Customized reconciliation method and device for adaptive data structure, equipment and medium

Abstract

The invention relates to an information reconciliation technology, and discloses a customized reconciliation method and device of a self-adaptive data structure, equipment and a storage medium. The method comprises the following steps: performing keyword extraction operation on a to-be-reconciliated task selected by a user to obtain a data demand keyword set and a rule demand keyword set; a to-be-reconciliated data set is called according to the data demand keyword set by using a pre-constructed reconciliation basic data configuration service; according to the rule demand keyword set, configuring an account checking rule, and according to the account checking rule, carrying out direct connection account checking on the data set to be subjected to account checking to obtain a direct connection account checking result; and when the direct connection reconciliation result shows that reconciliation fails, sending the reconciliation task and the direct connection reconciliation result to a pre-constructed manual reconciliation interface. According to the invention, the automation degree, accuracy and efficiency of account checking can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of information reconciliation, and in particular to a customized reconciliation method, device, equipment and computer-readable storage medium with an adaptive data structure. Background Art

[0002] In today's finance, e-commerce, supply chain management and other fields, reconciliation activities are an important part of ensuring transaction accuracy, financial transparency and compliance. Traditional reconciliation methods often rely on fixed data structures and preset reconciliation rules, which are more efficient when processing standardized transactions and data. However, with the complexity of business processes and the diversification of data sources, traditional methods are facing more and more significant challenges. For example, different systems and platforms may use different data structures to store and manage transaction data, which makes collecting and collating data from various data sources a challenging task; in addition, with the diversification of transaction types and business models, the rules that need to be applied to the reconciliation process have become increasingly complex, which requires the reconciliation system to be able to flexibly adapt to changing reconciliation needs; the reconciliation process with a low degree of automation is not only time-consuming, but also prone to errors, affecting the efficiency and accuracy of reconciliation.

[0003] Given these issues, existing reconciliation methods show limitations in handling rapidly changing business needs, coping with the diversity of data structures and the complexity of rules. Summary of the invention

[0004] The present invention provides a customized reconciliation method, device, equipment and storage medium with an adaptive data structure, the main purpose of which is to provide a method that can adapt to different data structures and flexibly configure reconciliation rules to improve the automation, accuracy and efficiency of reconciliation.

[0005] To achieve the above-mentioned purpose, the present invention provides a customized reconciliation method with an adaptive data structure, comprising:

[0006] Perform keyword extraction operations on the tasks to be reconciled selected by the user to obtain a data requirement keyword set and a rule requirement keyword set;

[0007] Using the pre-built reconciliation basic data configuration service, retrieve the data set to be reconciled according to the data requirement keyword set;

[0008] According to the rule requirement keyword set, a reconciliation rule is configured, and the to-be-reconciled data set is directly reconciled according to the reconciliation rule to obtain a direct reconciliation result;

[0009] When the direct connection reconciliation result is a reconciliation failure, the reconciliation task and the direct connection reconciliation result are sent to a pre-built manual reconciliation interface.

[0010] Optionally, the using of the pre-built reconciliation basic data configuration service to retrieve the to-be-reconciled data set according to the data requirement keyword set includes:

[0011] Using the reconciliation basic data configuration service, identifying the enterprise type and the reconciliation enterprise in the data demand keyword set, and acquiring the data source of the to-be-reconciled task according to the enterprise type, the data source including the accounts payable data source and the financing data source;

[0012] According to the enterprise type and data source, query the data of the reconciliation enterprise to obtain basic reconciliation data;

[0013] Select the reconciliation scope based on the type of data source;

[0014] Retrieving maintenance status mapping data according to the reconciliation scope and data source;

[0015] The data satisfying the basic reconciliation data, the reconciliation scope and the maintenance status mapping data are retrieved to obtain a set of data to be reconciled.

[0016] Optionally, performing data query on the reconciliation enterprise according to the enterprise type and data source to obtain basic reconciliation data includes:

[0017] When the enterprise type is a preset core enterprise, the core type data of the reconciliation enterprise in the accounts payable data source and the financing data source are called as basic reconciliation data;

[0018] When the enterprise type is a preset funding party, the funding party type data of the reconciliation enterprise in the financing data source is called as the basic reconciliation data.

