enhancing the overall response speed.

[0054] 3. Decision Support and Management Optimization:

[0055] Through comprehensive data analysis and statistics functions, the system provides decision support for enterprises based on the latest and most accurate data. This helps enterprises better understand market trends, customer needs, and internal operation conditions, thus making more informed decisions.

[0056] The intelligent decision support function enables enterprises to adapt to market changes more quickly, optimize resource allocation, and enhance competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The present invention has the following drawings:

[0058] The drawings are used to better understand the present invention and do not constitute an improper limitation to the present invention. Among them:

[0059] Figure 1 System architecture diagram of the first embodiment of the intelligent customer reconciliation system described in the present invention.

[0060] Figure 2 System architecture diagram of the second embodiment of the intelligent customer reconciliation system described in the present invention.

[0061] Figure 3 System architecture diagram of the third embodiment of the intelligent customer reconciliation system described in the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0062] The following further describes the present invention in detail with reference to the drawings. The detailed description is made in connection with the exemplary embodiments of the present invention, including various details of the embodiments of the present invention to facilitate understanding, which should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted below.

[0063] As Figure 1 shown, the intelligent customer reconciliation system described in the present invention includes:

[0064] A data extraction module, which is used to extract data related to customer transactions from various data sources based on the ETL (Extract, Transform, Load) technology, perform format conversion, data cleaning, and standardization processing to ensure the consistency and accuracy of the data;

[0065] The data sources include, for example, bank systems, sales systems, and logistics systems;

[0066] Through the ETL technology, the system can automatically extract data related to customer transactions from multiple data sources such as bank systems, sales systems, and logistics systems, ensuring the comprehensiveness and timeliness of the data. At the same time, it reduces manual intervention and improves the efficiency of data extraction;

[0067] A data management platform, which is used to build a unified data warehouse based on a big data framework, store and manage the raw data from the data extraction module, and form a single data source;

[0068] Through the construction of the data warehouse, the system realizes the centralized management and unified view of the data, avoids the problems of data islands and data inconsistency, enables the system to easily cope with the storage and management requirements of massive data, and at the same time ensures the integrity and security of the data;

[0069] An account period automatic calculation module, which automatically calculates and generates the account period information of customers according to customer information and preset account period rules, including annual account periods and monthly account periods, reducing errors and time costs of manual calculation;

[0070] The system can automatically calculate and generate the account period information of customers according to customer information and preset account period rules, including annual account periods and monthly account periods, reducing errors and time costs of manual calculation, and improving the accuracy and efficiency of account period management;

[0071] An automatic reconciliation processing module, which automatically completes the processing of customer reconciliation information, including the entry, verification, discrepancy analysis, and result generation of reconciliation information, improving the accuracy and efficiency of reconciliation;

[0072] The system can automatically complete the processing of customer reconciliation information, including the entry, verification, discrepancy analysis, and result generation of reconciliation information. The system can analyze the discrepant data identified during verification, generate a discrepancy report, and provide suggestions on the reasons for the discrepancies and solutions, improving the accuracy and efficiency of reconciliation, helping customers to promptly discover problems and take corresponding measures, and reducing the reconciliation risk;

[0073] An opening balance management module, which manages the opening balance information of customers, including rebate balances and cash balances, and supports the import, query, and update of balances;

[0074] The system can manage the opening balance information of customers, including rebate balance and cash balance, which helps customers comprehensively understand their financial status, provides a basis for subsequent reconciliation and settlement, and enables customers to conveniently manage and track their opening balance information.

[0075] On the basis of the above technical solution, during the data extraction process, a tagging process and a unique identification mechanism are introduced. A unique transaction identifier is assigned to each transaction data, and relevant tags are added to facilitate subsequent rapid retrieval and processing.

[0076] The tags include: transaction type tag, transaction status tag, transaction object tag.

