Data reconciliation method and device, computer device and storage medium

Abstract

The application belongs to the field of data processing, and relates to a data reconciliation method and device, a computer device and a storage medium, which comprises the following steps: obtaining service flow data of a first transaction from a service backup library; performing fee calculation on the first transaction based on a charging rule model to obtain first fee data, and generating first to-be-reconciled data based on the service flow data and the first fee data; obtaining reconciliation data of a second transaction from a channel system, performing fee calculation on the second transaction to obtain second fee data, and generating second to-be-reconciled data of the second transaction based on the reconciliation data and the second fee data; obtaining first key data of a specified transaction from the first to-be-reconciled data, and obtaining second key data of a target transaction from the second to-be-reconciled data; if the first key data is consistent with the second key data, comparing third key data of the specified transaction extracted from a service main library with the second key data to generate a reconciliation result of the specified transaction. The application improves the efficiency and accuracy of data reconciliation.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to methods, apparatus, computer equipment and storage media for data reconciliation. Background Technology

[0002] In financial and healthcare sectors, reconciliation is a crucial step in ensuring the accuracy and completeness of transaction data. However, current reconciliation systems, when performing electronic reconciliation, rely on a single database for all data storage. This single database is used to query and retrieve transaction records, which are then compared with payment records returned by the payment channels. This method results in high query load on the database, low efficiency, and low system stability. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, computer device, and storage medium for data reconciliation, in order to solve the technical problems of existing data reconciliation methods, such as high database query pressure, low data reconciliation efficiency, and low system stability.

[0004] To address the aforementioned technical problems, this application provides a data reconciliation method, employing the following technical solution:

[0005] The business transaction log data of the first transaction within a preset time period is obtained from the preset business backup database; wherein, the business backup database is a backup database of the business master database;

[0006] Based on the business transaction data and the preset billing rule model, the first transaction is calculated to obtain the corresponding first cost data, and the first reconciliation data of the first transaction is generated based on the business transaction data and the first cost data; wherein, the billing rule model is used to call and perform corresponding condition judgments and calculation logic steps when calculating costs to complete the cost calculation process;

[0007] The system obtains reconciliation data of the second transaction within a preset time period from the preset channel system, calculates the corresponding second fee data based on the reconciliation data and the billing rule model, and generates the second reconciliation data of the second transaction based on the reconciliation data and the second fee data.

[0008] The system retrieves first key data corresponding to a specified transaction from the first set of accounts to be reconciled, identifies a target transaction matching the specified transaction from the second set of accounts to be reconciled, and retrieves second key data corresponding to the target transaction from the second set of accounts to be reconciled; wherein, the specified transaction includes any one of the first transactions;

[0009] The first key data and the second key data are compared to determine whether the first key data and the second key data are consistent.

[0010] If the first key data is inconsistent with the second key data, then the third key data corresponding to the specified transaction is extracted from the preset business master database;

[0011] The third key data is compared with the second key data to generate a reconciliation result corresponding to the specified transaction.

[0012] To address the aforementioned technical problems, this application also provides a data reconciliation apparatus, which employs the following technical solution:

[0013] The first acquisition module is used to acquire the business transaction data of the first transaction within a preset time period from a preset business backup database; wherein, the business backup database is a backup database of the business master database;

[0014] The first processing module is used to calculate the cost of the first transaction based on the business transaction data and a preset billing rule model to obtain the corresponding first cost data, and to generate the first reconciliation data of the first transaction based on the business transaction data and the first cost data; wherein, the billing rule model is used to be invoked during the cost calculation and to perform corresponding condition judgments and calculation logic steps to complete the cost calculation process;

[0015] The second processing module is used to obtain reconciliation data of the second transaction within a preset time period from a preset channel system, calculate the corresponding second fee data for the second transaction based on the reconciliation data and the billing rule model, and generate the second reconciliation data of the second transaction based on the reconciliation data and the second fee data.

[0016] The third processing module is used to obtain first key data corresponding to a specified transaction from the first reconciliation data, determine a target transaction matching the specified transaction from the second transaction, and obtain second key data corresponding to the target transaction from the second reconciliation data; wherein, the specified transaction includes any one of the first transactions;

[0017] The comparison module is used to compare the first key data with the second key data to determine whether the first key data and the second key data are consistent.

[0018] The extraction module is used to extract the third key data corresponding to the specified transaction from a preset business master database if the first key data is inconsistent with the second key data.

[0019] The first generation module is used to compare the third key data with the second key data to generate a reconciliation result corresponding to the specified transaction.

[0020] To address the aforementioned technical problems, this application also provides a computer device that employs the following technical solution:

[0021] The business transaction log data of the first transaction within a preset time period is obtained from the preset business backup database; wherein, the business backup database is a backup database of the business master database;

[0022] Based on the business transaction data and the preset billing rule model, the first transaction is calculated to obtain the corresponding first cost data, and the first reconciliation data of the first transaction is generated based on the business transaction data and the first cost data; wherein, the billing rule model is used to call and perform corresponding condition judgments and calculation logic steps when calculating costs to complete the cost calculation process;

[0023] The system obtains reconciliation data of the second transaction within a preset time period from the preset channel system, calculates the corresponding second fee data based on the reconciliation data and the billing rule model, and generates the second reconciliation data of the second transaction based on the reconciliation data and the second fee data.

[0024] The system retrieves first key data corresponding to a specified transaction from the first set of accounts to be reconciled, identifies a target transaction matching the specified transaction from the second set of accounts to be reconciled, and retrieves second key data corresponding to the target transaction from the second set of accounts to be reconciled; wherein, the specified transaction includes any one of the first transactions;

[0025] The first key data and the second key data are compared to determine whether the first key data and the second key data are consistent.