[0019] Optionally, selecting a reconciliation scope according to the type of the data source includes:

[0020] When the data source is the accounts payable data, obtaining a preset reconciliation range of undisbursed loans and disbursed but unsettled loans;

[0021] When the data source is the financing data, the reconciliation scope of the disbursed but unsettled loans is obtained.

[0022] Optionally, the retrieving maintenance status mapping data according to the reconciliation scope and the data source includes:

[0023] When the data source is the accounts payable data;

[0024] If the reconciliation scope is the unsettled loan, retrieve the preset maintenance status mapping data of payables-financed-loans and payables-invoiced-loans;

[0025] If the reconciliation scope is the undisbursed funds, retrieve the preset maintenance status mapping data of payables-unused, payables-financing, payables-billing, payables-billed-undisbursed and payables-invalidated;

[0026] When the data source is financing data;

[0027] If the reconciliation scope is the unsettled loan, retrieve the preset financing-loan maintenance status mapping data.

[0028] Optionally, configuring the reconciliation rule according to the rule requirement keyword set includes:

[0029] Performing a semantic recognition operation on the rule requirement keyword set to obtain a semantic feature set;

[0030] Performing a correlation identification operation based on a preset reconciliation rule set on the semantic feature set to obtain a correlation score corresponding to each preset reconciliation rule in the preset reconciliation rule set;

[0031] Preset reconciliation rules whose relevance scores are greater than a preset matching threshold are extracted from the preset reconciliation rule set to obtain configured reconciliation rules.

[0032] Optionally, the keyword extraction operation is performed on the to-be-reconciled task selected by the user to obtain a data requirement keyword set and a rule requirement keyword set, including:

[0033] Performing word segmentation processing on the pending reconciliation tasks to obtain a word segmentation set;

[0034] Performing a sequential quantization encoding operation on the word segmentation set to obtain a word segmentation vector set;

[0035] Performing a context-based text semantic feature extraction operation on the word segmentation vector set to obtain a word segmentation feature sequence;

[0036] A binary keyword extraction operation based on data and demand is performed on the word segmentation feature sequence to obtain a data demand keyword set and a rule demand keyword set.

[0037] In order to solve the above problems, the present invention further provides a customized reconciliation device with an adaptive data structure, the device comprising:

[0038] The reconciliation requirement extraction module is used to extract keywords from the reconciliation tasks selected by the user to obtain a data requirement keyword set and a rule requirement keyword set;

[0039] A module for reconciliation data retrieval, used to retrieve the reconciliation data set according to the data requirement keyword set by using the pre-built reconciliation basic data configuration service;

[0040] A direct reconciliation module, configured to configure a reconciliation rule according to the rule requirement keyword set, and perform direct reconciliation on the to-be-reconciled data set according to the reconciliation rule to obtain a direct reconciliation result;

[0041] The manual reconciliation module is used to send the reconciliation task and the direct reconciliation result to a pre-built manual reconciliation interface when the direct reconciliation result is a reconciliation failure.

[0042] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0043] at least one processor; and,

[0044] a memory communicatively connected to the at least one processor; wherein,

[0045] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the customized reconciliation method of the adaptive data structure described above.

[0046] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored. The at least one computer program is executed by a processor in an electronic device to implement the customized reconciliation method of the adaptive data structure described above.

[0047] The present invention extracts keywords from reconciliation tasks to identify data requirement keywords and rule requirement keywords, and realizes flexible configuration of data structure and reconciliation rules through pre-built reconciliation basic data configuration services, which can well adapt to the diversified development of business structure; in addition, users only need to select or construct reconciliation tasks to complete reconciliation operations without excessive manual configuration, thereby improving the automation efficiency of customized reconciliation. Therefore, the customized reconciliation method, device, equipment and storage medium with adaptive data structure provided by the embodiments of the present invention can provide a method that can adapt to different data structures and flexibly configure reconciliation rules to improve the automation, accuracy and efficiency of reconciliation. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A schematic diagram of a process flow of a customized reconciliation method with an adaptive data structure provided by an embodiment of the present invention;

[0049] Figure 2 A detailed flowchart of a step in a customized reconciliation method of an adaptive data structure provided by an embodiment of the present invention;

[0050] Figure 3A functional module diagram of a customized account reconciliation device with an adaptive data structure provided by an embodiment of the present invention;

[0051] Figure 4 A schematic diagram of the structure of an electronic device for implementing the customized reconciliation method of the adaptive data structure provided in one embodiment of the present invention.

