Risk enterprise positioning method, device, equipment, medium and program product

Abstract

The invention provides a risk enterprise positioning method and device, equipment, a medium and a program product, relates to the field of big data, and can be applied to the field of financial science and technology. The method comprises the steps that an enterprise information table and a risk aggregation table at the current moment are acquired, the enterprise information table comprises first information of all enterprises and second information of part of enterprises in a preset area, the risk aggregation table comprises risk levels, first information and / or second information of enterprises with marked risk levels in the preset area, the first information comprises first basic information, and the second information comprises second basic information; the second information comprises second basic information and enterprise industry and commerce information, and the two types of information coincide; based on the risk aggregation table, predicting the risk level of each enterprise in the enterprise information table by using a risk prediction model, and generating a comprehensive data table containing the first information, the second information and the risk level of each enterprise; and obtaining a target enterprise meeting a screening condition from the comprehensive data table, wherein the screening condition is determined from at least one of the first information, the second information and the risk level based on the user demand.

Description

Technical Field

[0001] This application relates to the field of big data, to fintech scenarios, and more specifically to a method, apparatus, equipment, medium, and program product for locating risky enterprises. Background Technology

[0002] With the continuous upgrading of risk products and the increasing number of data types, how to quickly find and accurately locate the risk information of target enterprises has become an urgent problem to be solved. The general enterprise positioning methods have the following problems: (1) Data dispersion: Enterprise information and risk status data are stored in different systems, and these systems are independent of each other. Data cannot be shared, and cross-database queries are required to obtain the relevant information of enterprises, resulting in low query efficiency; (2) Basic information and operating status information of newly established enterprises cannot be synchronized to the system in real time; (3) Single screening dimension: It can only support single-dimensional screening to obtain target enterprises. For example, screening enterprises within a certain business scope or screening enterprises within a certain geographical location, but it cannot screen enterprises located within a certain geographical location and with a certain risk characteristic, thus resulting in poor screening flexibility and other problems. Summary of the Invention

[0003] In view of the above problems, this application provides a method, apparatus, equipment, medium and program product for identifying risky enterprises.

[0004] According to a first aspect of this application, a risk enterprise positioning method is provided, comprising: obtaining an enterprise information table and a risk aggregation table at the current time, wherein the enterprise information table includes first information of all registered enterprises within a preset area and second information of some registered enterprises within the preset area, and the risk aggregation table includes the risk level, first information, and / or second information of enterprises within the preset area marked with risk levels, wherein the first information includes first basic information, and the second information includes second basic information and enterprise business registration information, wherein the first basic information and the second basic information respectively represent basic enterprise information and there is duplicate information between the first basic information and the second basic information; based on the risk aggregation table, using a risk prediction model to predict the risk level of each enterprise in the enterprise information table to obtain a comprehensive data table, wherein the comprehensive data table includes the first information, the second information, and the predicted risk level of each enterprise in the enterprise information table; and in response to receiving user filtering conditions, obtaining target enterprises that meet the filtering conditions from the comprehensive data table, wherein the filtering conditions are determined based on user needs from at least one of the first information, the second information, and the risk level.

[0005] According to an embodiment of this application, based on a risk aggregation table, a risk prediction model is used to predict the risk level of each enterprise in an enterprise information table. This includes: comparing the fields representing the unique codes of enterprises in the risk aggregation table and the enterprise information table; if the content of the field in the risk aggregation table is different from the content of the field in the enterprise information table, then the risk prediction model is used to predict the risk level of the enterprise corresponding to the field in the enterprise information table, wherein the risk prediction model is trained based on the risk aggregation table; if the content of the field in the risk aggregation table is the same as the content of the field in the enterprise information table, then the risk level of the enterprise corresponding to the field in the risk aggregation table is taken as the risk level of the enterprise corresponding to the field in the enterprise information table.

[0006] According to an embodiment of this application, obtaining target companies that meet the filtering criteria from a comprehensive data table includes: searching for target companies that meet the filtering criteria in the comprehensive data table according to a first preset field and a second preset field, wherein the first preset field represents the field corresponding to the unified identity identifier of the target company and all its associated companies, and the second preset field represents the field corresponding to the unique identifier of each of the target company's associated companies; if no target company is found, then searching for target companies that meet the filtering criteria in the comprehensive data table according to the second preset field; if no target company is still found, then searching for target companies that meet the filtering criteria in the comprehensive data table according to the field representing the company's unique code.