[0026] If the first key data is inconsistent with the second key data, then the third key data corresponding to the specified transaction is extracted from the preset business master database;

[0027] The third key data is compared with the second key data to generate a reconciliation result corresponding to the specified transaction.

[0028] To address the aforementioned technical problems, this application also provides a computer-readable storage medium, employing the technical solution described below:

[0029] The business transaction log data of the first transaction within a preset time period is obtained from the preset business backup database; wherein, the business backup database is a backup database of the business master database;

[0030] Based on the business transaction data and the preset billing rule model, the first transaction is calculated to obtain the corresponding first cost data, and the first reconciliation data of the first transaction is generated based on the business transaction data and the first cost data; wherein, the billing rule model is used to call and perform corresponding condition judgments and calculation logic steps when calculating costs to complete the cost calculation process;

[0031] The system obtains reconciliation data of the second transaction within a preset time period from the preset channel system, calculates the corresponding second fee data based on the reconciliation data and the billing rule model, and generates the second reconciliation data of the second transaction based on the reconciliation data and the second fee data.

[0032] The system retrieves first key data corresponding to a specified transaction from the first set of accounts to be reconciled, identifies a target transaction matching the specified transaction from the second set of accounts to be reconciled, and retrieves second key data corresponding to the target transaction from the second set of accounts to be reconciled; wherein, the specified transaction includes any one of the first transactions;

[0033] The first key data and the second key data are compared to determine whether the first key data and the second key data are consistent.

[0034] If the first key data is inconsistent with the second key data, then the third key data corresponding to the specified transaction is extracted from the preset business master database;

[0035] The third key data is compared with the second key data to generate a reconciliation result corresponding to the specified transaction.

[0036] Compared with the prior art, the embodiments of this application have the following main advantages:

[0037] First, business transaction data for the first transaction within a preset time period is retrieved from a preset business backup database. Based on this data and a preset billing rule model, the cost of the first transaction is calculated to obtain corresponding first cost data. Then, based on this data, first reconciliation data for the first transaction is generated. Next, reconciliation data for the second transaction within a preset time period is retrieved from a preset channel system. Based on this data and the billing rule model, the cost of the second transaction is calculated to obtain corresponding second cost data. Then, based on this data, second reconciliation data for the second transaction is generated. Finally, first key data corresponding to a specified transaction is retrieved from the first reconciliation data, and a target transaction matching the specified transaction is identified from the second transaction. Finally, the second reconciliation data is retrieved from the second reconciliation data. The system retrieves second key data corresponding to the target transaction; wherein the designated transaction includes any one of the first transactions; subsequently, the first key data and the second key data are compared to determine whether they are consistent; if the first key data and the second key data are inconsistent, a third key data corresponding to the designated transaction is extracted from a preset business master database; finally, the third key data is compared with the second key data to generate a reconciliation result corresponding to the designated transaction. Thus, unlike existing data reconciliation methods, this application, by adopting a business backup database-first approach for automated reconciliation, can significantly reduce the query pressure on the business master database, thereby effectively improving the processing efficiency of data reconciliation, ensuring the accuracy of the reconciliation results, and enhancing the stability of the system. Attached Figure Description

[0038] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is an exemplary system architecture diagram to which this application can be applied;

[0040] Figure 2 A flowchart of an embodiment of the data reconciliation method according to this application;

[0041] Figure 3 This is a schematic diagram of one embodiment of a data reconciliation apparatus according to this application;

[0042] Figure 4 This is a schematic diagram of the structure of one embodiment of the computer device according to this application. Detailed Implementation

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0044] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0045] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0046] like Figure 1 As shown, system architecture 100 may include terminal device 101, network 102, and server 103. Terminal device 101 may be a laptop 1011, tablet 1012, or mobile phone 1013. Network 102 is used as a medium to provide a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0047] Users can use terminal device 101 to interact with server 103 via network 102 to receive or send messages, etc. Various communication client applications can be installed on terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.

[0048] Terminal device 101 can be various electronic devices with a display screen and support web browsing. In addition to laptops 1011, tablets 1012, or mobile phones 1013, terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 player (Moving Picture Experts Group Audio Layer IV), a laptop computer, and a desktop computer, etc.

[0049] Server 103 can be a server that provides various services, such as a backend server that provides support for the pages displayed on terminal device 101.

[0050] It should be noted that the data reconciliation method provided in this application embodiment is generally executed by a server / terminal device, and correspondingly, the data reconciliation device is generally set in the server / terminal device.

[0051] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0052] Continue to refer to Figure 2 A flowchart illustrating an embodiment of the data reconciliation method according to this application is shown. The order of steps in the flowchart can be changed, and some steps can be omitted, depending on different needs. The data reconciliation method provided in this application embodiment can be applied to any scenario requiring product recommendations, and thus can be applied to products in these scenarios, such as product recommendations in the financial insurance field. The data reconciliation method includes the following steps:

[0053] Step S201: Obtain the business transaction data of the first transaction within a preset time period from the preset business backup database; wherein, the business backup database is a backup database of the business master database.

[0054] In this embodiment, the data reconciliation method runs on electronic devices (e.g., Figure 1The server / terminal device shown can acquire business transaction data via wired or wireless connection. It should be noted that the aforementioned wireless connection methods include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra-wideband) connections, and other currently known or future-developed wireless connection methods. The executing entity of this application is specifically a reconciliation processing system, which can be simply referred to as the system. The system includes a primary business database and a backup business database. The backup business database is a copy or backup database of the primary business database, typically used for non-real-time operations such as data reading, analysis, and reporting. The primary business database stores core business data and is usually updated in real-time, containing the latest business data. Specifically, this application can be applied to data reconciliation processing in the financial and medical fields. For example, in the financial field, transactions requiring data reconciliation operations can include stock transactions, bond transactions, futures transactions, foreign exchange transactions, options transactions, etc. In the healthcare field, transactions requiring data reconciliation include medical equipment procurement, pharmaceutical procurement, medical service transactions, medical technology licensing transactions, and healthcare mergers and acquisitions, among others.

