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

Abstract

The invention provides an account data processing method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the account data processing method comprises the steps: obtaining a parameter type of an object behavior parameter and an object identifier associated with an object; target account book information to which target account data related to the object belongs is determined according to the object identifier, the target account book information is used for describing a target account book to which the target account data belongs, and the target account book is used for managing at least one target attribute related to the target account data; the target account book information is generated based on at least one target attribute; obtaining a target scene parameter according to the target account book information; and processing the target account data according to the parameter type and the target scene parameter to obtain a processing result. The technical problem that in the prior art, account data processing is not accurate enough, so that the risk prediction effect of account data is affected is solved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to an account data processing method, device, electronic device and storage medium. Background Art

[0002] In the financial field, in order to improve the ability of refined management, an efficient and flexible way is needed to manage and classify account data, and to predict the changes in account data in the future based on the classification results and multiple scenario simulations. In the related technology, the processing of account data is not accurate enough, which will affect the risk prediction effect of account data. Summary of the invention

[0003] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0004] To this end, the first purpose of the present disclosure is to propose an account data processing method to improve the processing accuracy of account data, thereby ensuring the risk prediction effect of account data.

[0005] A second objective of the present disclosure is to provide an account data processing device.

[0006] A third objective of the present disclosure is to provide an electronic device.

[0007] A fourth objective of the present disclosure is to provide a computer-readable storage medium.

[0008] A fifth object of the present disclosure is to provide a computer program product.

[0009] To achieve the above-mentioned purpose, the first aspect embodiment of the present disclosure proposes an account data processing method, including: obtaining the parameter type of the object behavior parameter and the object identifier associated with the object; determining the target account book information to which the target account data related to the object belongs according to the object identifier, wherein the target account book information is used to describe the target account book to which the target account data belongs, and the target account book is used to manage at least one target attribute related to the target account data, and the target account book information is generated based on the at least one target attribute; obtaining the target scenario parameters according to the target account book information; processing the target account data according to the parameter type and the target scenario parameters to obtain the processing result.

[0010] To achieve the above-mentioned purpose, the second aspect embodiment of the present disclosure proposes an account data processing device, including: a first acquisition module, used to obtain the parameter type of the object behavior parameter and the object identifier associated with the object; a determination module, used to determine the target account book information to which the target account data related to the object belongs according to the object identifier, wherein the target account book information is used to describe the target account book to which the target account data belongs, and the target account book is used to manage at least one target attribute related to the target account data, and the target account book information is generated based on the at least one target attribute; a second acquisition module, used to obtain the target scenario parameters according to the target account book information; a processing module, used to process the target account data according to the parameter type and the target scenario parameters to obtain a processing result.

[0011] To achieve the above-mentioned purpose, the third aspect embodiment of the present disclosure proposes an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement an account data processing method proposed in the first aspect embodiment of the present disclosure.

[0012] To achieve the above-mentioned purpose, the fourth aspect embodiment of the present disclosure proposes a computer-readable storage medium, in which computer execution instructions are stored. When the computer execution instructions are executed by the processor, they are used to implement an account data processing method proposed in the first aspect embodiment of the present disclosure.

[0013] To achieve the above-mentioned purpose, the fifth aspect of the present disclosure proposes a computer program product, including a computer program, which, when executed by a processor, implements an account data processing method proposed in the first aspect of the present disclosure.

[0014] The account data processing method, device, electronic device, non-transitory computer-readable storage medium storing computer instructions, and computer program product provided by the present disclosure obtain the parameter type of the object behavior parameter and the object identifier associated with the object, and determine the target account book information to which the target account data related to the object belongs according to the object identifier, wherein the target account book information is used to describe the target account book to which the target account data belongs, the target account book is used to manage at least one target attribute related to the target account data, the target account book information is generated based on at least one target attribute, and the target scenario parameter is obtained according to the target account book information, and the target account data is processed according to the parameter type and the target scenario parameter to obtain a processing result. Therefore, when processing the target account data, not only the parameter type corresponding to the object behavior parameter is considered, but also the target scenario parameter that conforms to the target account data related to the object is considered, so that the target account data can be processed based on multi-dimensional content, and the refinement of the target account data processing is improved, thereby improving the processing accuracy of the account data, thereby ensuring the risk prediction effect of the account data.

