Enterprise evaluation system, method and electronic equipment

Abstract

The present application provides an enterprise evaluation system, method and electronic device, including: a data acquisition module, which acquires multiple enterprise data of a target enterprise within a predetermined time period; a classification module, which divides the multiple enterprise data according to at least one operation theme for determining the operation efficiency index of the target enterprise to obtain multiple theme groups, each theme group corresponding to an operation theme; a missing judgment module, which determines, for each theme group, whether the enterprise data in the theme group contains the full amount of basic data under the corresponding operation theme, and if not, outputs a missing data label to indicate the missing basic data in the theme group; a model screening module, which selects a target evaluation model from a model library based on the missing data label; an indicator determination module, which inputs multiple enterprise data into the target evaluation model to obtain the operation efficiency index of the target enterprise; and an evaluation module, which determines the risk assessment index of the target enterprise based on the operation efficiency index.

Description

Technical Field

[0001] The present application relates to the field of information technology, and more specifically, to an enterprise evaluation system, method and electronic equipment. Background Art

[0002] With the continuous development of Internet technology and the advent of the Industrial 4.0 era, higher expectations have been raised for the improvement of information and digital capabilities in the process of enterprise transformation and upgrading. In this context, the economic operation situation of enterprises has also become the focus of attention of enterprises themselves.

[0003] In the current process of enterprise informatization, the DuPont model is a typical method for assessing the risks of enterprise economic operation. The traditional DuPont model assesses the enterprise risk informatization system. During the construction process, it is necessary to draw conclusions based on the basic full data such as net sales, cost and expenses, income tax, etc. in the DuPont model. The requirements for data sources and data volume are relatively strict. If the system is missing some basic information of the enterprise during the actual calculation process, the calculation results cannot be generated. This poses a high challenge and requirement for the universality of enterprise economic risk assessment. Summary of the invention

[0004] In view of this, the purpose of this application is to provide an enterprise evaluation system, method and electronic device, which collects the enterprise data of the target enterprise, analyzes the missing of basic information in the enterprise data, and matches the appropriate evaluation model in the model library according to the missing of basic information. The collected enterprise data is input into the evaluation model, and the operation efficiency index is obtained by using the evaluation model to obtain the risk assessment index of the target enterprise, thereby avoiding the situation that the enterprise risk assessment index cannot be obtained due to missing data when conducting risk assessment.

[0005] In the first aspect, the present application provides an enterprise evaluation system, including: a data acquisition module, which acquires multiple enterprise data of a target enterprise within a predetermined time period; a classification module, which divides the multiple enterprise data according to at least one operational theme used to determine the operational efficiency index of the target enterprise to obtain multiple subject groups, each subject group corresponding to an operational theme; a missing judgment module, which determines, for each subject group, whether the enterprise data in the subject group contains the full amount of basic data under the corresponding operational theme, and if not, outputs a missing data label, which is used to indicate the missing basic data in the subject group; a model screening module, which selects a target evaluation model from a model library based on the missing data label; an indicator determination module, which inputs multiple enterprise data into the target evaluation model to obtain the operational efficiency index of the target enterprise; and an evaluation module, which determines the risk assessment index of the target enterprise based on the operational efficiency index.

[0006] In a possible implementation, the plurality of enterprise data include enterprise data of a plurality of indicator types, wherein the data acquisition module is further used to: acquire enterprise data of a plurality of indicator types of the target enterprise within a predetermined time period from different data sources; mark the acquired enterprise data of a plurality of indicator types using the enterprise unified credit code, wherein each enterprise data includes an indicator type identifier and a source identifier, the indicator type identifier indicates the indicator type corresponding to the enterprise data, and the source identifier indicates the data source corresponding to the enterprise data; for each indicator type of enterprise data, extract the source identifier of the enterprise data of the indicator type, if the number of source identifiers is multiple, determine a target source identifier from the multiple source identifiers, and only retain the enterprise data of the indicator type corresponding to the target source identifier, if the number of source identifiers is one, retain the enterprise data of the indicator type corresponding to the unique source identifier; for each indicator type of enterprise data, compare the retained enterprise data of the indicator type with the corresponding enterprise threshold data range, if the enterprise data of the indicator type is within the enterprise threshold data range, retain the enterprise data of the indicator type, if the enterprise data of the indicator type is outside the enterprise threshold data range, discard the enterprise data of the indicator type.

