Bill data processing method and device, electronic equipment and storage medium

Abstract

The invention provides a bill data processing method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. In the application, a bill data processing request from a target terminal is received, and target bill data and a user account checking requirement for the target bill data are acquired from the bill data processing request; then, generating a target account checking rule of the target bill data based on the account checking requirement of the user and associated historical decision data; wherein the historical decision data can comprise at least one historical reconciliation rule; and finally, performing data processing on the target bill data based on the target account checking rule to obtain a bill data processing result. By adopting the mode, excessive manual participation is not needed, and the intelligent level is relatively high, so that the bill data processing efficiency and accuracy are improved. In addition, the target reconciliation rule can be generated in a targeted manner according to the reconciliation requirement of the user, and different bill data processing requirements can be flexibly met.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a bill data processing method, device, electronic device and storage medium. Background Art

[0002] With the rapid growth of billing data in the production and operation of enterprises or institutions, effective management of billing data has become an important means or method to measure whether the enterprises or institutions are operating normally.

[0003] At present, the reconciliation process in the bill reconciliation system (or bill data processing system) mainly relies on traditional financial software and manual processing. For example, the bill data of the enterprise or institution can be manually or semi-automatically collected from different systems (or channels), and the collected bill data can be manually entered (e.g., batch imported) into the bill reconciliation system, and then the bill reconciliation system can be used to compare multiple items included in the bill data to detect abnormal items. Optionally, the comparison results can be manually checked to ensure the accuracy of the comparison results and obtain the final reconciliation report.

[0004] It can be seen that the above-mentioned bill data processing method requires a lot of manual participation and has a low level of intelligence, which leads to low accuracy of bill data processing and is prone to errors; in addition, the efficiency of data processing is low. Summary of the invention

[0005] The embodiments of the present application provide a bill data processing method, device, electronic device and storage medium to improve the efficiency and accuracy of bill data processing.

[0006] In a first aspect, an embodiment of the present application provides a bill data processing method, the method comprising:

[0007] Receiving a billing data processing request from a target terminal, and obtaining target billing data and a user reconciliation requirement for the target billing data from the billing data processing request;

[0008] Based on the user's account reconciliation requirement and its associated historical decision data, generating a target account reconciliation rule for the target bill data; wherein the historical decision data includes at least one historical account reconciliation rule;

[0009] The target billing data is processed based on the target reconciliation rules to obtain the billing data processing result.

[0010] In an optional embodiment, obtaining target billing data and a user reconciliation requirement for the target billing data from the billing data processing request includes:

[0011] Parse the billing data processing request to obtain the initial billing data and initial reconciliation requirements;

[0012] The initial billing data is sequentially converted into data format, cleaned and verified to obtain the target billing data, and the initial reconciliation requirements are standardized to obtain the user's reconciliation requirements.

[0013] In an optional embodiment, the method further includes:

[0014] During data cleaning of the initial bill data, if sub-bill data that meets preset abnormal data conditions is found in the initial bill data, the sub-bill data is marked as abnormal data and first information is sent to the target terminal; the first information is used to indicate that the sub-bill data is abnormal data.

[0015] In an optional embodiment, based on the user's account reconciliation requirement and its associated historical decision data, a target account reconciliation rule for target bill data is generated, including:

[0016] Parse the user's reconciliation requirements to obtain the user's reconciliation intention, and filter out historical decision data that matches the reconciliation intention from the historical database; wherein the reconciliation intention is used to indicate at least one data processing method required by the user for the target bill data;

[0017] A target reconciliation rule is generated based on the user reconciliation requirement and at least one historical reconciliation rule included in the historical decision data.

[0018] In an optional embodiment, data processing is performed on the target billing data based on the target reconciliation rule to obtain the billing data processing result, including:

[0019] Based on the data processing instructions corresponding to the target reconciliation rules, reconciliation processing is performed on the multiple sub-bill data included in the target bill data respectively to obtain multiple reconciliation processing results; wherein each reconciliation processing result represents: whether the corresponding sub-bill data is abnormal sub-bill data;

[0020] Based on the multiple reconciliation processing results and the abnormal information respectively corresponding to at least one abnormal sub-bill data included in the multiple sub-bill data, a bill data processing result is obtained.

[0021] In an optional embodiment, after obtaining multiple reconciliation processing results, the method further includes:

[0022] For multiple reconciliation results, perform the following operations respectively:

[0023] If the first reconciliation result indicates that the first sub-bill data corresponding to the first reconciliation result is abnormal sub-bill data, obtaining the location information of the first sub-bill data in the target bill data, as well as the abnormal description and abnormal reason of the first sub-bill data; wherein the first reconciliation result is any one of the multiple reconciliation processing results;

[0024] Based on the location information, exception description and exception reason of the first sub-bill data, the exception information of the first sub-bill data is generated.

[0025] In an optional embodiment, after the target billing data is processed based on the target reconciliation rule and the billing data processing result is obtained, the method further includes:

[0026] Send billing data processing results to the target terminal;

[0027] Receive feedback information returned by the target terminal based on the bill data processing result; the feedback information is used to modify the target reconciliation rule to obtain the modified target reconciliation rule.

[0028] In a second aspect, an embodiment of the present application further provides a bill data processing device, the device comprising:

[0029] The transceiver module is used to receive a billing data processing request from a target terminal, and obtain target billing data and a user reconciliation requirement for the target billing data from the billing data processing request;

[0030] A generating module, configured to generate a target reconciliation rule for target billing data based on a user reconciliation requirement and its associated historical decision data; wherein the historical decision data includes at least one historical reconciliation rule;

[0031] The processing module is used to process the target bill data based on the target reconciliation rule to obtain the bill data processing result.