[0007] According to an embodiment of this application, the risk enterprise location method further includes: if a new enterprise is acquired, then based on the risk aggregation table, using a risk prediction model to predict the risk level of the new enterprise; calculating the sum of the acquisition time and the establishment time of the new enterprise to obtain the entry time of the new enterprise stored in the enterprise information table, and sorting the entry times in ascending order; and sending the new enterprises that meet the screening conditions to the user in the sorted order.

[0008] According to an embodiment of this application, the enterprise information table at the current moment is obtained by: updating a first data table every first preset time interval, and updating a second data table every second preset time interval, wherein the first data table includes first information of all registered enterprises within a preset area, and the second data table includes second information of some registered enterprises within the preset area; integrating the non-duplicate information in the first data table and the second data table at the current moment, the enterprise information table at the current moment is obtained. According to an embodiment of this application, before predicting the risk level of each enterprise in the enterprise information table using a risk prediction model, the process includes: standardizing each field in the first data table, the second data table, the enterprise information table, and the risk aggregation table respectively.

[0009] Another aspect of this application provides a risk enterprise positioning device, comprising: an enterprise information table and a risk aggregation table acquisition module, used to acquire the enterprise information table and the risk aggregation table at the current time, wherein the enterprise information table includes first information of all registered enterprises within a preset area and second information of some registered enterprises within the preset area, and the risk aggregation table includes the risk level, first information and / or second information of enterprises within the preset area marked with risk levels, the first information including first basic information, the second information including second basic information and enterprise business registration information, the first basic information and the second basic information respectively representing enterprise basic information and there is duplicate information between the first basic information and the second basic information; a comprehensive data table acquisition module, used to predict the risk level of each enterprise in the enterprise information table based on the risk aggregation table using a risk prediction model to obtain a comprehensive data table, wherein the comprehensive data table includes the first information, second information and predicted risk level of each enterprise in the enterprise information table; and a risk enterprise positioning module, used to, in response to receiving user filtering conditions, acquire target enterprises that meet the filtering conditions from the comprehensive data table, wherein the filtering conditions are determined based on user needs from at least one of the first information, second information and risk level.

[0010] Another aspect of this application provides an electronic device, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0011] Another aspect of this application provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0012] Another aspect of this application provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described method.

[0013] The risk enterprise positioning method of this application constructs a comprehensive data table that integrates enterprise information (including first information of all registered enterprises in a preset area and second information of some key enterprises) and risk level information in a risk aggregation table. It then uses a risk prediction model to predict the risk level of each enterprise in the enterprise information table. This allows users to efficiently and accurately obtain target enterprises with multi-dimensional characteristics from the comprehensive data table based on flexible selection criteria from the first information, second information, and risk level. This effectively solves the problem of low query efficiency caused by data dispersion, improving query efficiency, filtering flexibility, and positioning accuracy. This risk enterprise positioning method can help users quickly acquire the customer base they want to expand into. Attached Figure Description

[0014] The above-mentioned contents, other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0015] Figure 1 The illustrations depict application scenarios of the risk enterprise location method, apparatus, device, medium, and program products according to embodiments of this application.

[0016] Figure 2 A flowchart illustrating a risk enterprise identification method according to an embodiment of this application is shown schematically;

[0017] Figure 3 The flowchart illustrating the method for obtaining the risk level of each enterprise in the enterprise information table according to an embodiment of this application is shown in the illustration.

[0018] Figure 4 This illustration schematically shows a flowchart of retrieving target companies that meet the filtering criteria from a comprehensive data table according to an embodiment of this application;

[0019] Figure 5 A flowchart illustrating a method for acquiring a new enterprise according to an embodiment of this application is shown schematically.

[0020] Figure 6 A flowchart illustrating a method for obtaining an enterprise information table according to an embodiment of this application is shown in the illustration.

[0021] Figure 7 This schematic diagram illustrates a structural block diagram of an enterprise risk positioning device according to an embodiment of this application;

[0022] Figure 8 A block diagram schematically illustrates an electronic device suitable for implementing a venture enterprise positioning method according to an embodiment of this application. Detailed Implementation

[0023] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0024] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0025] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0026] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0027] In the technical solution of this application, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0028] In scenarios involving automated decision-making using personal information, the methods, devices, and systems provided in this application all offer users corresponding entry points for choosing to agree to or reject the automated decision-making results. If the user chooses to reject, the process proceeds to the expert decision-making stage. Here, "automated decision-making" refers to the activity of automatically analyzing and evaluating an individual's behavioral habits, interests, or economic, health, and credit status through computer programs, and then making a decision. Here, "expert decision-making" refers to the activity of making decisions by personnel who specialize in a particular field, possess specialized experience, knowledge, and skills, and have reached a certain level of professional expertise.