[0007] In a possible implementation, the missing judgment module is also used to: call an evaluation template for the target enterprise, the evaluation template includes multiple sub-templates, each sub-template corresponds to an operating theme and the full amount of basic data under the operating theme; for each theme group, select a sub-template corresponding to the operating theme of the theme group, and based on the sub-template, determine whether the enterprise data in the theme group contains the full amount of basic data under the corresponding operating theme; for each theme group, if it does not contain the full amount of basic data under the corresponding operating theme, determine the missing basic data under the operating theme, and output a missing data label, the missing data label indicates the operating theme of the missing data and the missing basic data under the operating theme.

[0008] In one possible implementation, each sub-template corresponds to a process expression formula, and each process expression formula is used to obtain process data through basic data; wherein the missing judgment module is also used to: for each subject group that does not lack basic data, input the enterprise data in the subject group into the process expression formula corresponding to the operating subject of the subject group, determine the result calculated by the process expression formula as the process data of the subject group, and store the process data in the enterprise data corresponding to the subject group.

[0009] In one possible implementation, a plurality of evaluation models are stored in a model library, the input of each evaluation model is different enterprise data, at least one enterprise data is different in the inputs of different evaluation models, and the output of each evaluation model is an operational efficiency indicator; wherein the model screening module is also used to: determine the missing basic data of the target enterprise based on the missing data label; and search for a target evaluation model from the model library, wherein the target evaluation model is an evaluation model among multiple evaluation models, the input of which does not include the missing basic data.

[0010] In a possible implementation, the indicator determination module is also used to: input multiple enterprise data into the target evaluation model to obtain model output results; judge the validity of the model output results; if the model output results are valid, determine the model output results as the operational efficiency indicators of the target enterprise; if the model output results are not valid, configure a temporary evaluation model based on multiple enterprise data; determine the operational efficiency indicators of the target enterprise based on the temporary evaluation model and the multiple enterprise data; and store the temporary evaluation model in the model library.

[0011] In a possible implementation, the indicator determination module is also used to: select multiple basic data participating in configuring a temporary evaluation model from multiple enterprise data as configuration parameters; configure a calculation formula based on the configuration parameters to obtain a temporary evaluation model that can calculate the operational efficiency indicators of the target enterprise.

[0012] In a possible implementation, the evaluation module is also used to: compare the operational efficiency indicator with a plurality of pre-set operational efficiency intervals, wherein each operational efficiency interval corresponds to a preset risk value; and determine the preset risk value corresponding to the operational efficiency interval containing the operational efficiency indicator as a risk assessment index.

[0013] In the second aspect, an embodiment of the present application also provides an enterprise evaluation method, including: obtaining multiple enterprise data of a target enterprise within a predetermined time period; dividing the multiple enterprise data according to at least one operational theme for determining the operational efficiency index of the target enterprise to obtain multiple theme groups, each theme group corresponding to an operational theme; for each theme group, determining whether the enterprise data in the theme group contains the full amount of basic data under the corresponding operational theme, and if not, outputting a missing data label, the missing data label is used to indicate the missing basic data in the theme group; based on the missing data label, selecting a target evaluation model from a model library; inputting multiple enterprise data into the target evaluation model to obtain the operational efficiency index of the target enterprise; based on the operational efficiency index, determining the risk assessment index of the target enterprise.

[0014] In a third aspect, the present application also provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the enterprise assessment method as described above are performed.