[0052] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0054] The embodiment of the present application provides a customized reconciliation method for an adaptive data structure. In the embodiment of the present application, the execution subject of the customized reconciliation method for the adaptive data structure includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the customized reconciliation method for the adaptive data structure can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0055] Reference Figure 1 FIG. 1 is a flow chart of a customized reconciliation method for an adaptive data structure provided by an embodiment of the present invention. In this embodiment, the customized reconciliation method for an adaptive data structure includes:

[0056] S1. Perform keyword extraction operation on the to-be-reconciled task selected by the user to obtain a data requirement keyword set and a rule requirement keyword set.

[0057] The reconciliation refers to a process aimed at verifying and confirming the consistency and accuracy between two sets of records or accounts. In embodiments of the present invention, it usually involves comparing internal records with data from external sources, such as bank statements, supplier bills, or customer accounts, to ensure that the data on both sides matches and is correct.

[0058] The to-be-reconciled task in the embodiment of the present invention may be a historically constructed phased reconciliation task, or may be a newly constructed customized reconciliation task.

[0059] In detail, in the embodiment of the present invention, the keyword extraction operation is performed on the task to be reconciled selected by the user to obtain a data requirement keyword set and a rule requirement keyword set, including:

[0060] Performing word segmentation processing on the pending reconciliation tasks to obtain a word segmentation set;

[0061] Performing a sequential quantization encoding operation on the word segmentation set to obtain a word segmentation vector set;

[0062] Performing a context-based text semantic feature extraction operation on the word segmentation vector set to obtain a word segmentation feature sequence;

[0063] A binary keyword extraction operation based on data and demand is performed on the word segmentation feature sequence to obtain a data demand keyword set and a rule demand keyword set.

[0064] In the embodiment of the present invention, a natural language processing method is used to segment the reconciliation task, and then a one-hot model is used to perform a quantization encoding operation on the segmentation set, and the sequential features between the segmentations are spliced ​​to obtain a segmentation feature sequence; then a Bert network is used to perform a feature extraction operation for contextual attention feature enhancement to obtain a segmentation feature sequence, and finally a pre-constructed binary classification network is used to perform a binary classification keyword extraction operation based on data and requirements on the segmentation feature sequence to obtain a data requirement keyword set and a rule requirement keyword set.

[0065] Specifically, the data requirement keyword set described in the present invention may include: account information [account holder's name; account number; account type (savings account, checking account, etc.)], transaction records [transaction date and time; transaction amount; transaction type (deposit, withdrawal, transfer, etc.); counterparty account information (if applicable)], beginning and ending balances [account balance at the beginning of the reconciliation cycle; account balance at the end of the reconciliation cycle], etc.

[0066] The keyword set of rule requirements may include: transaction matching rules [ensure that each transaction recorded internally has a corresponding record in the bank statement, and vice versa; transaction date, amount, type and other details must be consistent], balance verification rules [account balances at the beginning and end of the reconciliation cycle must match bank records], abnormal transaction processing rules [transactions that do not appear in the bank statement must be marked as pending verification, and a quick query and resolution mechanism must be provided; transactions with mismatched amounts, dates, etc. must also be marked and details provided for further review], etc.

[0067] S2. Using the pre-built reconciliation basic data configuration service, according to the data requirement keyword set, retrieve the to-be-reconciled data set.

[0068] In the embodiment of the present invention, the reconciliation basic data configuration service is a core configuration service in the reconciliation system, which is responsible for defining the mapping relationship between the reconciliation content and data. Whether it is a direct reconciliation or a manual reconciliation module, when executing the reconciliation operation, reconciliation will be performed according to the settings in this configuration service.