[0015] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0017] Figure 1 A flowchart of an account data processing method provided by an embodiment of the present disclosure;

[0018] Figure 2 A flowchart of another account data processing method provided by an embodiment of the present disclosure;

[0019] Figure 3 is a schematic diagram of an application flow in an embodiment of the present disclosure;

[0020] Figure 4 A schematic diagram of the structure of an account data processing device provided by an embodiment of the present disclosure;

[0021] Figure 5 It is a schematic structural diagram of an electronic device shown in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0022] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0023] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this disclosure are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions. The acquisition, transmission, storage, use and processing of data in the technical solution of this disclosure are in compliance with the relevant provisions of national laws and regulations.

[0024] It should be noted that in the embodiments of the present disclosure, certain software, components, models and other existing solutions in the industry may be mentioned, which should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present disclosure, but it does not mean that the applicant has or will necessarily use the solution.

[0025] Figure 1 A flowchart of an account data processing method provided by an embodiment of the present disclosure.

[0026] This embodiment takes the account data processing method being configured in an account data processing device as an example. In this embodiment, the account data processing method can be configured in an account data processing device. The account data processing device can be set in a server or in an electronic device, without limitation.

[0027] This embodiment takes the account data processing method configured in an electronic device as an example, wherein the electronic device is a hardware device such as a smart phone, a tablet computer, a personal digital assistant, an e-book, etc. having various operating systems.

[0028] It should be noted that the execution subject of the embodiment of the present disclosure may be, for example, a central processing unit (CPU) in a server or electronic device in terms of hardware, or may be, for example, a related background service in a server or electronic device in terms of software, without limitation.

[0029] like Figure 1 As shown, the account data processing method includes:

[0030] S101: Acquire a parameter type of an object behavior parameter and an object identifier associated with the object.

[0031] Among them, the object can be, for example, the user, customer, etc. to which the account belongs. Object behavior refers to some operational behaviors of the object on the account it owns, such as early withdrawal behavior, early loan repayment behavior, etc. Object behavior parameters are used to describe the parameters involved in the aforementioned various possible object behaviors (withdrawal behavior, early loan repayment behavior, etc.). The parameter type is used to describe the type of parameters (such as withdrawal amount, withdrawal time, etc.) involved in the aforementioned object behaviors (withdrawal behavior, early loan repayment behavior, etc.). The parameter type can be used to characterize the classification of the business to which the object behavior parameter belongs, and can also characterize some classification situations of the parameter itself, without limitation.

[0032] The object identifier is used to uniquely identify the object.

[0033] Optionally, in some embodiments, when implementing the acquisition of the parameter type of the object behavior parameter, the operating behavior of the object on the electronic device can be detected, and the object behavior parameters and the parameter type of the object behavior parameters can be identified based on the detection results; or the background log data of the electronic device can be obtained, and the parameter type of the object behavior parameters can be obtained from the background log data; or the parameter type of the object behavior parameters obtained by statistical analysis of a third-party device can be received, and there is no limitation on this.

[0034] Optionally, in some embodiments, when obtaining the object identifier associated with an object, feature detection for the object can be triggered, such as calling a detection interface to implement feature detection for the object, and identifying the object identifier based on the object features obtained by the detection, or analyzing the object identifier based on the account used by the object; or any other possible way can be used to obtain the object identifier associated with the object, without limitation.

[0035] Optionally, in some embodiments, after obtaining the parameter type of the object behavior parameter and the object identifier associated with the object, the parameter type of the object behavior parameter and the object identifier can be used to assist in fine-tuning the account data. For details, please refer to the subsequent embodiments.

[0036] S102: Determine, based on the object identifier, target account book information to which target account data related to the object belongs, wherein the target account book information is used to describe the target account book to which the target account data belongs, the target account book is used to manage at least one target attribute related to the target account data, and the target account book information is generated based on the at least one target attribute.

[0037] Among them, the target account data refers to the detailed data in one or more accounts belonging to the object. The target account data may contain various attributes, and the attributes contained in the target account data can be called target attributes. Different target attributes can correspond to different dimensions, and the target attributes are used to describe some characteristics of the target account data under the corresponding dimensions. The target attributes can be extracted from the target account data. The dimensions can be, for example, basic dimensions and management dimensions. The basic dimensions are used to define the basic attributes of the business where the target account data is located, including accounting subjects, currencies, terms, etc. The management dimensions are designed based on account management needs and can support the analysis of account data under the business from different angles. The management dimensions include cash flow patterns, customer types, ratings, etc., and there is no restriction on this.