[0015] The present application provides an enterprise evaluation system, method and electronic device, including: a data acquisition module, which acquires multiple enterprise data of a target enterprise within a predetermined time period; a classification module, which divides multiple enterprise data according to at least one operation theme for determining the operation efficiency index of the target enterprise, and obtains multiple theme groups, each theme group corresponding to an operation theme; a missing judgment module, for each theme group, determines whether the enterprise data in the theme group contains the full amount of basic data under the corresponding operation theme, if not, outputs a missing data label to indicate the missing basic data in the theme group; a model screening module, based on the missing data label, selects a target evaluation model from a model library; an indicator determination module, which inputs multiple enterprise data into the target evaluation model to obtain the operation efficiency index of the target enterprise; an evaluation module, based on the operation efficiency index, determines the risk assessment index of the target enterprise. In the existing enterprise evaluation method, if individual basic information is missing during the actual calculation process, the risk assessment result cannot be generated due to the lack of calculation parameters. However, the present application can match the evaluation model that does not involve the missing basic data based on the missing basic data when some basic data are missing, and then obtain the risk assessment index, which increases the adaptability of the enterprise evaluation work.

[0016] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A schematic diagram of the structure of the enterprise evaluation system provided in the embodiment of the present application;

[0019] Figure 2 A schematic diagram of an evaluation template provided in an embodiment of the present application;

[0020] Figure 3A schematic diagram of a process flow for determining an operational efficiency index of a target enterprise provided in an embodiment of the present application;

[0021] Figure 4 A schematic diagram of a processing flow for configuring a temporary evaluation model based on multiple enterprise data provided in an embodiment of the present application;

[0022] Figure 5 A flowchart of the enterprise evaluation method provided in the embodiment of the present application;

[0023] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0024] Figure numbers: 1-data acquisition module, 2-classification module, 3-missing judgment module, 4-model screening module, 5-indicator determination module, 6-evaluation module, 7-sub-template, 8-basic data, 9-operation theme, 10-process data, 600-electronic device, 610-processor, 620-memory, 630-bus. DETAILED DESCRIPTION

[0025] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0026] First, the application scenarios to which this application can be applied are introduced. This application can be applied to the scenario of enterprise risk assessment.

[0027] The research found that the DuPont model is a typical example of the existing enterprise economic operation risk assessment method. The traditional DuPont model-based enterprise risk information system needs to draw conclusions based on the basic full data such as net sales, costs and expenses, income tax, etc. in the DuPont model during the construction process. The requirements for data sources and data volume are relatively strict. If the enterprise lacks some basic information during the actual calculation process, the system cannot generate calculation results.

[0028] Based on this, the embodiment of the present application provides an enterprise evaluation system, method and electronic device, which collects the enterprise data of the target enterprise, analyzes the missing of basic information in the enterprise data, and matches the appropriate evaluation model in the model library according to the missing of basic information. The collected enterprise information is input into the evaluation model, and the operation efficiency index is obtained by using the evaluation model to obtain the risk assessment index of the target enterprise, thereby avoiding the situation that the enterprise risk assessment index cannot be obtained due to missing data when conducting risk assessment.

[0029] See also Figure 1 , Figure 1 This is a schematic diagram of the structure of an enterprise evaluation system provided by an embodiment of the present application. Figure 1 As shown in , the enterprise evaluation system provided by the embodiment of the present application includes:

[0030] The data acquisition module 1 acquires a plurality of enterprise data of a target enterprise within a predetermined time period.

[0031] The data acquisition module 1 can collect internal data information of the enterprise and external public data information of the enterprise, obtain structured, semi-structured and unstructured data, and convert these structured, semi-structured and unstructured data into structured data as enterprise data.

[0032] Here, multiple enterprise data include enterprise data of multiple indicator types, which mainly include key financial data indicators such as enterprise net sales, cost, income tax, sales revenue, current assets, non-current assets, current liabilities, long-term liabilities, total assets, etc. These enterprise data are stored periodically as enterprise basic data to form a basic database.

[0033] Specifically, the data acquisition module 1 extracts enterprise data from data provided by different data sources. Here, each enterprise data also includes an enterprise identifier, an indicator type identifier and a source identifier. The enterprise identifier is used to indicate the enterprise to which the enterprise data belongs. The indicator type identifier is used to indicate the indicator type corresponding to the enterprise data, such as cost data, current liabilities and other indicator types. The source identifier indicates the data source corresponding to the enterprise data. Here, the data source includes the enterprise's internal system, external public information, etc.

[0034] In addition to the above-mentioned methods, the data acquisition module 1 can also perform deduplication and error removal processing on the collected enterprise data.