[0069] The reconciliation basic data configuration service includes the definition of the data items required for comparison in the reconciliation task, the data sources, and the mapping relationship between data from different sources; including the key fields for reconciliation, the frequency of reconciliation, the information of the two or more parties involved in the reconciliation, the data formatting rules, the data mapping rules, etc.; and also includes the configuration of rules on how to correspond the data items in one system or module with the data items in another system or module to ensure that the data can be correctly compared. For example, the "customer ID" in one system may be called the "account number" in another system.

[0070] For details, refer to Figure 2 As shown, in the embodiment of the present invention, the pre-built reconciliation basic data configuration service is used to retrieve the to-be-reconciled data set according to the data requirement keyword set, including:

[0071] S21. Utilize the reconciliation basic data configuration service to identify the enterprise type and reconciliation enterprise in the data requirement keyword set, and obtain the data source of the to-be-reconciled task according to the enterprise type, wherein the data source includes an accounts payable data source and a financing data source.

[0072] The data source in the embodiment of the present invention includes an accounts payable data source and a financing data source.

[0073] When the enterprise type is a core enterprise, the configurable data sources are accounts payable data and financing data; when the enterprise type is a funding party, the data source can only be financing data.

[0074] S22. According to the enterprise type and data source, data query is performed on the reconciliation enterprise to obtain basic reconciliation data.

[0075] In detail, in the embodiment of the present invention, the data query of the reconciliation enterprise is performed according to the enterprise type and the data source to obtain the basic reconciliation data, including:

[0076] When the enterprise type is a preset core enterprise, the core type data of the reconciliation enterprise in the accounts payable data source and the financing data source are called as the basic reconciliation data; when the enterprise type is a preset funding party, the funding party type data of the reconciliation enterprise in the financing data source is called as the basic reconciliation data.

[0077] S23. Select a reconciliation scope according to the type of the data source.

[0078] In detail, in the embodiment of the present invention, selecting the reconciliation scope according to the type of the data source includes:

[0079] When the data source is the accounts payable data, the preset reconciliation range of undisbursed loans and disbursed but unsettled loans is obtained; when the data source is the financing data, the reconciliation range of disbursed but unsettled loans is obtained.

[0080] Specifically, when "Financing Data" is selected for [Data Source], since the financing data only notifies the core enterprise ERP to change its status during the loan and repayment stages, it is meaningless to compare it with other process statuses, so [Reconciliation Scope] can only select "Loans Disbursed but Not Settled" data.

[0081] S24. Retrieve maintenance status mapping data according to the reconciliation scope and data source.

[0082] In detail, in the embodiment of the present invention, the step of retrieving maintenance status mapping data according to the reconciliation scope and the data source includes:

[0083] When the data source is the accounts payable data; if the reconciliation scope is the accounts payable that have been disbursed but not settled, retrieve the preset accounts payable-financed-disbursed and accounts payable-invoiced-disbursed maintenance status mapping data; if the reconciliation scope is the undisbursed, retrieve the preset accounts payable-unused, accounts payable-financing, accounts payable-invoicing, accounts payable-invoiced-undisbursed and accounts payable-invalidated maintenance status mapping data;

[0084] When the data source is financing data; if the reconciliation scope is the unsettled loans, retrieve the preset financing-loan maintenance status mapping data.

[0085] The present invention realizes the linkage effect of the reconciliation scope on the maintenance status mapping according to the above configuration.

[0086] S25. Retrieve data that meets the basic reconciliation data, reconciliation scope, and maintenance status mapping data to obtain a set of data to be reconciled.

[0087] According to the above process, the embodiment of the present invention utilizes the reconciliation basic data configuration service to retrieve the set of data to be reconciled.