[0038] Among them, the target account book is used to manage one or more target attributes of the above-mentioned target account data. Under the target account book, one or more attributes involved in other account data can also be managed. The target account book information can be used to uniquely identify the target account book. The target account book information can be specifically, for example, the identifier of the target account book. The target account book information can be generated based on one or more target attributes. If the target account book not only manages at least one target attribute related to the target account data, but also manages one or more attributes involved in other account data, then the target account book information can be generated based on one or more target attributes and one or more attributes involved in other account data, and there is no limitation on this.

[0039] Optionally, in some embodiments, in the process of determining the target account book information to which the target account data related to the object belongs based on the object identifier, the target account belonging to the object can be determined based on the object identifier, and the target account can contain one or more target account data. Then, the target account book information to which each target account data in the target account belongs is determined, and a mapping relationship between the target account data and the target account book information can be established in advance. Then, the target account book information to which the target account data related to the object belongs can be identified based on the mapping relationship, and there is no limitation to this.

[0040] Optionally, in some embodiments, in the process of determining the target account book information to which the target account data related to the object belongs based on the object identifier, the target account belonging to the object can be determined based on the object identifier, and the target account can contain one or more target account data, and then one or more target attributes involved in the target account data are analyzed, and the account book information used to manage the one or more target attributes is used as the target account book information, without limitation.

[0041] Of course, it is also possible to determine the target account book information to which the target account data related to the object belongs based on the object identifier based on any other possible method, such as artificial intelligence method, data statistical analysis method, etc., without limitation.

[0042] S103: Obtain target scenario parameters according to the target account book information.

[0043] The scenario parameters can be used to simulate the corresponding scenario. The scenario is, for example, an interest rate change scenario. The scenario parameters are used to describe the characteristics related to the scenario, such as the interest rate change amount, etc., which are not limited.

[0044] The target scenario parameters refer to some scenario parameters applicable to the target account data corresponding to the target account book information. The scenarios that can be simulated by different target account data may be the same or different, so appropriate target scenario parameters can be obtained based on the target account book information to support subsequent scenario simulations.

[0045] Optionally, corresponding scenario parameters may be pre-configured for each account book information. In the process of obtaining the target scenario parameters based on the target account book information, the scenario parameters pre-configured for the target account book information may be obtained as the target scenario parameters; or, feature analysis may be performed on the target account data corresponding to the target account book information, and the target scenario parameters may be dynamically configured based on the results of the feature analysis; or, any other possible method may be used to obtain the target scenario parameters based on the target account book information, without limitation.

[0046] S104: Process the target account data according to the parameter type and the target scenario parameters to obtain a processing result.

[0047] After obtaining the parameter type of the object behavior parameter and the target scenario parameter according to the target account book information, the parameter type and the target scenario parameter can be used to process the target account data. Therefore, when processing the target account data, not only the parameter type corresponding to the object behavior parameter is considered, but also the target scenario parameters that conform to the target account data related to the object are considered. Thus, the target account data can be processed based on multi-dimensional content, which improves the degree of refinement of the target account data processing, thereby improving the processing accuracy of the account data and ensuring the risk prediction effect of the account data.

[0048] Optionally, in some embodiments, the target scenario parameter has one or more corresponding classification labels; wherein, in the process of processing the target account data according to the parameter type and the target scenario parameter to obtain the processing result, at least part of the account data related to the parameter type may be extracted from the target account data, and at least part of the account data may be classified according to one or more classification labels to obtain account sub-data corresponding to the classification label, and the processing result may be determined according to the one or more account sub-data. Thus, the processing accuracy can be greatly improved to ensure the risk prediction effect of the account data.

[0049] Among them, the classification label can be a label pre-configured based on the target scenario parameters. The classification label can be used for basic classification of account data (for example, classification into account sub-data in different processing stages, account sub-data under different business sub-categories, account sub-data generated based on different operation steps, etc.). The classification label can be a processing stage label, a business sub-category label, an operation step label, etc., among which the specific classification content of the classification label can be personalized based on the scenario simulation requirements, and there is no restriction on this.