[0035] In the deduplication process, the data acquisition module 1 first screens the enterprise data based on the enterprise identification, and screens out the enterprise data of the target enterprise within a predetermined time period. Subsequently, the data acquisition module 1 uses the enterprise unified credit code to mark the enterprise data of multiple indicator types obtained. The enterprise unified credit code here is the unique identifier of the enterprise bound to the target enterprise. The enterprise data of the target enterprise is marked with the enterprise unified credit code, which can distinguish the data of the target enterprise from the data of other entities, so that the system can directly call the enterprise data of the target enterprise in the basic database, reducing the calculation pressure of the system.

[0036] For each indicator type of enterprise data, extract the source identifier of the enterprise data of this indicator type. If there are multiple source identifiers, determine a target source identifier from the multiple source identifiers, and only retain the enterprise data of this indicator type corresponding to the target source identifier. If there is only one source identifier, retain the enterprise data of this indicator type corresponding to the unique source identifier. For example, the system obtains multiple copies of enterprise data of the indicator type of income tax from different data sources in the same time period. If there are income tax data with multiple source identifiers, determine a target source identifier from the multiple source identifiers. The specific determination method can be to identify the identification source whose data source is within the enterprise as the target identification source, retain only the income tax data with the target identification source, and discard the income tax data of other identification sources.

[0037] In the error removal process, the data acquisition module 1 compares the retained enterprise data of each indicator type with the corresponding enterprise threshold data range for the enterprise data of each indicator type. Here, different enterprise threshold data are set according to the data properties of enterprise data of different indicator types, so that each type of enterprise data of each indicator type has a corresponding enterprise threshold range. Specifically, the enterprise threshold range includes an upper limit value and a lower limit value, and the values ​​of the upper limit value and the lower limit value can be determined according to the corresponding indicator type.

[0038] If the enterprise data of this indicator type is within the enterprise threshold data range, the enterprise data of this indicator type will be retained. If the enterprise data of this indicator type is outside the enterprise threshold data range, for example, the value of the enterprise data of a certain indicator type is greater than the upper limit value corresponding to the indicator type or less than the lower limit value corresponding to the indicator type, then the enterprise data is considered to be abnormal and the enterprise data of this indicator type will be discarded.

[0039] In addition, when periodic enterprise data have null values ​​in a certain period of time, they are filled using the two-sided mean median method to reduce the amount of missing basic data.

[0040] In this way, after the collected enterprise data is deduplicated and processed for error elimination, the amount of enterprise data can be effectively reduced, the computational pressure of subsequent calculation processes can be reduced, and the working efficiency of the evaluation system can be improved.

[0041] Classification module 2 divides the data of multiple enterprises according to at least one operation theme for determining the operation efficiency index of the target enterprise to obtain multiple theme groups, each theme group corresponding to an operation theme.

[0042] In reality, the operational efficiency indicators used to determine the risk assessment index of an enterprise are mostly the enterprise's return on net assets, and the operational themes are usually the three operational themes of net sales margin, total asset turnover rate, and asset-liability ratio. Based on these three operational themes, the collected data of multiple enterprises are divided into the net sales margin theme group, the total asset turnover rate theme group, and the asset-liability ratio theme group.

[0043] In this way, multiple enterprise data are stored in groups. When calculating the values ​​of different operating topics, the required enterprise data can be directly retrieved from the corresponding group, thereby improving the calculation speed of the system.

[0044] Missing data judgment module 3 determines, for each subject group, whether the enterprise data in the subject group contains the full amount of basic data under the corresponding operating subject. If not, it outputs a missing data label, which is used to indicate the missing basic data in the subject group.

[0045] In the specific working process, the deficiency judgment module 3 first calls the evaluation template for the target enterprise. Figure 2 , Figure 2 A schematic diagram of an evaluation template provided as an example in an embodiment of the present application, such as Figure 2 As shown, the evaluation template includes multiple sub-templates 7, each sub-template 7 corresponds to an operation theme 9 and the full amount of basic data 8 under the operation theme 9.