[0032] In an optional embodiment, when obtaining the target billing data and the user reconciliation requirement for the target billing data from the billing data processing request, the transceiver module is specifically used to:

[0033] Parse the billing data processing request to obtain the initial billing data and initial reconciliation requirements;

[0034] The initial billing data is sequentially converted into data format, cleaned and verified to obtain the target billing data, and the initial reconciliation requirements are standardized to obtain the user's reconciliation requirements.

[0035] In an optional embodiment, the transceiver module is further used for:

[0036] During data cleaning of the initial bill data, if sub-bill data that meets preset abnormal data conditions is found in the initial bill data, the sub-bill data is marked as abnormal data and first information is sent to the target terminal; the first information is used to indicate that the sub-bill data is abnormal data.

[0037] In an optional embodiment, when generating a target reconciliation rule for target bill data based on the user reconciliation requirement and its associated historical decision data, the generating module is specifically configured to:

[0038] Parse the user's reconciliation requirements to obtain the user's reconciliation intention, and filter out historical decision data that matches the reconciliation intention from the historical database; wherein the reconciliation intention is used to indicate at least one data processing method required by the user for the target bill data;

[0039] A target reconciliation rule is generated based on the user reconciliation requirement and at least one historical reconciliation rule included in the historical decision data.

[0040] In an optional embodiment, when data processing is performed on the target bill data based on the target reconciliation rule to obtain the bill data processing result, the processing module is specifically used to:

[0041] Based on the data processing instructions corresponding to the target reconciliation rules, reconciliation processing is performed on the multiple sub-bill data included in the target bill data respectively to obtain multiple reconciliation processing results; wherein each reconciliation processing result represents: whether the corresponding sub-bill data is abnormal sub-bill data;

[0042] Based on the multiple reconciliation processing results and the abnormal information respectively corresponding to at least one abnormal sub-bill data included in the multiple sub-bill data, a bill data processing result is obtained.

[0043] In an optional embodiment, after obtaining multiple reconciliation processing results, the processing module is further used to:

[0044] For multiple reconciliation results, perform the following operations respectively:

[0045] If the first reconciliation result indicates that the first sub-bill data corresponding to the first reconciliation result is abnormal sub-bill data, obtaining the location information of the first sub-bill data in the target bill data, as well as the abnormal description and abnormal reason of the first sub-bill data; wherein the first reconciliation result is any one of the multiple reconciliation processing results;

[0046] Based on the location information, exception description and exception reason of the first sub-bill data, the exception information of the first sub-bill data is generated.

[0047] In an optional embodiment, after processing the target bill data based on the target reconciliation rule to obtain the bill data processing result, the transceiver module is further used to:

[0048] Send billing data processing results to the target terminal;

[0049] Receive feedback information returned by the target terminal based on the bill data processing result; the feedback information is used to modify the target reconciliation rule to obtain the modified target reconciliation rule.

[0050] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0051] Processor; and

[0052] Memory for storing programs,

[0053] The program includes instructions, which, when executed by a processor, cause the processor to execute the bill data processing method as described in the first aspect.

[0054] In a fourth aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the bill data processing method as described in the first aspect.

[0055] In a fifth aspect, the present application provides a computer program product, which, when called by a computer, enables the computer to execute the steps of the bill data processing method as described in the first aspect.

[0056] The beneficial effects of this application are as follows:

[0057] In the bill data processing method provided in the embodiment of the present application, after receiving a bill data processing request from a target terminal and obtaining the target bill data (i.e., the bill data to be processed) and the user reconciliation requirements for the target bill data from the bill data processing request, a target reconciliation rule for the target bill data can be generated based on the user reconciliation requirements and at least one historical reconciliation rule included in the associated historical decision data, thereby performing data processing on the target bill data based on the target reconciliation rule to obtain a bill data processing result. In this way, since there is no need for excessive manual participation and the level of intelligence is high, the efficiency and accuracy of bill data processing are improved. In addition, the target reconciliation rules can be generated in a targeted manner according to the user reconciliation requirements, and different bill data processing requirements can be flexibly adapted.

[0058] In addition, other features and advantages of the present application will be described in the subsequent description, and partly become apparent from the description, or be understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described here are used to provide a further understanding of the present application, constitute a part of the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0060] Figure 1 A schematic diagram of an optional system architecture applicable to the embodiments of the present application;

[0061] Figure 2 A schematic diagram of an implementation flow of a bill data processing method provided in an embodiment of the present application;

[0062] Figure 3 A logical diagram of generating a target reconciliation rule provided in an embodiment of the present application;

[0063] Figure 4 A modular schematic diagram of bill data processing based on an AI-Agent system provided in an embodiment of the present application;

[0064] Figure 5 A schematic diagram of the composition structure of an AI-Agent system provided in an embodiment of the present application;

[0065] Figure 6 A schematic diagram of the structure of a bill data processing device provided in an embodiment of the present application;

[0066] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0067] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be construed as being limited to the embodiments described herein. Instead, these embodiments are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes and are not intended to limit the scope of protection of the present application.

[0068] It should be understood that the various steps described in the method implementation of the present application can be performed in different orders and / or performed in parallel. In addition, the method implementation may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this respect.

[0069] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0070] It should be noted that the modifications of "one" and "plurality" mentioned in the present application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0071] The names of the messages or information exchanged between multiple devices in the embodiments of the present application are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0072] Some of the terms used in the embodiments of the present application are explained below to facilitate understanding by those skilled in the art.

[0073] (1) Artificial intelligence agent (AI-Agent): also known as artificial intelligence entity, refers to an autonomous program or system based on AI technology that can simulate human behavior and complete specific tasks through perception, understanding and decision-making. AI-Agent usually has the capabilities of data processing, learning, reasoning, planning, etc., and can respond to input information in a given environment and perform corresponding operations. Its core purpose is to improve the efficiency and accuracy of task processing through intelligent analysis and automated execution without human intervention.