[0029] Figure 1 The illustrations depict application scenarios of risk enterprise location methods, apparatus, devices, media, and program products according to embodiments of this application.

[0030] like Figure 1As shown, application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0031] Users can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0032] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0033] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0034] It should be noted that the risk enterprise location method provided in this application embodiment can generally be executed by server 105. Correspondingly, the risk enterprise location method apparatus provided in this application embodiment can generally be located in server 105. The risk enterprise location method provided in this application embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the risk enterprise location method apparatus provided in this application embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0035] It should be understood that Figure 1The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0036] The following will be based on Figure 1 The described scene, through Figures 2-6 The risk enterprise identification method according to the embodiments of this application will be described in detail.

[0037] Figure 2 A flowchart illustrating a risk enterprise identification method according to an embodiment of this application is shown.

[0038] like Figure 2 As shown, the risk enterprise identification method 200 of this embodiment includes operations S210 to S230.

[0039] In operation S210, the enterprise information table and risk aggregation table at the current time are obtained. The enterprise information table includes the first information of all registered enterprises within the preset area and the second information of some registered enterprises within the preset area. The risk aggregation table includes the risk level, first information and / or second information of enterprises marked with risk level within the preset area. The first information includes first basic information and the second information includes second basic information and enterprise business registration information. The first basic information and the second basic information respectively represent the basic information of the enterprise and there is duplicate information between the first basic information and the second basic information.

[0040] In the embodiments of this application, during operation S210, the first information covers the first basic information of registered enterprises within the whole country or other preset areas, which may specifically include enterprise name, enterprise geographical location, operating status (existing / cancelled / revoked), registered capital, unified social credit code, etc.

[0041] The second type of information targets registered companies that users are particularly interested in. This information is obtained through a multi-source heterogeneous data collection method, which involves acquiring different information about the same company from multiple institutions and / or business systems. For example, this includes acquiring the company's business scope, intellectual property details, administrative license information, administrative penalty records, annual financial reports, and legal proceedings, as well as second basic information such as registered capital, establishment date, legal representative or person in charge, and detailed operating status. The company's business information and second basic information come from different institutions and / or business systems. Furthermore, registered companies that users are particularly interested in can be determined by preset geographical locations (such as administrative region codes and geographical distances) or industry tags (such as finance / healthcare / education). For example, a user might be interested in a company in the education sector within their own region, or a company in the financial sector in a region a certain distance away from their location.

[0042] In operation S220, based on the risk aggregation table, the risk level of each enterprise in the enterprise information table is predicted using the risk prediction model to obtain a comprehensive data table. The comprehensive data table includes the first information, second information, and predicted risk level of each enterprise in the enterprise information table.

[0043] In operation S230, in response to receiving the user's filtering criteria, target companies that meet the filtering criteria are retrieved from the comprehensive data table, wherein the filtering criteria are determined based on user requirements from at least one of first information, second information, and risk level.

[0044] In the embodiments of this application, during operation S230, the user's multi-dimensional filtering conditions can be received through a visual interactive interface or other means. These filtering conditions can be freely combined with at least one of the first information, second information, and risk level to accurately locate the target enterprise from a comprehensive data table with a large amount of data.

[0045] For example, a user's screening criteria might be: accounting agencies with a risk level of B within the user's administrative region. Based on this screening criterion, the target companies the user wants to acquire can be determined from the comprehensive data table. Here, the risk level represents the risk status of the company, including credit risk and telecommunications fraud risk, etc. The user's screening criteria may also include company location information, operating status information, registered capital, and risk level, etc.

[0046] According to the embodiments of this application, filtering target enterprises from multiple dimensions can effectively solve the problem of low query efficiency caused by data dispersion, improve query efficiency, filtering flexibility and positioning accuracy, and help users quickly obtain the customer groups they want to expand.

[0047] Figure 3 The flowchart illustrating the method for obtaining the risk level of each enterprise in the enterprise information table according to an embodiment of this application is shown in the illustration.