[0050] Among them, extracting at least part of the account data related to the parameter type from the target account data means that at least part of the account data related to the parameter type can be extracted from the target account data. For example, if the parameter type is the parameter of early withdrawal behavior, then part of the account data involved in the "early withdrawal behavior" (such as changed account data, affected account data, etc.) can be extracted from the target account data, and there is no restriction on this.

[0051] Optionally, in some embodiments, in the process of implementing classification of at least part of the account data according to one or more classification tags to obtain account sub-data corresponding to the classification tags, at least part of the account data may be split based on one or more classification tags, and the corresponding account sub-data may be marked based on the classification tags, and then, the processing result may be determined based on the one or more account sub-data. For example, the target scenario parameters may be provided to a cash flow engine (which may be understood as an account data processing device), and the account data processing device may implement classification of at least part of the account data according to one or more classification tags of the target scenario parameters to obtain account sub-data corresponding to the classification tags, and determine the processing result based on the one or more account sub-data, without limitation.

[0052] Optionally, the above processing result may be, for example, a cash flow result detail, or a report result for describing the cash flow result detail, which is not limited.

[0053] In this embodiment, by obtaining the parameter type of the object behavior parameter and the object identifier associated with the object, and according to the object identifier, determining the target account book information to which the target account data related to the object belongs, wherein the target account book information is used to describe the target account book to which the target account data belongs, the target account book is used to manage at least one target attribute related to the target account data, and the target account book information is generated based on at least one target attribute, and according to the target account book information, the target scenario parameter is obtained, and the target account data is processed according to the parameter type and the target scenario parameter to obtain a processing result. Therefore, when processing the target account data, not only the parameter type corresponding to the object behavior parameter is considered, but also the target scenario parameter that conforms to the target account data related to the object is considered, so that the target account data can be processed based on multi-dimensional content, and the refinement of the target account data processing is improved, thereby achieving improved processing accuracy of the account data, thereby ensuring the risk prediction effect of the account data.

[0054] Optionally, in some other embodiments, when it is determined that there is a need to split and differentiate future cash flows, the target account data can be processed according to the parameter type and the target scenario parameters to obtain a processing result, and there is no limitation on this.

[0055] Figure 2 A flowchart of another account data processing method provided in an embodiment of the present disclosure.

[0056] like Figure 2 As shown, the account data processing method includes:

[0057] S201: Obtain the parameter type of the object behavior parameter and the object identifier associated with the object.

[0058] For the description of S201, please refer to the above embodiment, which will not be repeated here.

[0059] S202: Acquire a wide identification table, wherein the wide identification table includes: at least one candidate account book information, and one or more candidate account data associated with the candidate account book information.

[0060] Among them, the identification wide table may refer to a data table. The identification wide table may be pre-created. The identification wide table may contain one or more candidate account book information, wherein the candidate account book is used to manage one or more candidate attributes of the above-mentioned candidate account data, and under the candidate account book, one or more attributes involved in other account data may also be managed. The candidate account book information may be used to uniquely identify the candidate account book, and the candidate account book information may specifically be, for example, the identification of the candidate account book. The candidate account book information may be generated based on one or more candidate attributes. If the candidate account book not only manages at least one candidate attribute related to the candidate account data, but also manages one or more attributes involved in other account data, then the candidate account book information may be generated based on one or more candidate attributes, and one or more attributes involved in other account data, and there is no limitation on this.

[0061] Optionally, in some embodiments, the candidate account book information is generated based on the following method: receiving configuration information, wherein the configuration information is used to configure at least one attribute dimension, and obtaining candidate attributes corresponding to each attribute dimension from one or more candidate account data, and generating the candidate account book information based on the at least one candidate attribute. Thus, personalized configuration of the account book information can be supported, personalized processing scenario requirements can be met, and the flexibility of account data processing can be improved.

[0062] The above configuration information may be a user-triggered configuration, which is not limited.

[0063] Optionally, in some embodiments, after determining one or more attribute dimensions, candidate attributes corresponding to each attribute dimension may be obtained from one or more candidate account data, wherein the candidate attributes may be regarded as attribute values ​​corresponding to the corresponding attribute dimensions, and different attribute dimensions may be different, and may be traversed in each candidate account data to determine the candidate attributes that meet each attribute dimension. Then, candidate account book information may be generated based on at least one candidate attribute, such as processing one or more candidate attributes based on certain processing rules, and using the processing results as candidate account book information, without limitation.