[0074] (2) Natural Language Processing (NLP): It is an interdisciplinary field that combines knowledge from multiple disciplines such as computer science, artificial intelligence, and linguistics, aiming to enable computers to understand, interpret, and generate human language. NLP includes two parts: Natural Language Understanding (NLU) and Natural Language Generation (NLG). Among them, NLU is used to convert human language into a machine - understandable format for AI analysis; NLG is used to convert non - language - formatted data into a human - understandable language format.

[0075] (3) Reconciliation: That is, checking accounts. It refers to the work of checking and verifying relevant data in the accounts in accounting to ensure the correct and reliable records in the books.

[0076] (4) Structured Information: It refers to information that can be decomposed into multiple interrelated components after analysis. There is a clear hierarchical structure among the components, and its use and maintenance are managed through a database and have certain operation specifications. Exemplarily, taking the information managed by a database as an example, records in aspects such as production information, business information, transaction information, and customer information all belong to structured information.

[0077] Based on the above explanations of nouns and related terms, the design concept of the embodiments of this application is briefly introduced below:

[0078] In the current bill reconciliation system, the reconciliation process mainly relies on traditional financial software and manual processing. First, bill data can be collected manually or semi - automatically from different systems and channels, and the collected bill data can be manually entered into the bill reconciliation system, for example, imported into the bill reconciliation system in batches. Then, on the bill reconciliation system, multiple items included in the bill data can be compared to check for abnormal items. Further, the comparison results can be manually checked and confirmed to ensure the accuracy of the comparison results. Finally, a reconciliation report can be generated based on the comparison results for subsequent audit reference.

[0079] It can be seen that the existing bill reconciliation system requires a large amount of manual participation. In this way, during the process of data collection and verification, it is easy to cause errors, inaccuracies, and low efficiency, that is, there is a lot of manual intervention; moreover, there is a lack of intelligent analysis of bill data. Therefore, using the above - mentioned bill data processing method, the efficiency and accuracy of bill data processing are relatively low.

[0080] In view of this, in order to solve or improve the above problems, the embodiment of the present application provides a bill data processing method, which may specifically include: receiving a bill data processing request from a target terminal, and obtaining target bill data and user reconciliation requirements for the target bill data from the bill data processing request; generating target reconciliation rules for the target bill data based on the user reconciliation requirements and their associated historical decision data; wherein the historical decision data includes at least one historical reconciliation rule; and performing data processing on the target bill data based on the target reconciliation rule to obtain a bill data processing result. Since there is no need for excessive manual participation and the level of intelligence is high, the efficiency and accuracy of bill data processing are improved.

[0081] In addition, target reconciliation rules can be generated specifically according to user reconciliation requirements, which can flexibly adapt to the billing data processing requirements of different enterprises or institutions, thereby improving the existing billing data processing system, which usually requires repeated adjustments to meet customized needs and cannot quickly adapt to the changing business needs and complex reconciliation rules of different enterprises or institutions.

[0082] In particular, the preferred embodiments of the present application are described below in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application, and the embodiments of the present application and the features in the embodiments may be combined with each other if there is no conflict.

[0083] See also Figure 1 As shown, it is a schematic diagram of a system architecture applicable to an embodiment of the present application, and the system architecture may include: a target terminal (101a, 101b) and a server 102. The target terminal (101a, 101b) and the server 102 may exchange information through a communication network, wherein the communication mode adopted by the communication network may include: a wireless communication mode and a wired communication mode. Exemplarily, the target terminal (101a, 101b) may access the network through cellular mobile communication technology and communicate with the server 102. Wherein, the cellular mobile communication technology, for example, includes the fifth generation mobile communication (5th generation mobile networks, 5G) technology or the next generation mobile communication technology. Optionally, the target terminal (101a, 101b) may access the network through a short-range wireless communication mode and communicate with the server 102. Wherein, the short-range wireless communication mode, for example, includes wireless fidelity (wireless fidelity, Wi-Fi) technology.

[0084] The embodiment of the present application does not impose any restriction on the number of communication devices involved in the above system architecture. For example, the above system architecture may include more target terminals, or fewer target terminals, or other network devices. Figure 1 As shown, only the target terminal (101a, 101b) and the server 102 are described as examples, and the above-mentioned communication devices and their respective functions are briefly introduced below.

[0085] The target terminal (101a, 101b) is a device that can provide voice and / or data connectivity to users, and can be a device that supports wired and / or wireless connection.

[0086] Exemplarily, the target terminal (101a, 101b) may include, but is not limited to: mobile phones, tablet computers, laptop computers, PDAs, mobile internet devices (MID), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminal devices in industrial control, wireless terminal devices in unmanned driving, wireless terminal devices in smart grids, wireless terminal devices in transportation safety, wireless terminal devices in smart cities, or wireless terminal devices in smart homes, etc.

[0087] In addition, the target terminal (101a, 101b) may be installed with a relevant client, which may be software, such as an application (APP), a browser, a short video software, etc., and of course, a web page, a small program, etc. It should be noted that the target terminal (101a, 101b) in the embodiment of the present application may enable the above-mentioned client related to bill data processing to send a bill data processing request for the target bill data to the server 102, so as to subsequently perform the method steps such as intelligent bill data processing for the aforementioned target bill data.

[0088] Server 102 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also 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 (CDNs), and big data and artificial intelligence platforms.

[0089] It is worth mentioning that in an embodiment of the present application, the server 102 can be used to receive a bill data processing request from a target terminal (101a, 101b), and obtain the target bill data and the user reconciliation requirements for the target bill data from the bill data processing request; then, based on the user reconciliation requirements and their associated historical decision data, generate target reconciliation rules for the target bill data; wherein the historical decision data may include at least one historical reconciliation rule; finally, the target bill data is processed based on the target reconciliation rules to obtain the bill data processing results.