[0046] For each subject group, a sub-template 7 corresponding to the operating subject 9 of the subject group is selected, and based on the sub-template 7, it is determined whether the enterprise data in the subject group contains the full amount of basic data 8 under the corresponding operating subject. Figure 2 In the example shown in , in the sub-template 7 corresponding to the net sales margin operation theme 9, the full basic data 8 includes sales revenue, net sales, cost and income tax. The system retrieves the enterprise data with the indicator type marked as sales revenue, net sales, cost and income tax in the theme group corresponding to the net sales margin, and judges whether the enterprise data contains the full basic data 8 under the corresponding operation theme 9. The judgment process of other forms of evaluation templates and sub-templates is the same as above, and will not be repeated here.

[0047] For each subject group, if it does not contain the full amount of basic data 8 under the corresponding operating subject 9, the missing basic data under the operating subject 9 is determined, and a missing data label is output, which indicates the operating subject 9 with missing data and the basic data 8 missing in the operating subject 9. Figure 2 In the example shown in , if the net sales data is missing in the enterprise data, the output is the label of the missing data being net sales, which is used to indicate that the enterprise data under the net sales margin operation topic is missing net sales data.

[0048] In addition, each sub-template 7 should have a process expression formula, and each process expression formula is used to pass the basic data 8 to the process data 10. The missing judgment module can also input the enterprise data in the subject group into the process expression formula corresponding to the operating subject 9 of the subject group for each subject group that does not have missing basic data 8, determine the result calculated by the process expression formula as the process data 10 of the subject group, and store the obtained process data 10 in the enterprise data corresponding to the subject group for subsequent model calculation. For example Figure 2 In the example shown in , in the sub-template 7 corresponding to the asset-liability ratio operation theme 9, the full basic data 8 includes current liabilities, long-term liabilities and total assets. If there is basic data 8 of the indicator type of current liabilities and long-term liabilities in the enterprise data, the total liabilities data is obtained through the long-term liabilities data and current assets data based on the process expression formula as the process data 10 of the theme group. The judgment process of other forms of evaluation templates and sub-templates is the same as above and will not be repeated here.

[0049] In this way, the corresponding process data is calculated based on the basic data within the subject group and stored in the enterprise data corresponding to the subject group. In subsequent model calculations, when enterprise data corresponding to the process data is needed, the data can be directly retrieved without recalculating through the basic data, thereby improving calculation efficiency and reducing system calculation pressure.

[0050] Model screening module 4 selects a target evaluation model from the model library based on the missing data labels obtained in the above steps. Here, the model library stores multiple evaluation models, each of which has different enterprise data as input, and at least one enterprise data is different in the inputs of different evaluation models, and the output of each evaluation model is an operational efficiency indicator.

[0051] Specifically, the model screening module 4 determines the missing basic data of the target enterprise based on the missing data label. The target evaluation model is searched from the model library, where the target evaluation model is an evaluation model that does not include the missing basic data among multiple evaluation models. Here, the evaluation models in the model library are pre-configured, and each model involves different basic data.

[0052] In this way, based on the existing enterprise data, the target model that does not involve missing data is matched in multiple models, avoiding the situation where operational efficiency indicators cannot be derived through the model due to missing data.

[0053] The indicator determination module 5 inputs the data of multiple enterprises into the target evaluation model to obtain the operating efficiency indicators of the target enterprises. Figure 3 , Figure 3 A schematic diagram of a processing flow for inputting multiple enterprise data into a target evaluation model to obtain target enterprise operation efficiency indicators is provided in an embodiment of the present application. Figure 3 As shown in:

[0054] S01. Input multiple enterprise data into the target evaluation model to obtain the model output result.

[0055] Here, according to the basic data required by the target model, the corresponding enterprise data is input into the target evaluation model. If the target model involves process data, the process data is input into the target evaluation model to reduce the calculation pressure of the system.

[0056] S02. Judge the validity of the model output results.

[0057] Here, if the existing enterprise data contains the full amount of basic data of the target model, the target model will output the value of the operating efficiency indicator. If the existing enterprise data does not contain the full amount of basic data of the target model, the target model will output a null value, and at this time, the model output result is considered invalid.