[0055] The specific implementation process of obtaining the business transaction data of the first transaction within a preset time period from the preset business backup database will be further described in detail in subsequent specific embodiments of this application, and will not be elaborated on here.

[0056] Step S202: Based on the business transaction data and the preset billing rule model, calculate the cost of the first transaction to obtain the corresponding first cost data, and generate the first reconciliation data of the first transaction based on the business transaction data and the first cost data; wherein, the billing rule model is used to call and perform corresponding condition judgments and calculation logic steps when calculating costs to complete the cost calculation process.

[0057] In this embodiment, the specific implementation process of calculating the corresponding first fee data for the first transaction based on the business transaction data and the preset billing rule model will be further described in detail in subsequent specific embodiments of this application, and will not be elaborated on here. Additionally, the first reconciliation data for the first transaction can be obtained by integrating the aforementioned business transaction data and the first fee data. Furthermore, the generated first reconciliation data can be stored in a preset reconciliation database to facilitate subsequent data reconciliation processing.

[0058] Step S203: Obtain reconciliation data of the second transaction within a preset time period from the preset channel system; calculate the corresponding second fee data for the second transaction based on the reconciliation data and the billing rule model; and generate the second reconciliation data for the second transaction based on the reconciliation data and the second fee data.

[0059] In this embodiment, the aforementioned channel system refers to an interface or platform for exchanging data with external partners or third-party systems. Reconciliation data provided by the channel system can be received by establishing a data interface or data synchronization mechanism with the channel system. Reconciliation data typically includes key information such as transaction serial number, transaction amount, and channel fees. The received reconciliation data can undergo verification processes such as data format checks and data range checks to ensure its integrity, accuracy, and consistency. Furthermore, the process of calculating the corresponding second fee data for the second transaction based on the reconciliation data and the billing rule model can refer to the implementation process of calculating the corresponding first fee data for the first transaction based on the business transaction data and the preset billing rule model, and will not be elaborated further here. In addition, the reconciliation data and the second fee data can be integrated to obtain the second reconciliation data for the second transaction. The generated second reconciliation data can be stored in the aforementioned reconciliation database for subsequent data reconciliation processing.

[0060] Step S204: Obtain first key data corresponding to a specified transaction from the first reconciliation data, determine a target transaction matching the specified transaction from the second transaction, and obtain second key data corresponding to the target transaction from the second reconciliation data; wherein, the specified transaction includes any one of the first transactions.

[0061] In this embodiment, the designated transaction includes any one of the first transactions. The first key data may be the amount, fee, date, etc., of the designated transaction. The target transaction refers to the transaction with the same serial number as the first transaction among all the second transactions. Similarly, the second key data may refer to the amount, fee, date, etc., of the target transaction.

[0062] Step S205: Compare the first key data with the second key data to determine whether the first key data and the second key data are consistent.

[0063] In this embodiment, a preset comparison tool can be used to compare the first key data with the second key data. Specifically, the tool checks whether the amounts, fees, dates, and other key information are identical. If they are identical, the first key data and the second key data are determined to be consistent; otherwise, they are determined to be inconsistent. If the first key data and the second key data are consistent, the specified transaction is directly determined to be a transaction with normal reconciliation, and a reconciliation result for the specified transaction is generated.

[0064] This application takes into account the massive data volume and relatively low real-time requirements of reconciliation data, and prioritizes data reconciliation using a business backup database. This not only significantly reduces the query pressure on the primary business database and ensures the stability of the production environment, but also greatly improves data reconciliation efficiency. Furthermore, since the business backup database handles most of the reconciliation tasks, it effectively reduces the burden on the primary business database, thereby enhancing the stability of the entire system.

[0065] Step S206: If the first key data is inconsistent with the second key data, then extract the third key data corresponding to the specified transaction from the preset business master database.

[0066] In this embodiment, the aforementioned business master database refers to the main database storing core business data and is the authoritative source of data. Extracting the third key data corresponding to a specified transaction from the business master database may include extracting the specified business transaction flow data of the specified transaction from the business master database, calculating the corresponding specified fee data based on the specified business transaction flow data and the billing rule model, and then filtering out key information such as the amount, fee, and date required for data reconciliation processing from the specified business transaction flow data and the specified fee data as the aforementioned third key data.

[0067] Step S207: Compare the third key data with the second key data to generate a reconciliation result corresponding to the specified transaction.

[0068] In this embodiment, when an anomaly occurs in the business backup database reconciliation, the system automatically retrieves the corresponding data from the business master database for secondary verification. This effectively reduces reconciliation errors caused by data synchronization loss and greatly improves the accuracy of the reconciliation results. The specific implementation process of comparing the third key data with the second key data to generate the reconciliation result corresponding to the specified transaction will be further described in detail in subsequent embodiments of this application and will not be elaborated upon here.