[0090] The following describes the bill data processing method provided by the exemplary embodiment of the present application in combination with the above-mentioned system architecture and with reference to the accompanying drawings. It should be noted that the above-mentioned system architecture is only shown to facilitate understanding of the spirit and principles of the present application, and the implementation of the present application is not limited in this regard.

[0091] See also Figure 2 As shown, it is a schematic diagram of an implementation process of a bill data processing method provided in an embodiment of the present application. The execution subject takes a server as an example. The specific implementation process of the method is as follows:

[0092] S201: receiving a billing data processing request from a target terminal, and obtaining target billing data and a user reconciliation requirement for the target billing data from the billing data processing request.

[0093] The above-mentioned bill data request may be generated according to the relevant operation on the application side related to bill data processing deployed by the user on the target terminal (i.e., the user's reconciliation requirement for the target bill data). That is, the user can define the bill data processing method (i.e., the reconciliation process) for the target bill data according to his own needs on the application side of the target terminal.

[0094] It is understandable that the above-mentioned application end can be deployed on the target terminal. Of course, the above-mentioned application end can also be deployed on the server, and the embodiment of the present application does not specifically limit this. The above-mentioned application end is only an interface for interaction between the user and the billing data processing system (for example, AI-Agent system) on the server.

[0095] Exemplarily, the user can set at least one data processing method for the target bill data on the application side. For example, the aforementioned at least one data processing method is used to guide or control how the bill data processing system on the server compares the transaction amount, date, transaction object and other information in the target bill data, that is, how to analyze and check the target bill data to meet the user's bill data processing needs. In addition, the user can also set business parameters related to the aforementioned bill data processing requirements on the application side, for example, select the billing cycle, account type and fault tolerance range of the reconciliation, etc., to ensure that the bill data processing system can more accurately meet the user's personalized needs for bill data processing, thereby avoiding unnecessary error detection or missed detection. In addition, the user can also upload the target bill data on the application side and set the analysis requirements for the target bill data. For example, the aforementioned analysis requirements may include but are not limited to: detecting abnormal transactions, counting bill types, identifying duplicate bills, etc. Optionally, the user can also select the type of bill data processing results (i.e., analysis reports) generated subsequently to discover potential problems with the target bill data.

[0096] In this way, after receiving the bill data processing request from the target terminal, the server can use the bill data processing request as a basis for subsequent intelligent processing of the target bill data.

[0097] In an optional implementation, when executing step S201, after receiving the aforementioned bill data processing request, the server can parse the aforementioned bill data processing request to obtain initial bill data and initial reconciliation requirements, thereby successively performing data format conversion, data cleaning and data verification on the initial bill data to obtain target bill data, and standardizing the initial reconciliation requirements to obtain user reconciliation requirements.

[0098] The above data format conversion can convert the initial bill data provided by the user from an unstructured data format or a semi-structured data format (such as PDF bills, Excel tables, text files, etc.) to a standard structured data format (such as JSON format or database tables, etc.). In this way, the uniformity and standardization of the data format are ensured, which facilitates the subsequent data processing of the target bill data, and thus improves the data processing efficiency to a certain extent.

[0099] In other words, the server may perform data format conversion on the above-mentioned initial billing data based on a preset structured data format to obtain the initial billing data after data format conversion.

[0100] The above data cleaning can remove invalid information in the initial bill data after the data format conversion. The aforementioned invalid information may include blank fields and repeated data, etc., which is not specifically limited in the embodiment of the present application.

[0101] That is, the server can remove the invalid information in the initial bill data after data format conversion based on a preset data cleaning method, so as to obtain the initial bill data after data cleaning. By adopting this method, the data that does not meet the requirements (i.e., invalid information) in the initial bill data after data format conversion can be effectively filtered out, thereby improving the accuracy of the data, and further ensuring the data quality of the target bill data used for bill data subsequently.

[0102] The above data verification process is used to perform specific data format verification on the initial bill data after data cleaning to achieve data consistency. For example, the foregoing specific data format verification may include: unifying the date format, converting the currency unit, etc. That is, the server can perform data verification processing on the initial bill data after data cleaning based on a preset data verification method, so as to obtain the initial bill data after data verification (i.e., the target bill data).

[0103] Exemplarily, after the server obtains the initial reconciliation requirements (including at least one data processing method, business parameters, analysis requirements, etc.) set by the user on the application side, it can convert the initial reconciliation requirements into an instruction format that the bill data processing system can understand, standardize (or normalize) the expression of the initial reconciliation requirements, so as to obtain the user reconciliation requirements, so as to ensure that the processing requirements of the user for the target bill data can be accurately executed during the data processing stage.

[0104] In an alternative implementation, during the process of data cleaning of the initial bill data, if the server finds that there is sub-bill data in the initial bill data that meets the preset abnormal data conditions, the foregoing sub-bill data can be marked as abnormal data, and a first message can be sent to the target terminal. Among them, the foregoing first message can be used to indicate that the foregoing sub-bill data is marked as abnormal data. The foregoing abnormal data conditions may include data format errors, data incompleteness, etc.

[0105] Based on the above method, once it is determined that there is abnormal sub-bill data in the initial bill data according to the above preset abnormal data conditions, these abnormal data can be marked and fed back to the application side, that is, error detection and feedback are realized, so that the user can correct the data input in time, reduce problems in subsequent processing, and thus improve the accuracy of bill data processing.