[0088] In addition, in the embodiment of the present invention, the platform reconciliation status is defined as follows:

[0089] Payable-Unused: This account payable has not been used for financing transactions or billing transactions or is not in the process of these two transactions; Value: Accounts payable status = Unused accounts payable data;

[0090] Payables - Financing: This account payable has been financed, but the financing transaction has not been disbursed; Value: Accounts payable status = Accounts payable data in financing;

[0091] Payables - Funded - Disbursed / Repaid: This account payable has been financed, and the financing status is Disbursed, and the repayment status is To be Repaid / Repaid; Value: Accounts Payable Status = Funded, and the financing transaction status associated with this account payable = Disbursed, and the repayment status = Accounts Payable Data Not Yet Repaid / Repaid;

[0092] Accounts payable - billing in progress: The accounts payable is in billing progress, and the billing status is billing progress, waiting for receipt; Value: Accounts payable status = accounts payable data in billing progress;

[0093] Accounts payable - Invoiced - Not released: The invoice for this accounts payable has been issued, but no financing transaction has been initiated; Value: Accounts payable status = Invoiced; and Document status = Waiting for receipt; or Document status = Voiding; or Document status = Financing; or Document status = Normal holding, Document status = Liquidation, and the holder is a supplier, and no financing transaction has been initiated under this accounts payable, or there is a financing transaction, but the financing transaction status is financing, waiting for release, or rejected accounts payable data.

[0094] Accounts payable - Invoiced - Loaned / Repaid: The account payable has completed invoicing and a financing transaction has been initiated. The financing status is Loaned and the repayment status is Unpaid / Repaid. Values: Accounts payable data with Accounts payable status = Invoiced, and Voucher status = Normal holding, Clearing, and the holder is a supplier, and the financing transaction status corresponding to the voucher is Loaned and the repayment status is Unpaid / Repaid;

[0095] Accounts Payable - Invalidated: The accounts payable is invalid; Value: Accounts Payable Status = Invalidated Accounts Payable data.

[0096] Financing - Loan Released / Repaid: This financing transaction is in progress. The funding party has completed the loan, but has not yet repaid the loan. Value: Financing Transaction Status = Loan Released, Repayment Status = Unrepaid Financing Transaction Data / Repaid.

[0097] S3. According to the rule requirement keyword set, a reconciliation rule is configured, and according to the reconciliation rule, a direct reconciliation is performed on the to-be-reconciled data set to obtain a direct reconciliation result.

[0098] In the embodiment of the present invention, configuring the reconciliation rule refers to extracting the reconciliation rule that best suits the rule requirement keyword set from the configured reconciliation rules for configuration.

[0099] In detail, in the embodiment of the present invention, configuring the reconciliation rule according to the rule requirement keyword set includes:

[0100] Performing a semantic recognition operation on the rule requirement keyword set to obtain a semantic feature set;

[0101] Performing a correlation identification operation based on a preset reconciliation rule set on the semantic feature set to obtain a correlation score corresponding to each preset reconciliation rule in the preset reconciliation rule set;

[0102] Preset reconciliation rules whose relevance scores are greater than a preset matching threshold are extracted from the preset reconciliation rule set to obtain configured reconciliation rules.

[0103] Among them, the preset reconciliation rule sets, such as transaction matching rules, balance verification rules, abnormal transaction processing rules, data integrity and consistency rules, etc., have been constructed according to existing business scenarios and can be called at any time as a component. In addition, reconciliation rules can be constructed, deleted, and modified according to business development to increase the flexibility of customized reconciliation.

[0104] Furthermore, the direct reconciliation refers to automatically obtaining data from a preset data source, and performing data mapping and reconciliation according to the rules in the configuration module, usually without manual intervention. This method is suitable for scenarios with direct data access rights, and reconciliation can be completed automatically in real time or on a scheduled basis.

[0105] In the embodiment of the present invention, the to-be-reconciled tasks are automatically reconciled by a direct reconciliation method to obtain a reconciliation result, which can then be downloaded and exported.

[0106] Specifically, in the embodiment of the present invention, two tabs are divided into core enterprise reconciliation and funding party reconciliation according to the enterprise type. The list data and query data of the two reconciliation records are basically the same. The difference is that the filtering condition in the core enterprise tab is to query the core enterprise, and the enterprises displayed and queried in the list are also core enterprises; the filtering condition displayed in the funding party tab is the funding party, and the list and query are also the funding party.