[0058] S03. If the model output result is valid, the model output result is determined as the operational efficiency indicator of the target enterprise.

[0059] S04. If the model output result is not valid, configure a temporary evaluation model based on multiple enterprise data. Figure 4 , Figure 4 A schematic diagram of a process for configuring a temporary evaluation model based on multiple enterprise data provided in an embodiment of the present application is shown in FIG. Figure 4 As shown in:

[0060] S041. Parameter construction.

[0061] Through data synchronization, multiple basic data participating in configuring the temporary evaluation model are selected from multiple existing enterprise data in the basic database as configuration parameters. If the name of the indicator type corresponding to the selected basic data is inconsistent with the standardized name, the name of the above indicator type is standardized and defined in a standard semantic manner, and the configuration parameter is named according to the standard name.

[0062] S042. Custom indicators.

[0063] In the process of building an evaluation model, custom indicators refer to the indicator information that is not available in the basic database and is generated as a construction parameter in a custom form. For example, when creating an indicator type for basic data under a certain operation theme, the code, standard name, alias, unit of measurement, indicator calculation rules and other information of the newly added indicator type are configured. At the same time, custom indicators can also be used as a factor in the calculation formula to participate in other formula calculations.

[0064] S043. Calculation formula configuration.

[0065] Calculation formula configuration refers to configuring calculation formulas using configuration parameters, basic symbols, numerical symbols and other objects to build calculation formulas for obtaining data at all levels of the model from basic data, so that relevant personnel can configure the calculation formulas in the model as needed.

[0066] S044. Configuration strategy.

[0067] Configuration strategy refers to adding application preconditions to the model. Different models have different corresponding preconditions. Here, the preconditions refer to the conditions for calling the model. You can set which model to match when a certain indicator type of data is missing in the enterprise data.

[0068] S045. Build a model.

[0069] Here, building a model refers to generating a corresponding evaluation model based on the building parameters, calculation formulas, and configuration strategies determined in the above steps.

[0070] S046, Model release.

[0071] Here, model publishing refers to generating an applicable temporary evaluation model, obtaining a temporary evaluation model that can calculate the target enterprise's operating efficiency indicators, and storing the temporary evaluation model in the model library for future use in actual enterprise economic evaluation work.

[0072] In this way, based on the existing enterprise data, the parameters contained in the evaluation model can be flexibly adjusted to construct an evaluation model for calculating the enterprise's operational efficiency indicators, thereby improving the scalability and universality of the system.

[0073] S05. Determine the operational efficiency indicators of the target enterprise based on the temporary evaluation model and multiple enterprise data.

[0074] S06. Storing the temporary evaluation model in the model library.

[0075] In this way, the newly obtained evaluation model is stored in the model library for later use in enterprise evaluation, thereby enhancing the universality of the system and improving the system's work efficiency.

[0076] Evaluation module 6 determines the risk evaluation index of the target enterprise based on the operational efficiency index.

[0077] Specifically, the obtained operating efficiency index is compared with a plurality of pre-set operating efficiency intervals. Here, each operating efficiency interval corresponds to a preset risk value, and the range of the operating efficiency interval and the risk value corresponding to the operating efficiency interval can be set according to actual conditions.

[0078] The preset risk value corresponding to the operating efficiency range including the operating efficiency indicator is determined as the risk assessment index.

[0079] Here, after obtaining the results of the enterprise risk assessment, they can be pushed to the enterprise through system messages, text messages, emails, etc., to help the enterprise understand the economic operation situation in a timely and convenient manner.

[0080] The enterprise evaluation system provided in the embodiment of the present application collects the enterprise data of the target enterprise, analyzes the missing of basic information in the enterprise data, and matches the appropriate evaluation model in the model library according to the missing of basic information. The collected enterprise information is input into the evaluation model, and the operation efficiency index is obtained by using the evaluation model to obtain the risk evaluation index of the target enterprise, thereby avoiding the situation that the enterprise risk evaluation index cannot be obtained due to missing data when conducting risk evaluation.