[0048] like Figure 3 As shown, the method for obtaining the risk level of each enterprise in the enterprise information table of this embodiment includes operations S310 to S330.

[0049] In operation S310, compare the fields representing the unique codes of enterprises in the risk aggregation table and the enterprise information table.

[0050] In operation S320, if the content of a field in the risk aggregation table is different from the content of the field in the enterprise information table, the risk prediction model is used to predict the risk level of the enterprise corresponding to the field in the enterprise information table. The risk prediction model is trained based on the risk aggregation table.

[0051] In operation S330, if the content of a field in the risk aggregation table is the same as the content of the field in the enterprise information table, then the risk level of the enterprise corresponding to the field in the risk aggregation table will be used as the risk level of the enterprise corresponding to the field in the enterprise information table.

[0052] In the embodiments of this application, during operation S310, the risk aggregation table is obtained through historical data statistics. It includes the enterprise risk level (such as AE level) and the corresponding first information and / or second information of the enterprise. For example, the risk level of a certain enterprise is A level, and the risk level of a certain enterprise located in a certain geographical location is E level, etc. The higher the risk level, the higher the risk degree of the enterprise.

[0053] In the embodiments of this application, during operation S320, it is assumed that the field representing the unique code of an enterprise is the Unified Social Credit Code field. For the same enterprise, the enterprise has a unique Unified Social Credit Code. If the content corresponding to the Unified Social Credit Code field in the risk aggregation table (i.e., the enterprise corresponding to the Unified Social Credit Code) is different from the enterprise corresponding to the same Unified Social Credit Code field in the enterprise information table, it means that there is no enterprise corresponding to the Unified Social Credit Code in the enterprise information table. In this case, it is necessary to use the risk prediction model to predict the risk level of the enterprise in the enterprise information.

[0054] In the embodiments of this application, during operation S330, assuming that the field representing the unique code of an enterprise is the Unified Social Credit Code field, if the enterprise corresponding to a certain Unified Social Credit Code field in the risk aggregation table is the same as the enterprise corresponding to the same Unified Social Credit Code field in the enterprise information table, it means that the enterprise exists in the enterprise information table, and the risk level of the enterprise in the risk aggregation table is taken as the risk level of the enterprise in the enterprise information table.

[0055] In the embodiments of this application, the risk profile of an enterprise can be determined based on the risk level of each enterprise in the enterprise information table and the business registration information of each enterprise. For example, if an enterprise has a high risk level and there are records of dishonesty in its business registration information, the enterprise can be classified as a dishonest enterprise. For another example, if an enterprise has no revenue record or tax record for a long period of time (such as half a year, a year or longer), or if the registered address is false information or the registered address changes frequently, the enterprise can be considered to be a shell company.

[0056] According to embodiments of this application, by obtaining the risk level of each enterprise in the enterprise information table based on the field representing the enterprise's unique code, the risk level coverage and prediction accuracy can be improved.

[0057] Figure 4 The flowchart illustrating the process of retrieving target companies that meet the filtering criteria from a comprehensive data table according to an embodiment of this application is shown in the illustration.

[0058] like Figure 4 As shown, the process of obtaining target companies that meet the filtering criteria from the comprehensive data table in this embodiment includes operations S410 to S430.

[0059] In operation S410, the target enterprise that meets the filtering conditions is searched in the comprehensive data table according to the first preset field and the second preset field. The first preset field represents the field corresponding to the unified identity identifier of the target enterprise and all its related enterprises, and the second preset field represents the field corresponding to the unique identifier of each of the target enterprise's related enterprises.

[0060] In operation S420, if no target company is found, the target company that meets the filtering conditions is searched in the comprehensive data table according to the second preset field.

[0061] In operation S430, if the target company is still not found, the target company that meets the filtering criteria is searched in the comprehensive data table based on the field that represents the company's unique code.