[0107] The reconciliation result interface in the embodiment of the present invention is displayed as follows:

[0108] 1. Screening conditions:

[0109] Reconciliation serial number: Each reconciliation record of each reconciling enterprise has a separate reconciliation serial number;

[0110] Core enterprise / funder: support drop-down selection of corresponding type of enterprise;

[0111] Reconciliation result: supports drop-down selection, reconciliation success, reconciliation failure, and pull exception;

[0112] Reconciliation time: Date component, select a specific date.

[0113] 2. Details:

[0114] Click to enter the reconciliation details page.

[0115] 3. Delete:

[0116] Click to delete the reconciliation record.

[0117] 4. Export:

[0118] Export the table data according to the screening results.

[0119] 5. List:

[0120] Reconciliation result = data with abnormal or failed pulls needs to be displayed in red.

[0121] The reconciliation time needs to show specific data, accurate to the second.

[0122] The direct reconciliation details page provides an overview of:

[0123] 1. Display different detail pages according to different reconciliation results;

[0124] 2. When the reconciliation result is reconciliation failure or pull failure, the reconciliation failure reason module needs to be displayed;

[0125] 3. All detail pages support users to re-reconcile and export. For re-reconciliation, the data is pulled through the interface again to check with the platform and generate a new reconciliation record; for export, the detailed data is exported in a table.

[0126] S4. When the direct connection reconciliation result is a reconciliation failure, the reconciliation task and the direct connection reconciliation result are sent to a pre-built manual reconciliation interface.

[0127] In the embodiments of the present invention, the data source is unavailable or the response is delayed; the data format or standard changes, and the reconciliation system fails to be updated in time; data quality issues, such as incomplete or inaccurate data that lead to the inability to complete the reconciliation; network or technical problems lead to data synchronization failure, all of which can lead to reconciliation failure. To ensure that the reconciliation work can continue, manual reconciliation can be used as a supplementary method.

[0128] The manual reconciliation refers to allowing users to manually import or input data for reconciliation, which is usually used in situations where direct reconciliation cannot be handled, such as when the data source cannot be directly accessed, or for single reconciliation in special circumstances.

[0129] Specifically, the user clicks Menu-Reconciliation Management-Manual Reconciliation to enter the manual reconciliation page. The manual reconciliation interface supports the user to view historical manual reconciliation records and import data for manual reconciliation.

[0130] The manual reconciliation page is similar to the direct reconciliation result interface, with the addition of a [Add Reconciliation] button, which can be clicked to perform manual reconciliation, reconfigure the above-mentioned automatically configured reconciliation basic data configuration service, call a new set of data to be reconciled, configure new reconciliation rules, and re-reconcile.

[0131] The present invention extracts keywords from reconciliation tasks to identify data requirement keywords and rule requirement keywords, and realizes flexible configuration of data structure and reconciliation rules through pre-built reconciliation basic data configuration services, which can well adapt to the diversified development of business structure; in addition, users only need to select or construct reconciliation tasks to complete reconciliation operations without excessive manual configuration, thereby improving the automation efficiency of customized reconciliation. Therefore, the customized reconciliation method with adaptive data structure provided by the embodiment of the present invention can provide a method that can adapt to different data structures and flexibly configure reconciliation rules to improve the automation, accuracy and efficiency of reconciliation.

[0132] like Figure 3 , which is a functional module diagram of a customized reconciliation device with an adaptive data structure provided by an embodiment of the present invention.

[0133] The customized reconciliation device 100 of the adaptive data structure of the present invention can be installed in an electronic device. According to the functions to be implemented, the customized reconciliation device 100 of the adaptive data structure can include a reconciliation demand extraction module 101, a to-be-reconciled data retrieval module 102, a direct reconciliation module 103 and a manual reconciliation module 104. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, which are stored in the memory of the electronic device.

[0134] In this embodiment, the functions of each module / unit are as follows:

[0135] The reconciliation requirement extraction module 101 is used to perform a keyword extraction operation on the to-be-reconciled task selected by the user to obtain a data requirement keyword set and a rule requirement keyword set;

[0136] The to-be-reconciled data retrieval module 102 is used to retrieve the to-be-reconciled data set according to the data requirement keyword set by using the pre-built reconciliation basic data configuration service;

[0137] The direct connection reconciliation module 103 is used to configure the reconciliation rule according to the rule requirement keyword set, and perform direct connection reconciliation on the to-be-reconciled data set according to the reconciliation rule to obtain the direct connection reconciliation result;

[0138] The manual reconciliation module 104 is configured to send the reconciliation task and the direct reconciliation result to a pre-built manual reconciliation interface when the direct reconciliation result is a reconciliation failure.