[0077] In this embodiment, by assigning a unique transaction identifier to each transaction data, the system can quickly locate specific transaction records without having to screen through massive amounts of data one by one, greatly improving the speed and efficiency of data retrieval.

[0078] The tagging process enables the system to classify and aggregate data according to tags. For example, a certain type of transaction data can be quickly filtered out according to the transaction type tag for further analysis and processing, which helps the system process and analyze data more efficiently.

[0079] During the data extraction process, by assigning a unique identifier to each data, the generation of duplicate data can be avoided; at the same time, the addition of tags can also help the system more accurately identify and classify data, reducing the possibility of data errors.

[0080] During the reconciliation process, the system can quickly find relevant transaction data according to tags for comparison and analysis; the tagging process can also make the reconciliation result clearer and easier to understand, facilitating customer understanding and confirmation.

[0081] On the basis of the above technical solution, the data extraction module includes an Electronic Data Interchange (EDI) interface for receiving real-time transmitted electronic data, reducing the time and errors of data entry.

[0082] The data extraction module includes an Optical Character Recognition (OCR) interface for receiving paper documents and converting them into electronic data for easy processing by the reconciliation software.

[0083] Through the EDI interface, the system can receive electronic data from various data sources (such as bank systems, sales systems, logistics systems, etc.) in real time, reducing the time and errors of data entry because the data is directly transmitted between systems without manual intervention; at the same time, the receipt of real-time data also enables the system to more timely reflect the business situation and improve the timeliness of decision-making.

[0084] The OCR interface enables the system to receive and process paper documents, converting them into electronic data, which is particularly important for enterprises that still rely on paper documents for business operations. Through OCR technology, the system can automatically recognize the text and numerical information on the documents and convert it into an electronic format that can be processed by the reconciliation software, not only reducing the workload of manual entry but also improving the accuracy and efficiency of data processing.

[0085] Based on the above technical solution, the customer sends the account period setting information from the remote end, and the system maintains its basic information according to the customer input, including customer name, contract number, and settlement cycle.

[0086] The customer can flexibly set the account period rules in the system according to business needs, which by default include monthly settlement and quarterly settlement.

[0087] The system automatically calculates the account period for each customer according to the customer's settlement cycle and account period rules and generates an account period report for subsequent reconciliation processing.

[0088] In this implementation, through the introduction of the remote end, the customer can flexibly set the account period rules in the system according to their own business needs, such as monthly settlement, quarterly settlement, etc., meeting the personalized needs of different customers and enhancing the customer experience.

[0089] The system automatically calculates the account period according to the customer's settlement cycle and account period rules, which greatly reduces the cumbersome process and errors of manual reconciliation.

[0090] The account period setting information sent by the customer from the remote end is uniformly managed and maintained by the system, avoiding the problems of duplicate data entry and incorrect input.

[0091] The system automatically calculates the account period and generates a report, reducing human intervention and enhancing the consistency and accuracy of the data.

[0092] Based on the above technical solution, the automatic reconciliation processing module reads the customer transaction data and the enterprise's financial data from the data management platform and automatically enters the reconciliation information.

[0093] Automatically check the entered reconciliation information and compare the differences between the customer transaction data and the enterprise financial data; the differences include: amount mismatch, transaction time inconsistency, and transaction type error.

[0094] For the identified difference data, the system automatically analyzes it, generates a difference report, and provides suggestions on the reasons for the differences and solutions.

[0095] The system automatically generates a reconciliation report based on the results of the check and difference analysis for the financial personnel to review and confirm.

[0096] In this embodiment, the automatic reconciliation processing module can automatically complete the processes of inputting, verifying, and analyzing reconciliation information, greatly reducing the workload of manual reconciliation and improving the reconciliation efficiency. The system can automatically compare the differences between customer transaction data and enterprise financial data and generate a difference report, so the accuracy of reconciliation has also been significantly improved. For example: through the automatic verification of reconciliation information, the system can timely detect differences such as inconsistent amounts, inconsistent transaction times, and incorrect transaction types, and generate a difference report. Based on this, financial personnel can timely discover and correct errors, reducing the financial risks brought by reconciliation errors.