[0062] For example, when filtering target companies based on screening criteria, you can first filter by a first preset field and a second preset field. Let's assume the first preset field is a field that represents the unique identifier of a company and its related companies. Related companies can be understood as subsidiaries of the company or companies whose legal representatives are the same person. The second preset field is a field that represents the unique identifier of related companies. Suppose a user wants to find companies within 10km of their location with a risk level of A and whose business scope is in the financial sector. There are many companies in the comprehensive data table that meet these screening criteria, many of which are branches of a single company. In this case, you can further filter these companies by the first and second preset fields to more accurately find companies that meet the user's needs. For example, the first preset field for company A might be "UID" (Unique ID). The first preset field for all of Company A's affiliated companies is "UID," but the second preset fields for each of Company A's affiliated companies are different. For example, the second preset field for Company A's first affiliated company is "UID1," the second for the second is "UID2," and the third is "UID3," etc. After the user inputs filter criteria, Company A, Company B, Company C, etc., are retrieved from the comprehensive data table. Based on the first preset fields of these companies, the affiliated companies associated with each company are further retrieved. Finally, these affiliated companies, as well as Company A, Company B, Company C, etc., are all displayed to the user. If the target company does not belong to Company A, Company B, Company C, or their affiliated companies, or if the target company is not listed, the user is not informed. If the relationships between target companies are unclear, users may not be able to find the target company they are looking for among these companies. In this case, users can adjust the filter criteria, for example, by adjusting the filter criteria to "branch companies within 10km of their location with a risk level of A and whose business scope is in the financial field". This way, they can find companies based solely on the second preset field, and further filter from the comprehensive data table to find companies that meet the criteria, providing the subsidiaries under each parent company that meet the filter criteria. If users still cannot find the target company among these subsidiaries, they can filter the target company again by adjusting the filter criteria. For example, they can directly set the filter criteria to the company name or the unified social credit code, which represents the company's unique code, and filter the target company from the comprehensive data table based on this specific information.

[0063] Furthermore, since the amount of enterprise data obtained by filtering according to the first and second preset fields is relatively large, if the relationship between related enterprises is unclear, it may be impossible to accurately obtain the target enterprise. Further filtering according to the second preset field can obtain enterprises with a more precise range, thereby making up for the problem that the target enterprise cannot be obtained due to the unclear relationship between related enterprises. If the target enterprise is still not obtained, the information representing the unique code of the enterprise is combined for further searching, thereby accurately locating the target enterprise.

[0064] According to embodiments of this application, by utilizing various filtering strategies, such as combining a first preset field and a second preset field, or filtering target companies from a comprehensive data table based solely on the second preset field, or based on a field representing a unique enterprise code, the accuracy of target company location and the comprehensiveness of target company associations can be improved, thereby enhancing search efficiency.

[0065] Figure 5 A flowchart illustrating a method for acquiring a new enterprise according to an embodiment of this application is shown schematically.

[0066] like Figure 5 As shown, the method for acquiring new enterprises in this embodiment includes operations S510 to S530.

[0067] In operation S510, if a new enterprise is acquired, the risk level of the new enterprise is predicted using a risk prediction model based on the risk aggregation table.

[0068] In operation S520, the sum of the acquisition time and the establishment time of the new enterprise is calculated to obtain the entry time of the new enterprise into the enterprise information table, and the entry time is sorted in ascending order.

[0069] In the S530 operation, newly added enterprises that meet the filtering criteria are sent to the user in sorted order.

[0070] For example, in operation S530, the filtering criteria can be "enterprises located in a certain region that have been established within the past 30 days and are in operation" and "enterprises located in a certain region with enterprise type code 1190", where enterprise type code 1190 indicates a limited liability company.

[0071] In the embodiments of this application, the problem of delayed synchronization of new enterprise information is solved by timely including newly added enterprises in the enterprise information table; the sorting and push based on the entry time ensures that newly added risky enterprises are given priority exposure in the early stage, thereby improving the enterprise's customer acquisition scope and enterprise coverage.

[0072] Figure 6 A flowchart illustrating a method for obtaining an enterprise information table according to an embodiment of this application is shown.

[0073] like Figure 6 As shown, the flowchart of the enterprise information table acquisition method in this embodiment includes operations S610 to S620.

[0074] In operation S610, the first data table is updated once every first preset time interval, and the second data table is updated once every second preset time interval. The first data table includes the first information of all registered enterprises within the preset area, and the second data table includes the second information of some registered enterprises within the preset area.

[0075] In operation S620, the non-duplicate information in the first data table and the second data table at the current moment is integrated to obtain the enterprise information table at the current moment.

[0076] In the embodiments of this application, during operation S610, to construct the enterprise information table, the system obtains information from two data sources: a first data table and a second data table. The first data table covers the first information of all registered enterprises within a preset area, and its data is updated at relatively long intervals, typically on a daily or monthly basis, i.e., a first preset time. The second data table contains the second information of some registered enterprises within the preset area, and its data is updated more frequently, prioritizing timeliness, i.e., a second preset time. Furthermore, the second basic information in the second information can include the first basic information in the first information, or it can include a portion of the first basic information. There only needs to be overlapping information between the first and second basic information, so that information about the same enterprise at different dimensions can be found in the first and second data tables based on the overlapping information.