[0069] This application first obtains business transaction data for a first transaction within a preset time period from a preset business backup database; then, based on the business transaction data and a preset billing rule model, calculates the cost of the first transaction to obtain corresponding first cost data, and generates first reconciliation data for the first transaction based on the business transaction data and the first cost data; next, it obtains reconciliation data for a second transaction within a preset time period from a preset channel system, calculates the cost of the second transaction based on the reconciliation data and the billing rule model to obtain corresponding second cost data, and generates second reconciliation data for the second transaction based on the reconciliation data and the second cost data; then, it obtains first key data corresponding to a specified transaction from the first reconciliation data, identifies a target transaction matching the specified transaction from the second transaction, and obtains second reconciliation data from the second reconciliation data... The system retrieves second key data corresponding to the target transaction; wherein the designated transaction includes any one of the first transactions; subsequently, the first key data and the second key data are compared to determine whether they are consistent; if the first key data and the second key data are inconsistent, then the third key data corresponding to the designated transaction is extracted from the preset business master database; finally, the third key data is compared with the second key data to generate a reconciliation result corresponding to the designated transaction. Thus, unlike existing data reconciliation methods, this application, by adopting a business backup database-first automated reconciliation method, can significantly reduce the query pressure on the business master database, thereby effectively improving the processing efficiency of data reconciliation, ensuring the accuracy of the reconciliation results, and enhancing the stability of the system.

[0070] In some alternative implementations, step S201 includes the following steps:

[0071] Obtain the preset business transaction type, and construct the corresponding data extraction script based on the business transaction type.

[0072] In this embodiment, the aforementioned business transaction type refers to the information type corresponding to the transaction data required by the business, which is predetermined based on actual business needs. For example, it may include transaction time, transaction amount, transaction type, and transaction status. A matching data extraction script can be written based on the aforementioned business transaction type. This data extraction script can be an SQL query statement or a dedicated data extraction tool configuration, and it has the function of extracting business transaction data corresponding to that business transaction type from the business backup database. The business transaction data may at least include transaction time, transaction amount, transaction type, and transaction status.

[0073] The data extraction script is executed in the business backup database to extract the initial business transaction data within the preset time period.

[0074] In this embodiment, the data extraction script can be executed in the aforementioned business backup database to extract initial business transaction data that meets the requirements within a preset time period. The selection of the preset time period is not specifically limited and can be determined based on actual data reconciliation needs; for example, the past month could be used.

[0075] The initial business flow data is cleaned to obtain the corresponding first data.

[0076] In this embodiment, the data cleaning process described above may include deduplication and invalid data processing. Deduplication includes removing duplicate records from the extracted initial business transaction data through data comparison or deduplication algorithms. Invalid data processing includes identifying and processing invalid data, such as null values, invalid values, or data that does not conform to business rules.

[0077] The first data is formatted to obtain the corresponding second data.

[0078] In this embodiment, the above-mentioned formatting process refers to formatting the data into a uniform format, such as a date format or a monetary format, to ensure the accuracy and consistency of the data.

[0079] The second data is used as the business transaction data.

[0080] This application obtains a preset business transaction type and constructs a corresponding data extraction script based on the business transaction type. Then, it executes the data extraction script in the business backup database to extract initial business transaction data within a preset time period. Next, it performs data cleaning on the initial business transaction data to obtain corresponding first data. Subsequently, it formats the first data to obtain corresponding second data. Finally, it uses the second data as the business transaction data. This application, by obtaining a preset business transaction type and constructing a corresponding data extraction script based on the business transaction type, and then executing the data extraction script in the business backup database to extract initial business transaction data within a preset time period, and subsequently performing data cleaning and formatting on the initial business transaction data, can efficiently and accurately obtain the required first transaction business transaction data, improving the efficiency of business transaction data acquisition and ensuring the accuracy of the obtained business transaction data.

[0081] In some optional implementations of this embodiment, step S202, which involves calculating the cost of the first transaction based on the business transaction data and a preset billing rule model to obtain the corresponding first cost data, includes the following steps:

[0082] Invoke the aforementioned billing rule model.

[0083] In this embodiment, in-depth communication with business departments and channel partners was conducted beforehand to understand business needs, billing models, and channel reconciliation requirements. Based on these needs, a flexible billing rule model was defined, capable of easily handling complex scenarios such as tiered billing and personalized billing. This billing rule model meets the ever-changing market demands and provides enterprises with greater flexibility and innovation capabilities. Different billing rules are set for different scenarios and channels, such as per-transaction billing, percentage-based billing, and tiered billing. These billing rules clearly define key elements such as billing conditions, billing standards, and billing cycles. Before formal application, the billing rules are validated to ensure their correctness and rationality. The designed billing rules are then transformed into system-recognizable logic and stored in the system. This allows the billing rule model to call upon these rules during subsequent cost calculations, performing corresponding condition checks and calculations to complete the cost calculation process.

[0084] Based on the billing rule model, obtain the target billing rule that matches the first transaction.

[0085] In this embodiment, the aforementioned billing rule model can be used to match all pre-built billing rules with the first transaction, thereby identifying the target billing rule corresponding to the first transaction. For example, suppose the billing rules include billing rule 1 "Transactions with an amount greater than 1000 yuan will incur a 1% handling fee" and billing rule 2 "Transactions with an amount less than or equal to 1000 yuan will be free of charge." If the first transaction's amount is 1600 yuan, then the target billing rule corresponding to the first transaction is billing rule 1. If the first transaction's amount is 800 yuan, then the target billing rule corresponding to the first transaction is billing rule 2.

[0086] The target billing rule is applied to calculate the cost of the first transaction, and the corresponding cost calculation result is obtained.

[0087] In this embodiment, the calculation steps of the above-mentioned target billing rules can be applied to calculate the cost of the first transaction, thereby obtaining the corresponding cost calculation result, which can be used as the first cost data of the first transaction.

[0088] The calculated cost result is used as the first cost data for the first transaction.