[0139] In detail, each module described in the customized account reconciliation device 100 of the adaptive data structure described in the embodiment of the present application is used in the same manner as described above. Figure 1 to Figure 2 The customized reconciliation method of the adaptive data structure described in the text is the same technical means and can produce the same technical effects, so I will not go into details here.

[0140] like Figure 4 , which is a schematic diagram of the structure of an electronic device 1 for implementing a customized reconciliation method with an adaptive data structure provided by an embodiment of the present invention.

[0141] The electronic device 1 may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a customized reconciliation program with an adaptive data structure.

[0142] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 10 is the control core (ControlUnit) of the electronic device 1, and uses various interfaces and lines to connect the various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (for example, executing a customized reconciliation program for an adaptive data structure, etc.), and calls the data stored in the memory 11 to execute various functions of the electronic device and process data.

[0143] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 can also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 11 can also include both an internal storage unit of the electronic device and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of a customized reconciliation program of an adaptive data structure, but also can be used to temporarily store data that has been output or is to be output.

[0144] The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0145] The communication interface 13 is used for communication between the above-mentioned electronic device 1 and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0146] Figure 4 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 4The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0147] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0148] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0149] The customized account reconciliation program of the adaptive data structure stored in the memory 11 of the electronic device 1 is a combination of multiple instructions, and when running in the processor 10, it can achieve:

[0150] Perform keyword extraction operations on the tasks to be reconciled selected by the user to obtain a data requirement keyword set and a rule requirement keyword set;

[0151] Using the pre-built reconciliation basic data configuration service, retrieve the data set to be reconciled according to the data requirement keyword set;

[0152] According to the rule requirement keyword set, a reconciliation rule is configured, and the to-be-reconciled data set is directly reconciled according to the reconciliation rule to obtain a direct reconciliation result;

[0153] When the direct connection reconciliation result is a reconciliation failure, the reconciliation task and the direct connection reconciliation result are sent to a pre-built manual reconciliation interface.

[0154] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0155] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0156] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0157] Perform keyword extraction operations on the tasks to be reconciled selected by the user to obtain a data requirement keyword set and a rule requirement keyword set;

[0158] Using the pre-built reconciliation basic data configuration service, retrieve the data set to be reconciled according to the data requirement keyword set;

[0159] According to the rule requirement keyword set, a reconciliation rule is configured, and the to-be-reconciled data set is directly reconciled according to the reconciliation rule to obtain a direct reconciliation result;

[0160] When the direct connection reconciliation result is a reconciliation failure, the reconciliation task and the direct connection reconciliation result are sent to a pre-built manual reconciliation interface.

[0161] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0162] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0163] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0164] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0165] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is limited by the appended claims rather than the above description, so it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any attached figure mark in the claims should not be regarded as limiting the claims involved.

[0166] The blockchain referred to in this invention is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0167] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0168] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the system claim can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0169] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A customized reconciliation method with an adaptive data structure, characterized in that: The method comprises: Perform keyword extraction operations on the tasks to be reconciled selected by the user to obtain a data requirement keyword set and a rule requirement keyword set; Using the pre-built reconciliation basic data configuration service, retrieve the data set to be reconciled according to the data requirement keyword set; According to the rule requirement keyword set, a reconciliation rule is configured, and the to-be-reconciled data set is directly reconciled according to the reconciliation rule to obtain a direct reconciliation result; When the direct connection reconciliation result is a reconciliation failure, the reconciliation task and the direct connection reconciliation result are sent to a pre-built manual reconciliation interface.