[0077] In the embodiments of this application, after obtaining the first data table and the second data table at the current moment in operation S620, the system merges the contents of the first data table and the second data table to generate the enterprise information table at the current moment. This table integrates information from two data sources, ensuring comprehensive coverage of all registered enterprises while providing more timely and detailed data for key enterprises.

[0078] In the embodiments of this application, the first data table contains a large amount of data, while the second data table contains a smaller amount of data, which is detailed information about some companies that users are concerned about. By periodically obtaining these two data tables, not only can the problem of data dispersion be solved, but also the amount of data transmission and the probability of data congestion can be reduced. By taking the union of these two data tables, the enterprise information table can be obtained, which can ensure the comprehensiveness of enterprise information.

[0079] Furthermore, before using the risk prediction model to predict the risk level of each enterprise in the enterprise information table, the following steps are taken: standardize each field in the first data table, the second data table, the enterprise information table, and the risk aggregation table respectively.

[0080] In the embodiments of this application, standardization processing includes semantic parsing, format unification, and structured conversion. For example, key entity elements in a field can be parsed using natural language processing technology, and standardization processing operations such as format conversion and data cleaning can be performed on numerical units. For instance, the unified social credit code of an enterprise can be processed into a unified format, the type of currency can be uniformly converted into RMB or USD, and numerical values ​​representing the same meaning can be processed into the same format.

[0081] In the embodiments of this application, standardizing fields can reduce the impact of data format differences, improve data consistency, and lay the foundation for accurately obtaining target companies in the future.

[0082] Based on the above-mentioned venture enterprise positioning method, this application also provides a venture enterprise positioning device. The following will be combined with... Figure 7 The device is described in detail.

[0083] Figure 7 A schematic block diagram of a risk enterprise location device according to an embodiment of this application is shown.

[0084] like Figure 7 As shown, the risk enterprise positioning device 700 of this embodiment includes an enterprise information table and risk aggregation table acquisition module 710, a comprehensive data table acquisition module 720, and a risk enterprise positioning module 730.

[0085] The enterprise information table and risk aggregation table acquisition module 710 is used to acquire the enterprise information table and risk aggregation table at the current time. The enterprise information table includes first information of all registered enterprises within a preset area and second information of some registered enterprises within the preset area. The risk aggregation table includes the risk level, first information, and / or second information of enterprises within the preset area that are marked with risk levels. The first information includes first basic information, and the second information includes second basic information and enterprise business registration information. The first and second basic information respectively represent basic enterprise information, and there is duplicate information between the first and second basic information. In one embodiment, the enterprise information table and risk aggregation table acquisition module 710 can be used to perform the operation S210 described above, which will not be repeated here.

[0086] The comprehensive data table acquisition module 720 is used to predict the risk level of each enterprise in the enterprise information table based on the risk aggregation table and using a risk prediction model to obtain a comprehensive data table. The comprehensive data table includes first information, second information, and the predicted risk level of each enterprise in the enterprise information table. In one embodiment, the comprehensive data table acquisition module 720 can be used to perform the operation S220 described above, which will not be repeated here.

[0087] The risk enterprise positioning module 730 is used to retrieve target enterprises that meet the filtering conditions from a comprehensive data table in response to receiving user filtering conditions. The filtering conditions are determined based on user needs from at least one of first information, second information, and risk level. In one embodiment, the risk enterprise positioning module 730 can be used to perform the operation S230 described above, which will not be repeated here.

[0088] In embodiments of this application, the comprehensive data table acquisition module 720 includes a field comparison module for comparing the fields representing the unique codes of enterprises in the risk aggregation table and the enterprise information table, and a risk prediction model module for predicting the risk level of the enterprise corresponding to the field in the enterprise information table using the risk prediction model if the content of the field in the risk aggregation table is different from the content of the field in the enterprise information table, wherein the risk prediction model is trained based on the risk aggregation table; if the content of the field in the risk aggregation table is the same as the content of the field in the enterprise information table, the risk level of the enterprise corresponding to the field in the risk aggregation table is taken as the risk level of the enterprise corresponding to the field in the enterprise information table.