[0097] Based on the above technical solution, the automatic reconciliation processing module first determines the reconciliation objects and time range. The reconciliation objects include bank accounts, customer accounts, and supplier accounts.

[0098] The internal financial data and external unit transaction records are sequentially compared and matched item by item. When the match is successful, a reconciliation node is generated, and the data information of each successful match is recorded. When the match fails, a doubtful node is generated, and the data information of each unsuccessful match is recorded.

[0099] The contents of the verification include transaction objects, transaction amounts, transaction dates, transaction items, payment methods, and transaction statuses.

[0100] In this embodiment, by clarifying the reconciliation objects and time range, the automatic reconciliation processing module can perform data verification more pertinently, avoiding the interference of invalid data, thereby improving the accuracy of reconciliation. The method of item-by-item verification and matching can ensure that each transaction is accurately verified, further improving the accuracy of reconciliation. The automated processing reduces the need for manual operations and significantly improves the reconciliation efficiency.

[0101] The reconciliation process involves the verification of multiple dimensions such as transaction objects, transaction amounts, transaction dates, transaction items, payment methods, and transaction statuses, which helps to comprehensively verify the authenticity and accuracy of financial data. When data inconsistencies are found, the system can generate a doubtful node and record the relevant information, which provides clues for the enterprise to trace and investigate the root causes of problems, enhancing the reliability and transparency of financial data.

[0102] Based on the above technical solution, the automatic reconciliation processing module generates the following reconciliation reports according to the reconciliation results:

[0103] Bank reconciliation report, where the transaction records of the enterprise's bank account are reconciled with the bank statements provided by the bank;

[0104] Accounts receivable reconciliation report, where the enterprise's sales records are reconciled with the customer's payment records;

[0105] Accounts payable reconciliation report, where the enterprise's purchase records are reconciled with the supplier's invoice records;

[0106] Inventory reconciliation report, which reconciles the enterprise's inventory records with the actual inventory quantity;

[0107] Financial statement reconciliation report, which reconciles the data between different financial statements, such as the balance sheet and the income statement;

[0108] Department account reconciliation report, which reconciles the financial transactions between different departments or projects within the enterprise. For example, for the expenses incurred when the R & D department provides products for the sales department, it is necessary to check whether the records of both parties are consistent.

[0109] Based on the above technical solution, the automatic reconciliation processing module analyzes all parties involved in the reconciliation and sends the reconciliation results to all parties for review. After all parties have passed the review, blockchain technology is used for evidence storage to avoid tampering and improve the transparency and trust of the reconciliation.

[0110] Two-party reconciliation is the most common reconciliation method, usually occurring between two entities, such as between an enterprise and a bank, an enterprise and a supplier, and an enterprise and a customer. The main thing checked in two-party reconciliation is the transaction records between the two parties to ensure that the accounts of both parties are consistent.

[0111] In some complex transaction scenarios, the reconciliation of accounts may involve multiple entities, which is multi-party reconciliation. For example, in scenarios involving cross-bank transfers, multi-party transactions, or supply chain finance, multiple banks, enterprises, customers, etc. may need to participate in the reconciliation together.

[0112] Based on the above technical solution, as Figure 2 shown, it further includes:

[0113] Virtual reconciliation module, which is used to verify the availability of the original data in a single data source, to test and verify the effectiveness of the reconciliation algorithm, to simulate and train the reconciliation operation, and to evaluate the accuracy and impact consequences of the reconciliation results.

[0114] The virtual reconciliation module is first used to verify the availability of the original data in a single data source. During the data extraction and integration process, due to various reasons (such as data source failures, network delays, data format problems, etc.), the original data may have problems such as being incomplete, inaccurate, or having inconsistent formats. By verifying this original data, the accuracy and reliability of subsequent reconciliation operations can be ensured.