2. The customized reconciliation method of the adaptive data structure according to claim 1, characterized in that: The pre-built reconciliation basic data configuration service is used to retrieve the to-be-reconciled data set according to the data requirement keyword set, including: Using the reconciliation basic data configuration service, identifying the enterprise type and the reconciliation enterprise in the data demand keyword set, and acquiring the data source of the to-be-reconciled task according to the enterprise type, the data source including the accounts payable data source and the financing data source; According to the enterprise type and data source, query the data of the reconciliation enterprise to obtain basic reconciliation data; Select the reconciliation scope based on the type of data source; Retrieving maintenance status mapping data according to the reconciliation scope and data source; The data satisfying the basic reconciliation data, the reconciliation scope and the maintenance status mapping data are retrieved to obtain a set of data to be reconciled.

3. The customized reconciliation method of the adaptive data structure according to claim 2, characterized in that: According to the enterprise type and data source, data query is performed on the reconciliation enterprise to obtain basic reconciliation data, including: When the enterprise type is a preset core enterprise, the core type data of the reconciliation enterprise in the accounts payable data source and the financing data source are called as basic reconciliation data; When the enterprise type is a preset funding party, the funding party type data of the reconciliation enterprise in the financing data source is called as the basic reconciliation data.

4. The customized reconciliation method of the adaptive data structure according to claim 3, characterized in that: The selecting of the reconciliation scope according to the type of the data source includes: When the data source is the accounts payable data, obtaining a preset reconciliation range of undisbursed loans and disbursed but unsettled loans; When the data source is the financing data, the reconciliation scope of the disbursed but unsettled loans is obtained.

5. The customized reconciliation method of the adaptive data structure according to claim 4, characterized in that: The retrieving maintenance status mapping data according to the reconciliation scope and the data source includes: When the data source is the accounts payable data; If the reconciliation scope is the unsettled loan, retrieve the preset maintenance status mapping data of payables-financed-loans and payables-invoiced-loans; If the reconciliation scope is the undisbursed funds, retrieve the preset maintenance status mapping data of payables-unused, payables-financing, payables-billing, payables-billed-undisbursed and payables-invalidated; When the data source is financing data; If the reconciliation scope is the unsettled loan, retrieve the preset financing-loan maintenance status mapping data.

6. The customized reconciliation method of the adaptive data structure according to claim 1, characterized in that: The configuring of the reconciliation rule according to the rule requirement keyword set includes: Performing a semantic recognition operation on the rule requirement keyword set to obtain a semantic feature set; Performing a correlation identification operation based on a preset reconciliation rule set on the semantic feature set to obtain a correlation score corresponding to each preset reconciliation rule in the preset reconciliation rule set; Preset reconciliation rules whose relevance scores are greater than a preset matching threshold are extracted from the preset reconciliation rule set to obtain configured reconciliation rules.

7. The customized reconciliation method of the adaptive data structure according to claim 1, characterized in that: The keyword extraction operation is performed on the task to be reconciled selected by the user to obtain a data requirement keyword set and a rule requirement keyword set, including: Performing word segmentation processing on the pending reconciliation tasks to obtain a word segmentation set; Performing a sequential quantization encoding operation on the word segmentation set to obtain a word segmentation vector set; Performing a context-based text semantic feature extraction operation on the word segmentation vector set to obtain a word segmentation feature sequence; A binary keyword extraction operation based on data and demand is performed on the word segmentation feature sequence to obtain a data demand keyword set and a rule demand keyword set.

8. A customized reconciliation device with an adaptive data structure, characterized in that: The device comprises: The reconciliation requirement extraction module is used to extract keywords from the reconciliation tasks selected by the user to obtain a data requirement keyword set and a rule requirement keyword set; A module for reconciliation data retrieval, used to retrieve the reconciliation data set according to the data requirement keyword set by using the pre-built reconciliation basic data configuration service; A direct reconciliation module, configured to configure a reconciliation rule according to the rule requirement keyword set, and to perform direct reconciliation on the to-be-reconciled data set according to the reconciliation rule to obtain a direct reconciliation result; The manual reconciliation module is used to send the reconciliation task and the direct reconciliation result to a pre-built manual reconciliation interface when the direct reconciliation result is a reconciliation failure.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the customized reconciliation method of the adaptive data structure as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the customized reconciliation method of the adaptive data structure according to any one of claims 1 to 7 is implemented.

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