[0081] Based on the same inventive concept, an enterprise evaluation method corresponding to an enterprise evaluation system is also provided in the embodiment of the present application. Since the principle of solving the problem by the method in the embodiment of the present application is similar to the above-mentioned enterprise evaluation system in the embodiment of the present application, the implementation of the method can refer to the implementation of the system, and the repeated parts will not be repeated.

[0082] See also Figure 5 , Figure 5 A schematic diagram of an enterprise evaluation method provided in an embodiment of the present application is shown as follows: Figure 5 As shown in:

[0083] S1. Acquire multiple enterprise data of a target enterprise within a predetermined time period.

[0084] S2. Divide the data of multiple enterprises according to at least one operation theme for determining the operation efficiency index of the target enterprise to obtain multiple theme groups, each theme group corresponding to an operation theme.

[0085] S3. For each subject group, determine whether the enterprise data in the subject group contains the full amount of basic data under the corresponding operating subject. If not, output the missing data label, which is used to indicate the missing basic data in the subject group.

[0086] S4. Based on the missing data labels, select the target evaluation model from the model library.

[0087] S5. Input multiple enterprise data into the target evaluation model to obtain the operational efficiency indicators of the target enterprises.

[0088] S6. Determine the risk assessment index of the target enterprise based on the operational efficiency index.

[0089] Through the above method, when there is missing data in the collected enterprise data, an evaluation model that does not involve missing data can be selected in the model library for evaluation calculation based on the missing data, thereby avoiding the situation where the operational efficiency indicators cannot be derived through the model due to missing data.

[0090] See also Figure 6 , Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 6 As shown in , the electronic device 600 includes a processor 610 , a memory 620 and a bus 630 .

[0091] The memory 620 stores machine-readable instructions executable by the processor 610. When the electronic device 600 is running, the processor 610 communicates with the memory 620 via the bus 630. When the machine-readable instructions are executed by the processor 610, the above-mentioned Figure 5 The specific implementation of the enterprise evaluation method in the method embodiment shown can be found in the embodiment and will not be described in detail here.

[0092] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0093] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0094] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0095] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0096] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that can be executed by a processor. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0097] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. An enterprise evaluation system, It is characterized in that include: A data acquisition module, which acquires multiple enterprise data of a target enterprise within a predetermined time period; a classification module, which divides the plurality of enterprise data according to at least one operation theme for determining the operation efficiency index of the target enterprise to obtain a plurality of theme groups, each theme group corresponding to an operation theme; A missing judgment module calls an evaluation template for the target enterprise, wherein the evaluation template includes multiple sub-templates, each sub-template corresponds to an operation theme and the full amount of basic data under the operation theme; for each theme group, a sub-template corresponding to the operation theme of the theme group is selected, and based on the sub-template, whether the enterprise data in the theme group contains the full amount of basic data under the corresponding operation theme; for each theme group, if the full amount of basic data under the corresponding operation theme is not included, the missing basic data under the operation theme is determined, and a missing data label is output, wherein the missing data label is used to indicate the missing basic data in the theme group, and the missing data label indicates the operation theme of the missing data and the missing basic data under the operation theme; for each theme group that does not have missing basic data, the enterprise data in the theme group is input into the process expression formula corresponding to the operation theme of the theme group, the result calculated by the process expression formula is determined as the process data of the theme group, and the process data is stored in the enterprise data corresponding to the theme group, each sub-template corresponds to a process expression formula, and each process expression formula is used to obtain process data through basic data; A model screening module selects a target evaluation model from a model library based on the missing data labels; An indicator determination module, inputting the plurality of enterprise data into the target evaluation model to obtain an operational efficiency indicator of the target enterprise; An evaluation module determines a risk evaluation index of the target enterprise based on the operational efficiency indicator.