[0064] Optionally, in some embodiments, the identification wide table is generated based on the following method: one or more candidate account data are associated with candidate account book information, and the identification wide table is generated according to at least one candidate account book information and one or more candidate account data associated with the candidate account book information. Thus, it is possible to support rapid retrieval of target account book information to which target account data related to the object belongs, improve the efficiency of account data processing, effectively expand the application scenarios of account data processing, and improve the practicality of account data processing.

[0065] Optionally, in some embodiments, a pre-generated identification wide table may be obtained, and then at least one candidate account book information and one or more candidate account data associated with the candidate account book information are obtained from the identification wide table.

[0066] S203: Select target account data from one or more candidate account data according to the object identifier.

[0067] After obtaining one or more candidate account book information and one or more candidate account data associated with the candidate account book information from the identification wide table, the target account data may be selected from the one or more candidate account data with reference to the object identification.

[0068] The target account data refers to the account data belonging to the object. Different candidate account data may belong to different or the same objects, and different candidate account data may be associated with different or the same object identifiers. Based on the object identifier, the candidate account data belonging to the object may be selected as the target account data.

[0069] Optionally, in some embodiments, in the process of selecting the target account data from one or more candidate account data according to the object identifier, the target account information may be determined according to the object identifier, and the candidate account information corresponding to each candidate account data may be determined, and the candidate account information identical to the target account information may be determined from one or more candidate account information, and the candidate account data corresponding to the candidate account information identical to the target account information may be used as the target account data. In this way, the efficiency of obtaining the target account data can be greatly improved, and the efficiency of processing the account data can be further improved.

[0070] S204: Using the candidate account book information associated with the target account data as the target account book information.

[0071] After selecting the target account data from one or more candidate account data, the candidate account book information associated with the target account data may be used as the target account book information.

[0072] S205: Acquire a hierarchical tree, wherein the hierarchical tree includes: at least one candidate leaf node, each candidate leaf node having corresponding candidate scenario parameters and candidate account book information.

[0073] In the disclosed embodiment, multiple candidate account book information can be managed based on a tree structure. The hierarchical tree may include multiple levels, and one or more nodes may be distributed in each level. Among the multiple nodes, one or more parent nodes may be included, and one or more candidate leaf nodes may be included. Each candidate leaf node may be associated with a candidate account book information. After the association, appropriate candidate scenario parameters may be configured for each candidate account book information based on various possible account data processing requirements to obtain one or more candidate scenario parameters. The configured candidate scenario parameters may be used for subsequent scenario simulation.

[0074] S206: Determine candidate account book information that is the same as the target account book information from at least one candidate account book information.

[0075] S207: taking the candidate leaf node corresponding to the candidate account book information identical to the target account book information as the target leaf node, and taking the candidate scenario parameter corresponding to the target leaf node as the target scenario parameter.

[0076] After determining the candidate scenario parameters and candidate account book information corresponding to each candidate leaf node configured in the hierarchical tree, the candidate account book information that is identical to the target account book information can be determined from at least one candidate account book information, and then, the candidate leaf node corresponding to the candidate account book information that is identical to the target account book information is used as the target leaf node, and the candidate scenario parameters corresponding to the target leaf node are used as the target scenario parameters.

[0077] S208: Process the target account data according to the parameter type and the target scenario parameters to obtain a processing result.

[0078] For the description of S208, please refer to the above embodiment, which will not be repeated here.