[0089] This application calls the aforementioned billing rule model; then, based on the billing rule model, obtains a target billing rule matching the first transaction; subsequently, it applies the target billing rule to calculate the cost of the first transaction, obtaining the corresponding cost calculation result; and finally, it uses the cost calculation result as the first cost data for the first transaction. This application, by using the billing rule model to obtain a target billing rule matching the first transaction and then applying the target billing rule to calculate the cost of the first transaction, can quickly and accurately complete the cost calculation process for the first transaction, improving the processing efficiency of cost calculation and ensuring the accuracy of the obtained first cost data.

[0090] In some alternative implementations, step S207 includes the following steps:

[0091] The third key data is compared with the second key data using a preset comparison tool to determine whether the third key data and the second key data are consistent.

[0092] In this embodiment, the comparison tool is a tool with data comparison function. The comparison tool can be invoked to compare the third key data with the second key data, that is, to check whether the key information such as amount, fee, and date are the same. If they are the same, the third key data is determined to be consistent with the second key data; otherwise, the third key data is determined to be inconsistent with the second key data.

[0093] If the third key data is consistent with the second key data, then the first reconciliation result of the specified transaction reconciliation is generated.

[0094] In this embodiment, a data synchronization problem arises when the data between the business master database and the channel system is inconsistent. This inconsistency can be caused by various reasons, including but not limited to network latency, data loss, system errors, and human intervention. Data synchronization problems can lead to inaccurate reconciliation results because reconciliation typically relies on data consistency between two or more systems. However, if the data in the master database is identical to the data in the channel system, it can be determined that there is no data synchronization problem in this case. This means that the data between the two systems is consistent, and therefore, errors due to data inconsistency will not occur during the reconciliation process.

[0095] If the third key data is found to be consistent with the second key data, the system will intelligently determine that the specified transaction is a transaction with normal reconciliation, and then generate the first reconciliation result that the specified transaction is normal.

[0096] If the third key data is inconsistent with the second key data, a second result for the specified transaction reconciliation anomaly is generated.

[0097] In this embodiment, if the third key data is found to be inconsistent with the second key data, it indicates that there is a data synchronization problem between the business master database and the channel system. Consequently, the specified transaction will be determined to be a transaction with reconciliation anomalies, and a second result of the specified transaction reconciliation anomalies will be generated.

[0098] This application compares the third key data with the second key data using a preset comparison tool to determine whether the third key data and the second key data are consistent. If the third key data and the second key data are consistent, a first reconciliation result indicating that the specified transaction reconciliation is normal is generated; otherwise, a second result indicating that the specified transaction reconciliation is abnormal is generated. When the first key data and the second key data are detected to be inconsistent, this application performs a secondary comparison between the third key data obtained from the business master database and the second key data using a comparison tool. This allows for the intelligent and accurate generation of a reconciliation result corresponding to the specified transaction based on the comparison results, thereby ensuring the accuracy of the generated reconciliation result and reducing errors caused by data synchronization issues.

[0099] In some alternative implementations, prior to step S202, the electronic device may also perform the following steps:

[0100] Obtain simulated transaction data corresponding to the billing rule model.

[0101] In this embodiment, diverse simulated transaction data can be pre-generated based on business logic and transaction scenarios. Simulated transaction data can include normal transaction data, abnormal transaction data, and boundary condition data. Normal transaction data can include common transaction types, amounts, and times. Abnormal transaction data can include invalid transaction types, extreme amounts, and illegal times. Boundary condition data can include minimum transaction amounts, maximum transaction amounts, and transactions at specific times. Additionally, each simulated transaction is labeled with the expected cost result (expected result) as a benchmark for verification.

[0102] Invoke the verification script corresponding to the billing rule model.

[0103] In this embodiment, the verification script is a pre-built script that has the function of reading simulated transaction data, calculating fees through a billing rule model, and comparing them with expected results.

[0104] Run the verification script to verify the simulated transaction data and obtain the corresponding verification results.

[0105] In this embodiment, the verification objective is to verify whether the billing rule model can correctly calculate fees under various transaction scenarios. By running the aforementioned verification script, simulated transaction data is read from the billing rule model to calculate fees, and the results are compared with the expected results. The comparison results can include those that meet expectations and those that do not. By filtering out the expected target comparison results from the above comparison results, the ratio between the first number of target comparison results and the second number of all comparison results is calculated. If the ratio is greater than a preset verification threshold, a verification result corresponding to the billing rule model that has passed is generated; otherwise, a verification result corresponding to the billing rule model that has failed is generated. Furthermore, the value of the aforementioned verification threshold is not specifically limited and can be set according to actual business needs; for example, it can be set to 0.95.

[0106] Determine whether the verification result is a successful verification.

[0107] In this embodiment, the verification result may include verification passed or verification failed. If the verification result is unsuccessful, the simulated transaction data cases that do not meet expectations can be further analyzed, and the reasons for the unsuccessful simulated transaction data cases can be analyzed, such as model logic errors, data labeling errors, etc. Then, the errors in the billing rule model can be repaired based on the analysis results, and the repaired billing rule model can be verified again to ensure that the problem is resolved.

[0108] If so, the billing rule model is deployed and processed.

[0109] In this embodiment, if the verification result is detected as successful, it indicates that the billing rule model has good correctness and rationality. Subsequently, the billing rule model will be directly deployed into the system so that it can be used directly for transaction fee calculation.

[0110] This application obtains simulated transaction data corresponding to the billing rule model; then calls a verification script corresponding to the billing rule model; subsequently runs the verification script to verify the simulated transaction data and obtains the corresponding verification result; then determines whether the verification result is successful; if so, the billing rule model is deployed. This application obtains simulated transaction data corresponding to the billing rule model, calls a verification script corresponding to the billing rule model, and then verifies the simulated transaction data based on the use of the verification script to obtain the corresponding verification result. Only when the verification result is detected as successful will the billing rule model be deployed. This effectively ensures that the billing rule model undergoes sufficient verification before formal application, thereby improving the correctness and rationality of the billing rule model.