[0115] The virtual reconciliation module is also used to test and verify the effectiveness of the reconciliation algorithm. In actual applications, the reconciliation algorithm may be affected by various factors, such as the data volume, data type, data distribution, etc. Through the virtual reconciliation module, these algorithms can be fully tested and verified without interfering with the actual business, ensuring that they can accurately and efficiently handle various reconciliation tasks.

[0116] For reconciliation operators, the virtual reconciliation module provides a simulation training platform. By performing simulated reconciliation operations on this platform, operators can become familiar with the reconciliation process, master reconciliation skills, and improve reconciliation efficiency. This simulated training not only helps improve the skill level of operators but also reduces the error rate in actual operations.

[0117] The virtual reconciliation module is also used to evaluate the accuracy and impact consequences of reconciliation results. By comparing the virtual reconciliation results with the expected results, potential problems and deviations in the reconciliation process can be promptly discovered and analyzed in depth. This helps the enterprise better understand the impact of reconciliation operations and provides a basis for subsequent decision-making and optimization.

[0118] After introducing the virtual reconciliation module, the reliability and stability of the entire reconciliation system have been significantly improved. Through the verification, testing, training, and evaluation functions of the virtual reconciliation module, potential problems in the system can be promptly discovered and repaired, ensuring that the system can operate stably and accurately process various reconciliation tasks in actual applications.

[0119] Based on the above technical solutions, as Figure 3 shown, it further includes:

[0120] A document management pool for storing original documents that have been preliminarily checked and are correct.

[0121] After double-checking by the document submitter and the financial staff, the original documents are stored in a single data source and recorded in the document management pool. The automatic reconciliation processing module preferentially processes the original documents recorded in the document management pool. For the original documents not in the document management pool, it is prompted that preliminary checking is required.

[0122] The document management pool is a system area for storing original documents that have been preliminarily checked and are correct. As a temporary storage area, it ensures that all correct documents are safely stored until they are finally processed or archived. According to the progress of the reconciliation business process, the original documents in the document management pool are assigned corresponding labels to indicate which departments or personnel have verified or processed the original documents.

[0123] Exemplarily, before the original documents are stored in the document management pool, the system automatically performs a series of verification checks, such as format checks, signature verifications, and logical consistency verifications. For the documents that fail the verification, the system automatically marks them as abnormal and transfers them to the exception handling queue for further manual review.

[0124] Exemplarily, a status label such as "checked", "pending processing", "archived", "reconciled", "approved", or "voided" is assigned to each document in the document management pool to track the processing progress of the documents.

[0125] The content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0126] The above is only the preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiment. Any equivalent modification or change made by those skilled in the art according to the disclosure of the present invention shall be included in the protection scope recorded in the claims.

Claims

1. An intelligent customer reconciliation system, characterized in that: include: Data extraction module, which is used to extract data related to customer transactions from various data sources based on the extraction, transformation and loading (ETL) technology, perform format conversion, data cleaning and standardization to ensure data consistency and accuracy; The data sources include banking systems, sales systems, and logistics systems; Data management platform, which is used to build a unified data warehouse based on the big data framework, store and manage the original data from the data extraction module, and form a single data source; The automatic payment period calculation module automatically calculates and generates the customer's payment period information, including annual payment period and monthly payment period, based on the customer information and preset payment period rules, thus reducing the errors and time costs of manual calculation; The automatic reconciliation processing module automatically completes the processing of customer reconciliation information, including the entry, verification, difference analysis and result generation of reconciliation information, improving the accuracy and efficiency of reconciliation; The opening balance management module manages the customer's opening balance information, including rebate balance and cash balance, and supports the import, query and update of balances.

2. An intelligent customer reconciliation system as claimed in claim 1, characterized in that: During the data extraction process, a labeling and unique identification mechanism is introduced to assign a unique transaction ID to each transaction data and add relevant tags to facilitate subsequent rapid retrieval and processing; The labels include: transaction type label, transaction status label, and transaction object label.