[0106] Thus, through data format conversion, data cleaning and data verification of the initial bill data, as well as standardization processing of the initial reconciliation requirements, the high-quality input of the target bill data and the user reconciliation requirements is ensured, laying a foundation for subsequent intelligent processing of the target bill data.

[0107] S202: Generate target reconciliation rules for target bill data based on the user reconciliation requirements and the associated historical decision data.

[0108] The above-mentioned historical decision data may include at least one historical reconciliation rule related to the user's reconciliation requirement.

[0109] In an optional implementation, when executing step S202, refer to Figure 3 As shown, after obtaining the user's reconciliation request, the server can parse the user's reconciliation request, obtain the user's reconciliation intention, and filter out historical decision data that matches the reconciliation intention from the historical database, thereby generating a target reconciliation rule based on the user's reconciliation request and at least one historical reconciliation rule included in the historical decision data. Among them, the aforementioned reconciliation intention can be used to indicate at least one data processing method for the target bill data required by the user. Exemplarily, the aforementioned reconciliation intention may include: "Compare transaction amounts", "Find abnormal bill sub-data (or abnormal entries)" or "Transaction matching", etc.

[0110] Based on the above method, after the server has deeply understood and analyzed the user's reconciliation requirements and identified the user's reconciliation intention, it can combine the historical database to determine the historical decision data related to the reconciliation intention, and then formulate specific reconciliation rules (i.e., target reconciliation rules) based on the user's reconciliation requirements and the historical decision data obtained to ensure that the subsequent bill data processing results meet user requirements.

[0111] S203: Process the target bill data based on the target reconciliation rule to obtain a bill data processing result.

[0112] In an optional implementation, when executing step S203, the server can perform reconciliation processing on multiple sub-bill data included in the target bill data based on the data processing instructions corresponding to the target reconciliation rule, and obtain multiple reconciliation processing results. Each reconciliation processing result can represent whether the corresponding sub-bill data is abnormal sub-bill data. Then, the server can obtain the bill data processing result based on the multiple reconciliation processing results and the abnormal information corresponding to at least one abnormal sub-bill data included in the multiple sub-bill data.

[0113] Taking the example that the target bill data includes 100 sub-bill data (or items), the server can perform reconciliation processing on the aforementioned 100 sub-bill data based on the target reconciliation rules to obtain the reconciliation processing results of each of the 100 sub-bill data. These 100 reconciliation processing results can determine the number of normal sub-bill data and the number of abnormal sub-bill data included in the 100 sub-bill data. After determining the number of normal sub-bill data and the number of abnormal sub-bill data included in the 100 sub-bill data, the server can obtain the bill data processing result based on the 100 reconciliation processing results and the abnormal information corresponding to at least one abnormal sub-bill data included in the 100 sub-bill data. Optionally, the aforementioned bill data processing result may include: whether the 100 sub-bill data are normal sub-bill data or abnormal sub-bill data, and the abnormal information corresponding to the abnormal sub-bill data.

[0114] Among them, each abnormal information may include but is not limited to: the location information of the corresponding sub-bill data in the target data bill (ie, the location of the sub-bill data), the abnormal description of the sub-bill data and the abnormal reason of the sub-bill data.

[0115] Therefore, in an optional implementation method, after obtaining the reconciliation processing results corresponding to the multiple sub-bill data included in the target bill data, the server can perform the following operations for any one of the multiple reconciliation processing results, for example, the first reconciliation processing result: If the first reconciliation result indicates that the first sub-bill data corresponding to the first reconciliation result is abnormal sub-bill data, the location information of the first sub-bill data in the target bill data, as well as the abnormal description and abnormal reason of the first sub-bill data can be obtained, thereby generating abnormal information of the first sub-bill data based on the location information, abnormal description and abnormal reason of the first sub-bill data.

[0116] In order to facilitate users to view, download or further process, the server processes the target bill data based on the target reconciliation rules, and after obtaining the bill data processing results, it can send the bill data processing results to the target terminal. Optionally, the server can also format the target bill data to generate reports and data that can be displayed by the target terminal.

[0117] In addition, after viewing the bill data processing result, the user can also feedback the user's feedback information to the server through the target terminal, that is, the server can receive the feedback information returned by the target terminal based on the bill data processing result. The feedback information may include the user's correction result or review result of the bill data processing result, and the feedback information may be used to modify the target reconciliation rule to obtain the modified target reconciliation rule.

[0118] In this way, by optimizing the data processing capabilities of the billing data processing system through user feedback information, the reconciliation accuracy, intelligence level and processing efficiency of the billing data processing system can be continuously improved.

[0119] Based on the bill data processing method described in steps S201 to S203 above, taking the bill data processing system as an AI-Agent system as an example, refer to Figure 4 As shown in the figure, the AI-Agent system can realize the intelligent processing of target bill data and the display of bill data processing results (i.e., reconciliation results) through the interaction of six core modules: application end, agent input module, perception layer, brain layer, action layer, and agent output module. Among them, the application end is the interface for interaction between users and the AI-Agent system, which is mainly used to collect and transmit users' reconciliation requirements. Users can define user reconciliation requirements for target bill data on the application end, which may include: setting at least one data processing method for target bill data, business parameters with the effect of user bill data processing requirements, and analysis requirements for target bill data. After receiving the user's input, the application end can send the bill data processing request for the target bill data to the Agent input module as the basis for subsequent intelligent processing of the target bill data. In addition, the application end is also responsible for displaying the final reconciliation result (i.e., bill data processing result) to the user, so that the user can quickly obtain the bill data processing result (i.e., the analysis report of the target bill data) and feedback on the target bill data, thereby realizing intelligent bill management.