[0111] In some optional implementations of this embodiment, after step S202, the electronic device may further perform the following steps:

[0112] Call the preset reconciliation database.

[0113] In this embodiment, the aforementioned reconciliation database is a pre-built database used to store data that needs to be reconciled.

[0114] Get the preset data insertion strategy.

[0115] In this embodiment, the selection of the above data insertion strategy is not specifically limited and can be determined according to actual business needs. For example, batch insertion operation or sequential insertion operation can be used.

[0116] Based on the data insertion strategy, the first account reconciliation data is stored in the reconciliation database.

[0117] In this embodiment, the first reconciliation data can be stored in the reconciliation database according to the data insertion operation corresponding to the above data insertion strategy, providing a reliable data foundation for subsequent reconciliation processing. Specifically, tables for storing reconciliation data can be created or updated in the reconciliation database. Additionally, the time, amount, success or failure information of the first reconciliation data storage can be recorded synchronously for subsequent tracking and auditing. Similarly, when generating the second reconciliation data for the second transaction based on the reconciliation data and the second expense data, the operation of storing the second reconciliation data in the reconciliation database also needs to be performed, thereby providing a reliable data foundation for subsequent reconciliation processing.

[0118] This application calls a preset reconciliation database; then obtains a preset data insertion strategy; and subsequently, based on the data insertion strategy, stores the first reconciliation data to be reconciled into the reconciliation database. After generating the first reconciliation data for the first transaction based on business transaction data and first expense data, this application intelligently stores the first reconciliation data into the reconciliation database based on the data insertion strategy, thereby completing the storage process for the first reconciliation data, ensuring the security of the generated first reconciliation data, and providing a reliable data foundation for subsequent reconciliation processing.

[0119] In some optional implementations of this embodiment, after step S207, the electronic device may further perform the following steps:

[0120] Determine whether the reconciliation result indicates an anomaly in the reconciliation of the specified transaction.

[0121] In this embodiment, the content of the above reconciliation results may include specified transaction reconciliation abnormalities or specified transaction reconciliation normalities.

[0122] If so, retrieve the abnormal data corresponding to the specified transaction.

[0123] In this embodiment, if the reconciliation result is detected as an anomaly in the specified transaction reconciliation, the abnormal data existing in the specified transaction will be extracted. The abnormal data refers to data with reconciliation anomalies, such as mismatched transaction serial numbers, different transaction amounts, or different transaction fees, etc.

[0124] Based on the abnormal data, an early warning message corresponding to the specified transaction is generated.

[0125] In this embodiment, the aforementioned abnormal data can be filled into the corresponding positions within a preset warning information template to generate corresponding warning information. The content of the warning information template is not limited and can be written according to actual needs.

[0126] Obtain the notification method corresponding to the target business personnel.

[0127] In this embodiment, the target business personnel mentioned above can be the business personnel responsible for data reconciliation. The selection of the notification method is not specifically limited and can be determined according to actual business needs; for example, email notifications, SMS notifications, etc., can be used.

[0128] Based on the notification method, the warning information is sent to the target business personnel.

[0129] In this embodiment, the notification method described above can be used to send warning information to the target business personnel. This allows the target business personnel to address the discrepancies in the specified transactions with reconciliation anomalies based on the warning information. This includes processes such as communication with channel partners, data correction, and transaction adjustments, thereby resolving the reconciliation anomaly issue and avoiding potential risks and disputes.

[0130] This application determines whether the reconciliation result indicates an anomaly in the reconciliation of a specified transaction. If so, it acquires the abnormal data corresponding to the specified transaction, generates an early warning message based on the abnormal data, acquires a notification method corresponding to the target business personnel, and then sends the early warning message to the target business personnel based on the notification method. When this application detects an anomaly in the reconciliation result of a specified transaction, it intelligently acquires the abnormal data corresponding to the specified transaction and automatically generates an early warning message based on the abnormal data. Then, according to the acquired notification method corresponding to the target business personnel, it sends the early warning message to the target business personnel, enabling them to promptly follow up and process the abnormal data in the specified transaction, thereby resolving the reconciliation anomaly issue. This helps improve the efficiency and accuracy of reconciliation processing and avoids potential risks and disputes.

[0131] In some alternative implementations, the user information obtained is subject to user consent and complies with relevant laws and policies.

[0132] Furthermore, any software tools or components not belonging to our company that appear in the embodiments of this application are merely illustrative examples and do not represent actual use.

[0133] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0134] It should be emphasized that, to further ensure the privacy and security of the above reconciliation results, the reconciliation results can also be stored in a node of a blockchain.

[0135] The blockchain referred to in this application is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked together using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying blockchain platform, a platform product service layer, and an application service layer.

[0136] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0137] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0138] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware with computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When executed, the program can include the processes of the embodiments of the above methods. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0139] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0140] Further reference Figure 3 As a response to the above Figure 2 To implement the method shown, this application provides an embodiment of a data reconciliation apparatus, which is similar to... Figure 2 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0141] like Figure 3 As shown, the data reconciliation device 300 described in this embodiment includes: a first acquisition module 301, a first processing module 302, a second processing module 303, a third processing module 304, a comparison module 305, an extraction module 306, and a first generation module 307. Wherein:

[0142] The first acquisition module 301 is used to acquire the business transaction data of the first transaction within a preset time period from a preset business backup database; wherein, the business backup database is a backup database of the business master database;

[0143] The first processing module 302 is used to calculate the cost of the first transaction based on the business transaction data and a preset billing rule model to obtain the corresponding first cost data, and to generate the first reconciliation data of the first transaction based on the business transaction data and the first cost data; wherein, the billing rule model is used to be called during the cost calculation and to perform corresponding condition judgments and calculation logic steps to complete the cost calculation process.