3. The intelligent customer reconciliation system according to claim 1, characterized in that: The data extraction module includes an EDI interface for receiving electronic data transmitted in real time, reducing the time and errors of data entry; The data extraction module includes an optical character recognition (OCR) interface for receiving paper documents and converting them into electronic data for easy processing by the reconciliation software.

4. The intelligent customer reconciliation system according to claim 1, characterized in that: The customer sends the billing period setting information from the remote end as needed, and the system maintains the basic information according to the customer's input, including customer name, contract number, and settlement period; Customers can flexibly set payment period rules in the system according to business needs, including monthly settlement and quarterly settlement by default; The system automatically calculates each customer's billing period based on the customer's settlement cycle and billing period rules, and generates a billing period report for subsequent reconciliation processing.

5. The intelligent customer reconciliation system according to claim 1, characterized in that: The automatic reconciliation processing module reads customer transaction data and corporate financial data from the data management platform and automatically enters reconciliation information; Automatically check the entered reconciliation information to compare the differences between customer transaction data and corporate financial data; the differences include: inconsistent amounts, inconsistent transaction times, and incorrect transaction types; For the verified discrepancy data, the system automatically analyzes it, generates a discrepancy report, and provides suggestions on the causes of the discrepancy and solutions; Based on the results of verification and variance analysis, the system automatically generates a reconciliation report for review and confirmation by financial personnel.

6. The intelligent customer reconciliation system according to claim 1, characterized in that: The automatic reconciliation processing module first determines the reconciliation object and time range, and the reconciliation object includes bank accounts, customer accounts, and supplier accounts; The internal financial data and the transaction records of external units are checked and matched one by one in sequence. When the match is successful, a reconciliation node is generated and the data information of the successful match is recorded; when the match fails, a questionable node is generated and the data information of the unsuccessful match is recorded; The verification contents include transaction object, transaction amount, transaction date, transaction item, payment method and transaction status.

7. An intelligent customer reconciliation system as claimed in claim 1, characterized in that: The automatic reconciliation processing module generates the following reconciliation report based on the reconciliation results: Bank reconciliation report, which verifies the transaction records of the corporate bank account with the bank statement; Accounts receivable reconciliation report, which checks the company's sales records with the customer's payment records; Accounts payable reconciliation report, which checks the company's purchase records with the supplier's invoice records; Inventory reconciliation report, which verifies the company's inventory records with the actual inventory quantity; Financial statement reconciliation reports, which check the data between different financial statements, such as the balance sheet and income statement; Department account reconciliation report is used to check the financial transactions between different departments or projects within the enterprise. For example, the expenses incurred by the R&D department for providing products to the sales department need to be checked to see if the records of both parties are consistent.

8. An intelligent customer reconciliation system as claimed in claim 1, characterized in that: The automatic reconciliation processing module analyzes the parties involved in the reconciliation and sends the reconciliation results to all parties for review. After all parties have reviewed and approved them, blockchain technology is used to store evidence to avoid tampering, thereby improving the transparency and trust of the reconciliation.

9. The intelligent customer reconciliation system according to claim 1, characterized in that: Also includes: The virtual reconciliation module is used to verify the availability of original data in a single data source, to test and verify the effectiveness of the reconciliation algorithm, to simulate the training of reconciliation operations, and to evaluate the accuracy of reconciliation results and their consequences.

10. An intelligent customer account reconciliation system as claimed in claim 1, characterized in that: Also includes: The document management pool is used to store original documents that have been preliminarily checked and are correct; After double checking by the price submitter and the financial staff, the original document is stored in a single data source and filed in the document management pool. The automatic reconciliation processing module gives priority to processing the original documents filed in the document management pool. For original documents that are not in the document management pool, it is prompted that a preliminary check is required.

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