[0120] The Agent input module is a key link in the data preprocessing of the AI-Agent system. It is mainly responsible for the preliminary processing and formatting of the initial reconciliation requirements and initial billing data transmitted by the application end, so as to obtain the user's reconciliation requirements and target billing data to lay the foundation for subsequent intelligent processing. The core tasks of the Agent input module can include: performing data format conversion, data request and verification, error detection and feedback on the initial billing data to obtain the target billing data; and performing user reconciliation requirements analysis and standardized processing on the initial billing data to obtain the user's reconciliation requirements.

[0121] It can be seen that the Agent input module ensures the high-quality input of the initial reconciliation requirements and initial bill data, so that the perception layer of the AI-Agent system can smoothly receive and process this information and achieve the best effect of the reconciliation operation.

[0122] The perception layer is the core data processing module of the AI-Agent system, responsible for receiving the target bill data and user reconciliation requirements transmitted by the Agent input module, and parsing and analyzing them. Exemplarily, the work performed by the perception layer may include: 1. Parsing user reconciliation requirements: The perception layer can use NLP technology to parse the user's reconciliation requirements, identify the user's reconciliation intentions and specific needs, and thus form operational instructions that can be understood by the AI-Agent system. 2. Data extraction of target bill data: The perception layer identifies and extracts key information such as amount, date, and transaction object from the target bill data. 3. Structured conversion: The perception layer can convert the parsed user reconciliation requirements and the target bill data after data extraction into structured information, and pass the structured information to the brain layer.

[0123] The brain layer is the intelligent decision-making center of the AI-Agent system, and has intelligent processing capabilities such as intent understanding, memory retrieval, reasoning and planning. Specifically, the brain layer can complete the following tasks: a. Intention understanding and demand analysis: Based on the user needs (i.e., user reconciliation requirements) transmitted by the perception layer, the brain layer conducts in-depth understanding and analysis to identify the user's reconciliation intentions, such as "comparing transaction amounts" and "finding abnormal entries". b. Memory retrieval: The brain layer can retrieve historical data and decision records (i.e., historical decision data) related to the current user reconciliation requirements from historical data as one of the basis for this decision. c. Reasoning and planning: Based on user needs and the results of memory retrieval, a specific reconciliation plan and data processing plan (i.e., target reconciliation rules) are formulated to ensure that the reconciliation results meet user requirements. d. Instruction generation: The brain layer converts the generated target reconciliation plan into data processing instructions and sends them to the action layer, instructing the action layer how to process the target bill data.

[0124] The action layer can be responsible for executing the data processing instructions of the brain layer and reconciling the target bill data. Exemplarily, the specific steps include: A. Data acquisition: Obtain the required reconciliation items from the target bill data, that is, select specific fields or data blocks according to the data processing instructions of the brain layer to ensure the accuracy of the reconciliation data. B. Data processing and comparison: Compare, calculate and analyze the selected sub-bill data (i.e., reconciliation items) according to the data processing instructions of the brain layer to identify whether the sub-bill data is abnormal sub-bill data. This process may include: amount comparison, date verification, transaction matching, etc. C. Processing feedback: If abnormal or inconsistent sub-bill data is detected during the reconciliation process, the action layer will record and feedback these abnormal sub-bill data, marking potential errors or risks.

[0125] The Agent output module is the final output module of the AI-Agent system, which is responsible for formatting the bill data processing results and returning them to the application side for users to view. The main tasks may include: 1). Result formatting: The Agent output formats the reconciliation processing results processed by the action layer and generates reports and data that can be displayed by the application side. 2). Abnormal marking and report generation: For abnormal sub-bill data detected, the Agent output module will generate a detailed abnormal report, which may include the description, location and possible causes of the abnormal sub-bill data, to facilitate subsequent processing by users. 3). Result delivery: The final reconciliation processing results and abnormality reports (i.e., bill data processing results) are delivered to the application side for users to view, download or further process.

[0126] Based on the above method, the NLP technology of the AI-Agent system can intelligently perceive, parse and understand the user's reconciliation requirements. The AI-Agent system analyzes and identifies the natural language instructions (i.e., the initial reconciliation requirements) input by the user, and can automatically generate corresponding reconciliation rules and operations, reduce the formatting requirements for user input, and improve the flexibility and adaptability of bill data processing. This NLP-based intelligent processing technology can quickly respond to the user's reconciliation requirements, improve the ease of use and intelligence level of the reconciliation system. In addition, the Agent technology is deeply applied to the billing business process to realize the automatic collection, processing and verification of bill data. Moreover, the bill data is automatically collected and cleaned according to the reconciliation rules set by the user, and the data is formatted and verified, which greatly reduces the necessity of manual participation. Therefore, the efficiency and accuracy of the billing system are improved, the labor cost and time cost are saved, and the needs of enterprises and institutions for efficient reconciliation are met.

[0127] In addition, the AI-Agent system also has the function of intelligent analysis and prediction of target billing data. That is, through deep learning of historical billing data and reconciliation results (i.e. historical decision data), the AI-Agent system can predict potential problems in the reconciliation process of target billing data and identify possible abnormal transactions or data anomalies (i.e. abnormal sub-bill data). Optionally, the AI-Agent system can also provide optimization suggestions to help users make more informed choices in billing data processing.

[0128] Therefore, in an optional implementation, see Figure 5 As shown in Figure 1, the AI-Agent system can include three parts: application layer (i.e., application end), Agent, and billing data layer. The AI-Agent system can be implemented as follows: Figure 5The system closed-loop feedback is shown in Figure 1. Moreover, after the user views and confirms the bill data processing results presented by the application layer, the AI-Agent system can optimize the decision-making module of the brain layer and the data processing capabilities of the perception layer based on the user's feedback information. In this way, through continuous feedback and learning, the AI-Agent system will continue to improve the accuracy, intelligence level and processing efficiency of reconciliation.