2. The enterprise evaluation system according to claim 1, It is characterized in that The plurality of enterprise data includes enterprise data of various indicator types. Wherein, the data acquisition module is also used for: Acquire enterprise data of multiple indicator types of the target enterprise within the predetermined time period from different data sources; Using the enterprise unified credit code to mark the acquired enterprise data of multiple indicator types, wherein each enterprise data includes an indicator type identifier and a source identifier, the indicator type identifier indicates the indicator type corresponding to the enterprise data, and the source identifier indicates the data source corresponding to the enterprise data; For each indicator type of enterprise data, extract the source identifier of the enterprise data of the indicator type. If there are multiple source identifiers, determine a target source identifier from the multiple source identifiers, and only retain the enterprise data of the indicator type corresponding to the target source identifier. If there is only one source identifier, retain the enterprise data of the indicator type corresponding to the unique source identifier. For each indicator type of enterprise data, the retained enterprise data of this indicator type is compared with the corresponding enterprise threshold data range. If the enterprise data of this indicator type is within the enterprise threshold data range, the enterprise data of this indicator type is retained; if the enterprise data of this indicator type is outside the enterprise threshold data range, the enterprise data of this indicator type is discarded.

3. The enterprise evaluation system according to claim 1, It is characterized in that The model library stores multiple evaluation models, each of which is inputted with different enterprise data, and at least one enterprise data is different in the inputs of different evaluation models, and the output of each evaluation model is an operational efficiency indicator; Wherein, the model screening module is also used for: Based on the missing data label, determining the missing basic data of the target enterprise; A target evaluation model is searched from the model library, where the target evaluation model is an evaluation model among multiple evaluation models, the input of which does not include the missing basic data.

4. The enterprise evaluation system according to claim 1, It is characterized in that The indicator determination module is also used for: Inputting the plurality of enterprise data into the target evaluation model to obtain a model output result; Conducting validity judgment on the output results of the model; If the model output result is valid, the model output result is determined as the operating efficiency indicator of the target enterprise; If the model output result is not valid, configuring a temporary evaluation model based on the plurality of enterprise data; Determining an operational efficiency index of the target enterprise based on the temporary evaluation model and the plurality of enterprise data; The temporary evaluation model is stored in the model library.

5. The enterprise evaluation system according to claim 4, It is characterized in that The indicator determination module is also used for: Selecting a plurality of basic data involved in configuring the temporary evaluation model from the plurality of enterprise data as configuration parameters; A calculation formula is configured based on the configuration parameters to obtain a temporary evaluation model capable of calculating the operating efficiency index of the target enterprise.

6. The enterprise evaluation system according to claim 1, It is characterized in that The evaluation module is also used to: Comparing the operational efficiency indicator with a plurality of pre-set operational efficiency intervals, wherein each operational efficiency interval corresponds to a pre-set risk value; The preset risk value corresponding to the operation efficiency interval including the operation efficiency indicator is determined as the risk assessment index.

7. A method for evaluating an enterprise. It is characterized in that include: Obtaining multiple enterprise data of the target enterprise within a predetermined time period; According to at least one operation theme for determining the operation efficiency index of the target enterprise, the plurality of enterprise data are divided to obtain a plurality of theme groups, each theme group corresponding to an operation theme; Calling an evaluation template for the target enterprise, the evaluation template includes a plurality of sub-templates, each sub-template corresponding to an operation theme and the full amount of basic data under the operation theme; for each theme group, selecting a sub-template corresponding to the operation theme of the theme group, and determining whether the enterprise data in the theme group contains the full amount of basic data under the corresponding operation theme based on the sub-template; for each theme group, if the full amount of basic data under the corresponding operation theme is not contained, determining the missing basic data under the operation theme, and outputting a missing data label, the missing data label is used to indicate the missing basic data in the theme group, and the missing data label indicates the operation theme of the missing data and the missing basic data under the operation theme; for each theme group that does not have missing basic data, inputting the enterprise data in the theme group into the process expression formula corresponding to the operation theme of the theme group, determining the result calculated by the process expression formula as the process data of the theme group, and storing the process data in the enterprise data corresponding to the theme group, each sub-template corresponds to a process expression formula, and each process expression formula is used to obtain process data through basic data; Based on the missing data labels, selecting a target evaluation model from a model library; Inputting the plurality of enterprise data into the target evaluation model to obtain an operational efficiency index of the target enterprise; Based on the operational efficiency indicator, a risk assessment index of the target enterprise is determined.

8. An electronic device, It is characterized in that include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the memory via the bus, and the processor executes the machine-readable instructions to perform the steps of the method as claimed in claim 7.

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