[0089] In the embodiments of this application, the risk enterprise positioning module 730 includes a first filtering module, used to search for target enterprises that meet the filtering conditions in a comprehensive data table according to a first preset field and a second preset field, wherein the first preset field represents the field corresponding to the unified identity identifier of the target enterprise and all its associated enterprises, and the second preset field represents the field corresponding to the unique identifier of each of the target enterprise's associated enterprises; a second filtering module, used to search for target enterprises that meet the filtering conditions in the comprehensive data table according to the second preset field if no target enterprise is found; and a third filtering module, used to search for target enterprises that meet the filtering conditions in the comprehensive data table according to the field representing the enterprise's unique code if no target enterprise is found.

[0090] In the embodiments of this application, the risk enterprise location device 700 is further configured to: if a new enterprise is acquired, predict the risk level of the new enterprise based on the risk aggregation table and the risk prediction model; calculate the sum of the acquisition time and the establishment time of the new enterprise to obtain the entry time of the new enterprise stored in the enterprise information table, sort the entry times in ascending order; and send the new enterprises that meet the screening conditions to the user in the sorted order.

[0091] In the embodiments of this application, the enterprise information table and risk aggregation table acquisition module 710 is further used to: update the first data table once every first preset time, and update the second data table once every second preset time, wherein the first data table includes the first information of all registered enterprises within a preset area, and the second data table includes the second information of some registered enterprises within the preset area; integrate the non-duplicate information in the first data table and the second data table at the current moment to obtain the enterprise information table at the current moment.

[0092] In the embodiments of this application, the comprehensive data table acquisition module 720 is further used to: standardize each field in the first data table, the second data table, the enterprise information table, and the risk aggregation table respectively.

[0093] According to embodiments of this application, any multiple modules among the enterprise information table and risk aggregation table acquisition module 710, the comprehensive data table acquisition module 720, and the risk enterprise positioning module 730 can be merged into one module, or any one of these modules can be split into multiple modules. Alternatively, at least some of the functions of one or more of these modules can be combined with at least some of the functions of other modules and implemented in one module. According to embodiments of this application, at least one of the enterprise information table and risk aggregation table acquisition module 710, the comprehensive data table acquisition module 720, and the risk enterprise positioning module 730 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any one of the three implementation methods or a suitable combination of any of them. Alternatively, at least one of the enterprise information table and risk aggregation table acquisition module 710, comprehensive data table acquisition module 720, and risk enterprise positioning module 730 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0094] Figure 8 A block diagram schematically illustrates an electronic device suitable for implementing a venture enterprise positioning method according to an embodiment of this application.

[0095] like Figure 8As shown, an electronic device 800 according to an embodiment of this application includes a processor 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage portion 808 into a random access memory (RAM) 803. The processor 801 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 801 may also include onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this application.

[0096] RAM 803 stores various programs and data required for the operation of electronic device 800. Processor 801, ROM 802, and RAM 803 are interconnected via bus 804. Processor 801 executes various operations of the method flow according to embodiments of this application by executing programs in ROM 802 and / or RAM 803. It should be noted that the programs may also be stored in one or more memories other than ROM 802 and RAM 803. Processor 801 may also execute various operations of the method flow according to embodiments of this application by executing programs stored in said one or more memories.

[0097] According to embodiments of this application, the electronic device 800 may further include an input / output (I / O) interface 805, which is also connected to a bus 804. The electronic device 800 may also include one or more of the following components connected to the input / output (I / O) interface 805: an input section 806 including a keyboard, mouse, etc.; an output section 807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the input / output (I / O) interface 805 as needed. A removable medium 811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 810 as needed so that computer programs read from it can be installed into the storage section 808 as needed.

[0098] This application also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0099] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this application, the computer-readable storage medium may include ROM 802 and / or RAM 803 and / or one or more memories other than ROM 802 and RAM 803 described above.

[0100] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to enable the computer system to implement the risk enterprise positioning method provided in the embodiments of this application.

[0101] When the computer program is executed by the processor 801, it performs the functions defined in the system / apparatus of this application embodiment. According to the embodiments of this application, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0102] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 809, and / or installed from a removable medium 811. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0103] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 809, and / or installed from the removable medium 811. When the computer program is executed by the processor 801, it performs the functions defined in the system of this application embodiment. According to the embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0104] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0105] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0106] Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application.