[0129] In summary, the existing bill reconciliation system has problems such as low efficiency, much manual intervention, poor flexibility and lack of intelligence. The bill data processing method of AI-Agent reduces the manual participation in data collection, comparison and anomaly detection in bill data processing, significantly reduces the error rate and the need for manual intervention, and thus improves the overall reconciliation efficiency and accuracy. The existing bill reconciliation system cannot quickly adapt to complex and changing business needs. By using AI-Agent to support custom reconciliation rules, it can flexibly adapt to the special needs of different enterprises and institutions, and improve the versatility and adaptability of the bill reconciliation system. The traditional bill reconciliation system lacks deep insight into bill data. AI-Agent can realize automatic comparison, intelligent matching and anomaly detection of bill data, quickly identify bill anomalies and potential risks, and reduce reliance on manual review. Through AI-Agent's automated execution of bill data collection, analysis, comparison, anomaly detection and report generation, the processing time of bill reconciliation is significantly shortened, labor costs are saved, and the processing efficiency of the overall bill reconciliation system is improved.

[0130] In summary, in the bill data processing method provided in the embodiment of the present application, after receiving the bill data processing request from the target terminal and obtaining the target bill data (i.e., the bill data to be processed) and the user reconciliation requirements for the target bill data from the bill data processing request, the target reconciliation rules for the target bill data can be generated based on the user reconciliation requirements and at least one historical reconciliation rule included in the associated historical decision data, thereby performing data processing on the target bill data based on the target reconciliation rules to obtain the bill data processing results. In this way, since there is no need for excessive manual participation and the level of intelligence is high, the efficiency and accuracy of bill data processing are improved. In addition, the target reconciliation rules can be generated in a targeted manner according to the user reconciliation requirements, and different bill data processing requirements can be flexibly adapted.

[0131] Further, based on the same technical concept, the embodiment of the present application provides a bill data processing device, which is used to implement the above method flow of the embodiment of the present application. Figure 6 As shown, the bill data processing device 600 may include: a transceiver module 601, a generation module 602 and a processing module 603, wherein:

[0132] The transceiver module 601 is used to receive a billing data processing request from a target terminal, and obtain target billing data and a user reconciliation requirement for the target billing data from the billing data processing request;

[0133] A generating module 602, configured to generate a target reconciliation rule for target billing data based on a user reconciliation requirement and its associated historical decision data; wherein the historical decision data includes at least one historical reconciliation rule;

[0134] The processing module 603 is used to process the target bill data based on the target reconciliation rule to obtain the bill data processing result.

[0135] In an optional embodiment, when obtaining the target billing data and the user reconciliation requirement for the target billing data from the billing data processing request, the transceiver module 601 is specifically used to:

[0136] Parse the billing data processing request to obtain the initial billing data and initial reconciliation requirements;

[0137] The initial billing data is sequentially converted into data format, cleaned and verified to obtain the target billing data, and the initial reconciliation requirements are standardized to obtain the user's reconciliation requirements.

[0138] In an optional embodiment, the transceiver module 601 is further used for:

[0139] During data cleaning of the initial bill data, if sub-bill data that meets preset abnormal data conditions is found in the initial bill data, the sub-bill data is marked as abnormal data and first information is sent to the target terminal; the first information is used to indicate that the sub-bill data is abnormal data.

[0140] In an optional embodiment, when generating a target reconciliation rule for target bill data based on the user reconciliation requirement and its associated historical decision data, the generating module 602 is specifically configured to:

[0141] Parse the user's reconciliation requirements to obtain the user's reconciliation intention, and filter out historical decision data that matches the reconciliation intention from the historical database; wherein the reconciliation intention is used to indicate at least one data processing method required by the user for the target bill data;

[0142] A target reconciliation rule is generated based on the user reconciliation requirement and at least one historical reconciliation rule included in the historical decision data.

[0143] In an optional embodiment, when the target billing data is processed based on the target reconciliation rule to obtain the billing data processing result, the processing module 603 is specifically used to:

[0144] Based on the data processing instructions corresponding to the target reconciliation rules, reconciliation processing is performed on the multiple sub-bill data included in the target bill data respectively to obtain multiple reconciliation processing results; wherein each reconciliation processing result represents: whether the corresponding sub-bill data is abnormal sub-bill data;

[0145] Based on the multiple reconciliation processing results and the abnormal information respectively corresponding to at least one abnormal sub-bill data included in the multiple sub-bill data, a bill data processing result is obtained.

[0146] In an optional embodiment, after obtaining multiple reconciliation processing results, the processing module 603 is further used to:

[0147] For multiple reconciliation results, perform the following operations respectively:

[0148] If the first reconciliation result indicates that the first sub-bill data corresponding to the first reconciliation result is abnormal sub-bill data, obtaining the location information of the first sub-bill data in the target bill data, as well as the abnormal description and abnormal reason of the first sub-bill data; wherein the first reconciliation result is any one of the multiple reconciliation processing results;

[0149] Based on the location information, exception description and exception reason of the first sub-bill data, the exception information of the first sub-bill data is generated.

[0150] In an optional embodiment, after processing the target bill data based on the target reconciliation rule to obtain the bill data processing result, the transceiver module 601 is further used to:

[0151] Send billing data processing results to the target terminal;

[0152] Receive feedback information returned by the target terminal based on the bill data processing result; the feedback information is used to modify the target reconciliation rule to obtain the modified target reconciliation rule.

[0153] Based on the description of the above method embodiment and device embodiment, the exemplary embodiment of the present invention further provides an electronic device, including: at least one processor; and a memory connected to the at least one processor in communication. The memory stores a computer program that can be executed by the at least one processor, and the computer program is used to enable the electronic device to perform the method according to the embodiment of the present invention when executed by the at least one processor.