[0079] In this embodiment, by obtaining the parameter type of the object behavior parameter and the object identifier associated with the object, and according to the object identifier, determining the target account book information to which the target account data related to the object belongs, wherein the target account book information is used to describe the target account book to which the target account data belongs, the target account book is used to manage at least one target attribute related to the target account data, and the target account book information is generated based on at least one target attribute, according to the target account book information, obtaining the target scenario parameter, and processing the target account data according to the parameter type and the target scenario parameter, to obtain the processing result. Therefore, since when processing the target account data, not only the parameter type corresponding to the object behavior parameter is considered, but also the target scenario parameter that conforms to the target account data related to the object is considered, the target account data can be processed based on multi-dimensional content, the refinement of the target account data processing is improved, thereby improving the processing accuracy of the account data, and ensuring the risk prediction effect of the account data. By obtaining the identification wide table, wherein the identification wide table includes: at least one candidate account book information, and one or more candidate account data associated with the candidate account book information, and according to the object identifier, the target account data is selected from the one or more candidate account data, and the candidate account book information associated with the target account data is used as the target account book information. Thus, it is possible to support the rapid retrieval of the target account book information to which the target account data related to the object belongs, improve the efficiency of account data processing, effectively expand the application scenarios of account data processing, and improve the practicality of account data processing. By obtaining a hierarchical tree, wherein the hierarchical tree includes: at least one candidate leaf node, each candidate leaf node has a corresponding candidate scenario parameter and candidate account book information, and the candidate account book information identical to the target account book information is determined from at least one candidate account book information, and the candidate leaf node corresponding to the candidate account book information identical to the target account book information is used as the target leaf node, and the candidate scenario parameter corresponding to the target leaf node is used as the target scenario parameter. Thus, the efficiency of obtaining the target scenario parameter is improved, and the efficiency of account data processing is further supported. Moreover, since the target scenario parameter can be pre-configured on demand, when a scenario simulation is performed based on the target scenario parameter, on-demand simulation can be achieved, and the simulation accuracy can be ensured, thereby further ensuring the risk prediction effect of the account data.

[0080] The examples for the above embodiment are as follows:

[0081] like Figure 3 As shown, Figure 3It is a schematic diagram of the application process in the embodiment of the present disclosure, wherein, customer behavior (which may be an optional example of object behavior), object behavior parameters such as parameters in the early withdrawal parameter table, parameters in the early repayment parameter table, parameters in the current loss parameter table, account book hierarchy tree (which is an optional example of the above hierarchy tree), account book hierarchy tree node table includes the identification of nodes in the hierarchy tree (such as candidate leaf nodes and parent nodes), hierarchy and other structural information, account book item dimension data (which is an optional example of the above candidate attributes or target attributes), and dimension table includes several optional (configurable) attribute dimensions (also referred to as dimension attributes). Personalized selection can be supported to select dimension attributes in the dimension table and mark the selected dimension attributes. If it is determined that the results need to be summarized based on the account data processing requirements, various possible customer behavior parameter tables (an optional example of the above-mentioned object behavior parameters) can be associated with the identification wide table (which may also be simply referred to as the wide table) and can also be associated with the hierarchical tree node table. If there is no need to summarize the results, the various possible customer behavior parameter tables do not need to be associated with the identification wide table and the hierarchical tree node table, and subsequent account data processing can be completed according to the account data processing requirements.

[0082] In the disclosed embodiment, the account book management module can be used to manage and configure the account book, thereby supporting the configuration of the account book, the import and export of the account book configuration results, and the configuration of the account book hierarchy structure. By configuring each attribute dimension into an account book and an account book hierarchy tree, the fine-grained requirements of scenario simulation and report analysis are met.

[0083] In the disclosed embodiment, the dimension can be configured, for example, according to the user input field (which may include the attribute dimension), the attribute data that conforms to the attribute dimension can be identified from the account data, and then one or more attribute data can be separated and spliced ​​by "|", an account book identifier is generated, and the account data is marked, and the identifier wide table is obtained according to the account book identifier and the account data. Then, the hierarchical tree can be configured, and the account book identifier can be configured on the leaf node of the hierarchical tree. According to the account book node and the hierarchical tree, the mapping relationship between the processing level and the account book identifier corresponding to the leaf node can be processed. In addition, the corresponding scenario parameters (an optional example of candidate scenario parameters) can be configured on each leaf node. The corresponding relationship between the account book identifier and the scenario parameter on each node in the hierarchical tree can be obtained through the account book identifier. And it is determined whether the future cash flow splitting is required. If not, it can be based on the identifier wide table, or the account data corresponding to the account book identifier, and based on the account data to obtain the statistical results (an optional example of the processing result). If necessary, the scenario parameters can be obtained, and the scenario parameters can be provided to the cash flow engine. The cash flow engine can split and process the account data based on the scenario parameters to obtain the processing result. In addition, the hierarchical relationship between the account book identifiers corresponding to each node in the hierarchical tree can also be obtained, and the processing results can be summarized to generate report results.