[0144] The second processing module 303 is used to obtain reconciliation data of the second transaction within a preset time period from a preset channel system, calculate the corresponding second fee data for the second transaction based on the reconciliation data and the billing rule model, and generate the second reconciliation data of the second transaction based on the reconciliation data and the second fee data.

[0145] The third processing module 304 is used to obtain first key data corresponding to a specified transaction from the first reconciliation data, determine a target transaction matching the specified transaction from the second transaction, and obtain second key data corresponding to the target transaction from the second reconciliation data; wherein, the specified transaction includes any one of the first transactions;

[0146] The comparison module 305 is used to compare the first key data with the second key data to determine whether the first key data and the second key data are consistent.

[0147] Extraction module 306 is used to extract third key data corresponding to the specified transaction from a preset business master database if the first key data is inconsistent with the second key data.

[0148] The first generation module 307 is used to compare the third key data with the second key data to generate a reconciliation result corresponding to the specified transaction.

[0149] In this embodiment, the operations performed by the above modules or units correspond one-to-one with the steps of the data reconciliation method in the aforementioned embodiments, and will not be repeated here.

[0150] In some optional implementations of this embodiment, the first acquisition module 301 includes:

[0151] A submodule is constructed to obtain a preset business transaction type and construct a corresponding data extraction script based on the business transaction type.

[0152] The extraction submodule is used to execute the data extraction script in the business backup database to extract the initial business transaction data within the preset time period;

[0153] The cleaning submodule is used to perform data cleaning processing on the initial business flow data to obtain the corresponding first data.

[0154] The processing submodule is used to format the first data to obtain the corresponding second data.

[0155] The first determining submodule is used to use the second data as the business transaction data.

[0156] In this embodiment, the operations performed by the above modules or units correspond one-to-one with the steps of the data reconciliation method in the aforementioned embodiments, and will not be repeated here.

[0157] In some optional implementations of this embodiment, the first processing module 302 includes:

[0158] The submodule is invoked to invoke the billing rule model;

[0159] The acquisition submodule is used to acquire the target billing rule that matches the first transaction based on the billing rule model.

[0160] The calculation submodule is used to apply the target billing rule to calculate the cost of the first transaction and obtain the corresponding cost calculation result.

[0161] The second determining submodule is used to use the cost calculation result as the first cost data of the first transaction.

[0162] In this embodiment, the operations performed by the above modules or units correspond one-to-one with the steps of the data reconciliation method in the aforementioned embodiments, and will not be repeated here.

[0163] In some optional implementations of this embodiment, the first generation module 307 includes:

[0164] The judgment submodule is used to compare the third key data with the second key data based on a preset comparison tool, and to determine whether the third key data and the second key data are consistent.

[0165] The first generation submodule is used to generate a first reconciliation result indicating that the specified transaction reconciliation is normal if the third key data is consistent with the second key data.

[0166] The second generation submodule is used to generate a second result of the specified transaction reconciliation anomaly if the third key data is inconsistent with the second key data.

[0167] In this embodiment, the operations performed by the above modules or units correspond one-to-one with the steps of the data reconciliation method in the aforementioned embodiments, and will not be repeated here.

[0168] In some optional implementations of this embodiment, the data reconciliation apparatus further includes:

[0169] The second acquisition module is used to acquire simulated transaction data corresponding to the billing rule model;

[0170] The first calling module is used to call the verification script corresponding to the billing rule model;

[0171] The verification module is used to run the verification script to verify the simulated transaction data and obtain the corresponding verification results;

[0172] The first judgment module is used to determine whether the verification result is a successful verification.

[0173] The deployment module is used to deploy the billing rule model if the condition is met.

[0174] In this embodiment, the operations performed by the above modules or units correspond one-to-one with the steps of the data reconciliation method in the aforementioned embodiments, and will not be repeated here.

[0175] In some optional implementations of this embodiment, the data reconciliation apparatus further includes:

[0176] The second calling module is used to call the preset reconciliation database;

[0177] The third acquisition module is used to acquire the preset data insertion strategy;

[0178] The storage module is used to store the first account reconciliation data into the reconciliation database based on the data insertion strategy.

[0179] In this embodiment, the operations performed by the above modules or units correspond one-to-one with the steps of the data reconciliation method in the aforementioned embodiments, and will not be repeated here.

[0180] In some optional implementations of this embodiment, the data reconciliation apparatus further includes:

[0181] The second judgment module is used to determine whether the reconciliation result is an abnormal reconciliation of the specified transaction.

[0182] The third acquisition module is used to acquire, if yes, the abnormal data corresponding to the specified transaction;

[0183] The second generation module is used to generate early warning information corresponding to the specified transaction based on the abnormal data;

[0184] The fourth acquisition module is used to acquire the notification method corresponding to the target business personnel;

[0185] The sending module is used to send the warning information to the target business personnel based on the notification method.

[0186] In this embodiment, the operations performed by the above modules or units correspond one-to-one with the steps of the data reconciliation method in the aforementioned embodiments, and will not be repeated here.

[0187] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0188] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected via a system bus. It should be noted that only the computer device 4 with components 41-43 is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0189] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0190] The memory 41 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 4. Of course, the memory 41 may also include both the internal storage unit and its external storage device of the computer device 4. In this embodiment, the memory 41 is typically used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions for data reconciliation methods. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or will be output.

[0191] In some embodiments, the processor 42 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to execute computer-readable instructions stored in the memory 41 or to process data, such as computer-readable instructions for executing the data reconciliation method.

[0192] The network interface 43 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 4 and other electronic devices.