[0154] An embodiment of the present application also provides a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to execute a method according to an embodiment of the present application.

[0155] An embodiment of the present application also provides a computer program product, including a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to execute a method according to an embodiment of the present application.

[0156] See also Figure 7 As shown, the structured block diagram of the electronic device 700 that can be used as the server or client of the present application will now be described, which is an example of the hardware device that can be applied to various aspects of the present application. The electronic device is intended to represent the computer device of various forms of digital electronics, such as, laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processing, cellular phones, smart phones, wearable devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only used as examples, and are not intended to limit the implementation of the present application described herein and / or required.

[0157] like Figure 7 As shown, the electronic device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 to a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0158] A plurality of components in the electronic device 700 are connected to the I / O interface 705, including: an input unit 706, an output unit 707, a storage unit 708, and a communication unit 709. The input unit 706 may be any type of device capable of inputting information to the electronic device 700, and the input unit 706 may receive input digital or character information, and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 707 may be any type of device capable of presenting information, and may include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 708 may include but is not limited to a disk, an optical disk. The communication unit 709 allows the electronic device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and may include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth device, a WiFi device, a worldwide interoperability for microwave access (WiMax) device, a cellular communication device, and / or the like.

[0159] The computing unit 701 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various AI computing chips, various computing units running machine learning model algorithms, digital signal processors (DSP), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 701 performs the various methods and processes described above. For example, in some embodiments, the above-mentioned bill data processing method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 700 via the ROM 702 and / or the communication unit 709. In some embodiments, the computing unit 701 may be configured to perform the above-mentioned bill data processing method by any other appropriate means (e.g., by means of firmware).

[0160] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0161] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an erasable programmable read-only memory (EPROM) or a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0162] As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0163] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a cathode ray tub (CRT) or a liquid crystal display (LCD) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0164] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0165] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0166] Furthermore, it should be understood that what is disclosed above is only a preferred embodiment of the present application, and certainly cannot be used to limit the scope of rights of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope covered by the present application.

Claims

1. A bill data processing method, characterized in that: include: Receiving a billing data processing request from a target terminal, and obtaining target billing data and a user reconciliation requirement for the target billing data from the billing data processing request; Based on the user reconciliation requirement and its associated historical decision data, generating a target reconciliation rule for the target bill data; wherein the historical decision data includes at least one historical reconciliation rule; The target billing data is processed based on the target reconciliation rule to obtain a billing data processing result.

2. The method according to claim 1, characterized in that The acquiring, from the bill data processing request, target bill data and a user reconciliation requirement for the target bill data, comprises: Parsing the billing data processing request to obtain initial billing data and initial reconciliation requirements; The initial billing data is sequentially subjected to data format conversion, data cleaning and data verification processing to obtain the target billing data, and the initial reconciliation requirements are standardized to obtain the user reconciliation requirements.

3. The method according to claim 2, characterized in that The method further comprises: During the process of data cleaning the initial bill data, if it is found that sub-bill data that meets the preset abnormal data conditions exists in the initial bill data, the sub-bill data is marked as abnormal data, and first information is sent to the target terminal; the first information is used to indicate that the sub-bill data is the abnormal data.

4. The method according to any one of claims 1 to 3, characterized in that The generating the target reconciliation rule of the target bill data based on the user reconciliation requirement and the associated historical decision data includes: Parsing the user's reconciliation requirement to obtain the user's reconciliation intention, and filtering out the historical decision data matching the reconciliation intention from the historical database; wherein the reconciliation intention is used to indicate at least one data processing method required by the user for the target bill data; The target reconciliation rule is generated based on the user reconciliation requirement and the at least one historical reconciliation rule included in the historical decision data.

5. The method according to any one of claims 1 to 3, characterized in that The performing data processing on the target bill data based on the target reconciliation rule to obtain a bill data processing result includes: Based on the data processing instructions corresponding to the target reconciliation rule, reconciliation processing is performed on the multiple sub-bill data included in the target bill data respectively to obtain multiple reconciliation processing results; wherein each reconciliation processing result represents: whether the corresponding sub-bill data is abnormal sub-bill data; The bill data processing result is obtained based on the multiple reconciliation processing results and the abnormal information corresponding to at least one abnormal sub-bill data included in the multiple sub-bill data.

6. The method according to claim 5, characterized in that After obtaining the multiple reconciliation processing results, the method further includes: For the multiple reconciliation processing results, perform the following operations respectively: If the first reconciliation result indicates that the first sub-bill data corresponding to the first reconciliation result is the abnormal sub-bill data, obtaining the location information of the first sub-bill data in the target bill data, and the abnormal description and abnormal reason of the first sub-bill data; wherein the first reconciliation result is any one of the multiple reconciliation processing results; Based on the location information, the exception description and the exception reason of the first sub-bill data, the exception information of the first sub-bill data is generated.

7. The method according to any one of claims 1 to 3, characterized in that After the target bill data is processed based on the target reconciliation rule to obtain the bill data processing result, the method further includes: Sending the bill data processing result to the target terminal; receiving feedback information returned by the target terminal based on the bill data processing result; the feedback information is used to modify the target reconciliation rule to obtain the modified target reconciliation rule.

8. A bill data processing device, characterized in that: include: A transceiver module, configured to receive a billing data processing request from a target terminal, and obtain target billing data and a user reconciliation requirement for the target billing data from the billing data processing request; A generating module, configured to generate a target reconciliation rule for the target bill data based on the user reconciliation requirement and its associated historical decision data; wherein the historical decision data includes at least one historical reconciliation rule; The processing module is used to perform data processing on the target billing data based on the target reconciliation rule to obtain a billing data processing result.

9. An electronic device, comprising: processor; as well as Memory for storing programs, The program includes instructions, which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 7.

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