[0084] In the disclosed embodiments, it is possible to support flexible configuration of attribute dimensions, dynamic splicing to obtain account book identifiers, fusion of multiple attribute dimensions, and simplified association conditions. Avoid field redundancy and support personalized configuration of multiple attribute dimensions. It also supports one-time labeling of all account data, with the account book as the core basic unit, and can support reuse in multiple modules to avoid repeated processing of account data. In addition, by compressing account data through the account book, it can effectively reduce the amount of data and improve the engine splitting performance. It also supports efficient management of all connected attribute dimensions, supports adaptive expansion of attribute dimensions, and supports dynamic configuration of account book attribute dimensions to achieve easy expansion and maintenance of multiple attribute dimensions.

[0085] Figure 4 A schematic diagram of the structure of an account data processing device provided in an embodiment of the present disclosure.

[0086] like Figure 4 As shown, the account data processing device 40 includes:

[0087] The first acquisition module 401 is used to acquire the parameter type of the object behavior parameter and the object identifier associated with the object.

[0088] The determination module 402 is used to determine the target account book information to which the target account data related to the object belongs according to the object identifier, wherein the target account book information is used to describe the target account book to which the target account data belongs, the target account book is used to manage at least one target attribute related to the target account data, and the target account book information is generated based on the at least one target attribute.

[0089] The second acquisition module 403 is used to acquire target scenario parameters according to the target account book information.

[0090] The processing module 404 is used to process the target account data according to the parameter type and the target scenario parameter to obtain a processing result.

[0091] It should be noted that the above explanation of the account data processing method is also applicable to the account data processing device of this embodiment and will not be repeated here.

[0092] In this embodiment, by obtaining the parameter type of the object behavior parameter and the object identifier associated with the object, and according to the object identifier, determining the target account book information to which the target account data related to the object belongs, wherein the target account book information is used to describe the target account book to which the target account data belongs, the target account book is used to manage at least one target attribute related to the target account data, and the target account book information is generated based on at least one target attribute, and according to the target account book information, the target scenario parameter is obtained, and the target account data is processed according to the parameter type and the target scenario parameter to obtain a processing result. Therefore, when processing the target account data, not only the parameter type corresponding to the object behavior parameter is considered, but also the target scenario parameter that conforms to the target account data related to the object is considered, so that the target account data can be processed based on multi-dimensional content, and the refinement of the target account data processing is improved, thereby achieving improved processing accuracy of the account data, thereby ensuring the risk prediction effect of the account data.

[0093] As an example, Figure 5 is a schematic diagram of the structure of an electronic device shown in an exemplary embodiment of the present disclosure, such as Figure 5 As shown, the electronic device 700 may further include:

[0094] The memory 710 and the processor 720 , and the bus 730 connecting different components (including the memory 710 and the processor 720 ), the memory 710 stores a computer program, and when the processor 720 executes the program, the account data processing method of the embodiment of the present disclosure is implemented.

[0095] Bus 730 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0096] The electronic device 700 typically includes a variety of electronic device readable media. These media can be any available media that can be accessed by the electronic device 700, including volatile and non-volatile media, removable and non-removable media.

[0097] The memory 710 may also include computer system readable media in the form of volatile memory, such as random access memory (RAM) 740 and / or cache memory 750. The electronic device 700 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 760 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 not shown, usually called a "hard drive"). Although Figure 5 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 730 via one or more data medium interfaces. The memory 710 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0098] A program / utility 780 having a set (at least one) of program modules 770 may be stored, for example, in the memory 710, such program modules 770 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 770 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0099] The electronic device 700 may also communicate with one or more external devices 790 (e.g., keyboard, pointing device, display 791, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 700, and / or communicate with any device that enables the electronic device 700 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 792. Furthermore, the electronic device 700 may also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN) and / or public network, such as the Internet) through a network adapter 793. As shown, the network adapter 793 communicates with other modules of the electronic device 700 through a bus 730. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0100] The processor 720 executes various functional applications and data processing by running the programs stored in the memory 710 .

[0101] It should be noted that the implementation process and technical principles of the electronic device of this embodiment refer to the aforementioned explanation of the account data processing method of the embodiment of the present disclosure, and will not be repeated here.

[0102] In order to implement the above embodiments, the present disclosure also proposes an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0103] In order to implement the above embodiments, the present disclosure further proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0104] In order to implement the above embodiments, the present disclosure also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0105] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this disclosure shall comply with the relevant laws and regulations and shall not violate public order and good morals.