[0193] This application also provides another embodiment, namely, providing a computer-readable storage medium storing computer-readable instructions that can be executed by at least one processor to cause the at least one processor to perform the steps of the data reconciliation method as described above.

[0194] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0195] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A method for data reconciliation, characterized in that, Includes the following steps: The business transaction log data of the first transaction within a preset time period is obtained from the preset business backup database; wherein, the business backup database is a backup database of the business master database; Based on the business transaction data and the preset billing rule model, the first transaction is calculated to obtain the corresponding first cost data, and the first reconciliation data of the first transaction is generated based on the business transaction data and the first cost data; wherein, the billing rule model is used to call and perform corresponding condition judgments and calculation logic steps when calculating costs to complete the cost calculation process; The system obtains reconciliation data of the second transaction within a preset time period from the preset channel system, calculates the corresponding second fee data based on the reconciliation data and the billing rule model, and generates the second reconciliation data of the second transaction based on the reconciliation data and the second fee data. First key data corresponding to a specified transaction is obtained from the first set of accounts to be reconciled, and a target transaction matching the specified transaction is determined from the second set of transactions. Second key data corresponding to the target transaction is obtained from the second set of accounts to be reconciled. The specified transaction is any one of the first transactions. The first key data and the second key data are compared to determine whether the first key data and the second key data are consistent. If the first key data is inconsistent with the second key data, then the third key data corresponding to the specified transaction is extracted from the preset business master database; The third key data is compared with the second key data to generate a reconciliation result corresponding to the specified transaction.

2. The data reconciliation method according to claim 1, characterized in that, The step of obtaining the business transaction data of the first transaction within a preset time period from the preset business backup database specifically includes: Obtain the preset business transaction type, and construct the corresponding data extraction script based on the business transaction type; The data extraction script is executed in the business backup database to extract the initial business transaction data within the preset time period; The initial business flow data is cleaned to obtain the corresponding first data; The first data is formatted to obtain the corresponding second data; The second data is used as the business transaction data.

3. The data reconciliation method according to claim 1, characterized in that, The step of calculating the corresponding first fee data for the first transaction based on the business transaction data and a preset billing rule model specifically includes: Invoke the aforementioned billing rule model; Based on the billing rule model, obtain the target billing rule that matches the first transaction; The first transaction is charged according to the target billing rule to obtain the corresponding charge calculation result. The calculated cost result is used as the first cost data for the first transaction.

4. The data reconciliation method according to claim 1, characterized in that, The step of comparing the third key data with the second key data to generate a reconciliation result corresponding to the specified transaction specifically includes: The third key data is compared with the second key data using a preset comparison tool to determine whether the third key data and the second key data are consistent. If the third key data is consistent with the second key data, then the first reconciliation result of the specified transaction reconciliation is generated; If the third key data is inconsistent with the second key data, a second result for the specified transaction reconciliation anomaly is generated.

5. The data reconciliation method according to claim 1, characterized in that, Before the step of calculating the cost of the first transaction based on the business transaction data and a preset billing rule model to obtain the corresponding first cost data, the method further includes: Obtain simulated transaction data corresponding to the billing rule model; Invoke the verification script corresponding to the billing rule model; Run the verification script to verify the simulated transaction data and obtain the corresponding verification results; Determine whether the verification result is a successful verification; If so, the billing rule model is deployed and processed.

6. The data reconciliation method according to claim 1, characterized in that, After the step of generating the first reconciliation data for the first transaction based on the business transaction data and the first expense data, the method further includes: Call the preset reconciliation database; Retrieve the preset data insertion strategy; Based on the data insertion strategy, the first account reconciliation data is stored in the reconciliation database.

7. The data reconciliation method according to claim 1, characterized in that, After the step of comparing the third key data with the second key data to generate a reconciliation result corresponding to the specified transaction, the method further includes: Determine whether the reconciliation result indicates an anomaly in the reconciliation of the specified transaction; If so, retrieve the abnormal data corresponding to the specified transaction; Based on the abnormal data, generate early warning information corresponding to the specified transaction; Obtain the notification method corresponding to the target business personnel; Based on the notification method, the warning information is sent to the target business personnel.

8. A data reconciliation device, characterized in that, include: The first acquisition module is used to acquire the business transaction data of the first transaction within a preset time period from a preset business backup database; wherein, the business backup database is a backup database of the business master database; The first processing module is used to calculate the cost of the first transaction based on the business transaction data and a preset billing rule model to obtain the corresponding first cost data, and to generate the first reconciliation data of the first transaction based on the business transaction data and the first cost data; wherein, the billing rule model is used to be invoked during the cost calculation and to perform corresponding condition judgments and calculation logic steps to complete the cost calculation process; The second processing module is used to obtain reconciliation data of the second transaction within a preset time period from a preset channel system, calculate the corresponding second fee data for the second transaction based on the reconciliation data and the billing rule model, and generate the second reconciliation data of the second transaction based on the reconciliation data and the second fee data. The third processing module is used to obtain first key data corresponding to a specified transaction from the first reconciliation data, determine a target transaction matching the specified transaction from the second transaction, and obtain second key data corresponding to the target transaction from the second reconciliation data; wherein, the specified transaction is any one of all the first transactions; The comparison module is used to compare the first key data with the second key data to determine whether the first key data and the second key data are consistent. The extraction module is used to extract the third key data corresponding to the specified transaction from a preset business master database if the first key data is inconsistent with the second key data. The first generation module is used to compare the third key data with the second key data to generate a reconciliation result corresponding to the specified transaction.

9. A computer device, characterized in that, The method includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the data reconciliation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-readable instructions that, when executed by a processor, implement the steps of the data reconciliation method as described in any one of claims 1 to 7.

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