Claims

1. A method for identifying venture capital firms, characterized in that, The method includes: Obtain the enterprise information table and risk aggregation table at the current moment. The enterprise information table includes first information of all registered enterprises within a preset area and second information of some registered enterprises within the preset area. The risk aggregation table includes the risk level of enterprises marked with risk level within the preset area, the first information and / or the second information. The first information includes first basic information, and the second information includes second basic information and enterprise business registration information. The first basic information and the second basic information respectively represent enterprise basic information and there is duplicate information between the first basic information and the second basic information. Based on the risk aggregation table, the risk level of each enterprise in the enterprise information table is predicted using a risk prediction model to obtain a comprehensive data table, wherein the comprehensive data table includes the first information, the second information, and the predicted risk level of each enterprise in the enterprise information table; In response to receiving the user's filtering criteria, target companies that meet the filtering criteria are obtained from the comprehensive data table, wherein the filtering criteria are determined based on the user's needs from at least one of the first information, the second information, and the risk level.

2. The method according to claim 1, characterized in that, The step of predicting the risk level of each enterprise in the enterprise information table based on the risk aggregation table and using a risk prediction model includes: Compare the fields representing the unique enterprise code in the risk aggregation table with those in the enterprise information table; If the content of the field in the risk aggregation table is different from the content of the field in the enterprise information table, then the risk prediction model is used to predict the risk level of the enterprise corresponding to the field in the enterprise information table, wherein the risk prediction model is trained based on the risk aggregation table; If the content of the field in the risk aggregation table is the same as the content of the field in the enterprise information table, then the risk level of the enterprise corresponding to the field in the risk aggregation table shall be used as the risk level of the enterprise corresponding to the field in the enterprise information table.

3. The method according to claim 2, characterized in that, The step of obtaining target companies that meet the filtering criteria from the comprehensive data table includes: The target enterprise that meets the filtering conditions is searched in the comprehensive data table according to the first preset field and the second preset field. The first preset field represents the field corresponding to the unified identity identifier of the target enterprise and all its related enterprises, and the second preset field represents the field corresponding to the unique identifier of each of the related enterprises of the target enterprise. If the target company is not found, then search for the target company that meets the filtering conditions in the comprehensive data table according to the second preset field; If the target company is still not found, then the target company that meets the filtering conditions is searched in the comprehensive data table based on the field representing the unique code of the company.

4. The method according to claim 1, characterized in that, The method further includes: If a new enterprise is obtained, the risk level of the new enterprise is predicted using the risk prediction model based on the risk aggregation table. Calculate the sum of the acquisition time and the establishment time of the newly added enterprise to obtain the entry time of the newly added enterprise into the enterprise information table, and sort the entry times in ascending order; The newly added enterprises that meet the filtering criteria will be sent to the user in the sorted order.

5. The method according to claim 1, characterized in that, The current enterprise information table is obtained through the following methods: The first data table is updated every first preset time interval, and the second data table is updated every second preset time interval. The first data table includes first information of all registered enterprises within the preset area, and the second data table includes second information of some registered enterprises within the preset area. By integrating the non-duplicate information from the first data table and the second data table at the current moment, the enterprise information table at the current moment is obtained.

6. The method according to claim 5, characterized in that, Before using the risk prediction model to predict the risk level of each enterprise in the enterprise information table, the following steps are included: Each field in the first data table, the second data table, the enterprise information table, and the risk aggregation table is standardized.

7. A risk enterprise positioning device, characterized in that, The device includes: The enterprise information table and risk aggregation table acquisition module is used to acquire the enterprise information table and risk aggregation table at the current time. The enterprise information table includes first information of all registered enterprises within a preset area and second information of some registered enterprises within the preset area. The risk aggregation table includes the risk level of enterprises marked with risk level within the preset area, the first information and / or the second information. The first information includes first basic information, and the second information includes second basic information and enterprise business registration information. The first basic information and the second basic information respectively represent the basic information of the enterprise, and there is duplicate information between the first basic information and the second basic information. The comprehensive data table acquisition module is used to predict the risk level of each enterprise in the enterprise information table based on the risk aggregation table and using a risk prediction model to obtain a comprehensive data table, wherein the comprehensive data table includes the first information, the second information and the predicted risk level of each enterprise in the enterprise information table; The risk enterprise positioning module is used to, in response to receiving user filtering conditions, retrieve target enterprises that meet the filtering conditions from the comprehensive data table, wherein the filtering conditions are determined based on the user's needs from at least one of the first information, the second information, and the risk level.

8. An electronic device, comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 6.

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