[0106] It should be noted that personal information from users should be collected for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign the agreement / authorization including authorization of relevant user information before the user uses the function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others who have access to personal information data comply with its privacy policy and procedures.

[0107] The present disclosure anticipates providing implementation schemes for users to selectively block the use or access of personal information data. That is, the present disclosure anticipates providing hardware and / or software to prevent or block access to such personal information data. Once the personal information data is no longer needed, risks can be minimized by limiting data collection and deleting the data. In addition, when applicable, such personal information is de-identified to protect the privacy of the user.

[0108] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0109] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, "plurality" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0110] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present disclosure includes additional implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present disclosure belong.

[0111] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0112] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0113] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0114] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0115] The storage medium mentioned above may be a read-only memory, a disk or an optical disk, etc. Although the embodiments of the present disclosure have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present disclosure. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present disclosure.

Claims

1. A method for processing account data, characterized in that: The following steps are involved: Get the parameter type of the object behavior parameter and the object identifier associated with the object; Determine, according to the object identifier, target account book information to which the target account data related to the object belongs, wherein the target account book information is used to describe the target account book to which the target account data belongs, the target account book is used to manage at least one target attribute related to the target account data, and the target account book information is generated based on the at least one target attribute; Obtain target scenario parameters according to the target account book information; The target account data is processed according to the parameter type and the target scenario parameter to obtain a processing result.

2. The method according to claim 1, characterized in that The step of determining, according to the object identifier, target account book information to which target account data related to the object belongs includes: Acquire a wide identification table, wherein the wide identification table includes: at least one candidate account book information, and one or more candidate account data associated with the candidate account book information; selecting the target account data from the one or more candidate account data according to the object identifier; The candidate account book information associated with the target account data is used as the target account book information.

3. The method according to claim 2, characterized in that The selecting the target account data from the one or more candidate account data according to the object identifier includes: Determining target account information according to the object identifier; Determining candidate account information corresponding to each of the candidate account data; Determine candidate account information identical to the target account information from one or more of the candidate account information, and use candidate account data corresponding to the candidate account information identical to the target account information as the target account data.

4. The method according to claim 2, characterized in that: The step of obtaining target scenario parameters according to the target account book information includes: Acquire a hierarchical tree, wherein the hierarchical tree includes: at least one candidate leaf node, each candidate leaf node having corresponding candidate scenario parameters and candidate account book information; Determine candidate account book information that is the same as the target account book information from at least one of the candidate account book information; The candidate leaf node corresponding to the candidate account book information that is the same as the target account book information is used as the target leaf node, and the candidate scenario parameter corresponding to the target leaf node is used as the target scenario parameter.

5. The method according to claim 4, characterized in that The candidate account book information is generated based on the following method: receiving configuration information, wherein the configuration information is used to configure at least one attribute dimension; A candidate attribute corresponding to each attribute dimension is obtained from one or more candidate account data, and the candidate account book information is generated according to at least one of the candidate attributes.

6. The method according to claim 4, characterized in that The identification wide table is generated based on the following method: Associating the one or more candidate account data with the candidate account book information; The identification wide table is generated according to at least one of the candidate account book information and one or more candidate account data associated with the candidate account book information.

7. The method according to claim 1, characterized in that The target scenario parameter has one or more corresponding classification labels; wherein the processing of the target account data according to the parameter type and the target scenario parameter to obtain a processing result includes: extracting at least part of the account data related to the parameter type from the target account data; Classifying at least part of the account data according to the one or more classification labels to obtain account sub-data corresponding to the classification labels; The processing result is determined according to one or more of the account sub-data.

8. An account data processing device, characterized in that: include: A first acquisition module, used to acquire a parameter type of an object behavior parameter and an object identifier associated with the object; a determination module, configured to determine, according to the object identifier, target account book information to which target account data related to the object belongs, wherein the target account book information is used to describe the target account book to which the target account data belongs, the target account book is used to manage at least one target attribute related to the target account data, and the target account book information is generated based on the at least one target attribute; A second acquisition module, used to acquire target scenario parameters according to the target account book information; A processing module is used to process the target account data according to the parameter type and the target scenario parameter to obtain a processing result.

9. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

11. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 7 when being executed by a processor.

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