Enterprise intelligent assessment and transaction risk early warning system and method

Abstract

The invention relates to the technical field of enterprise transaction assessment, and discloses an enterprise intelligent assessment and transaction risk early warning system and method, and the method comprises the steps: obtaining target information, forming analysis data according to the target information, forming judgment data according to the analysis data, and assessing the transaction risk of a target enterprise according to the judgment data. According to the enterprise intelligent assessment and transaction risk early warning system and method, whether the enterprise has transaction conditions such as ex-migration or not is judged according to data adjustment of the enterprise, whether the enterprise has transaction risks such as ex-migration or not is judged according to data adjustment of an enterprise principal, and according to the ex-migration conditions of other enterprises in the same industry in the same region, the enterprise intelligent assessment and transaction risk early warning can be realized. And the transaction risk of the target enterprise is judged, so that adverse effects caused by transactions such as ex-migration of the enterprise are timely handled, and economic losses caused by the transactions such as ex-migration of the enterprise are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise change assessment, and in particular to an enterprise intelligent assessment and change risk early warning system and method. Background Art

[0002] Enterprise intelligent assessment and abnormal risk early warning systems are usually designed to help enterprises identify and manage potential risks, optimize operations, and improve decision-making capabilities. Such systems combine big data analysis, artificial intelligence, machine learning and other technologies to monitor various indicators and risk factors in enterprise operations in real time, including: data collection and integration, risk assessment models, real-time monitoring and early warning, risk early warning and decision support, and system optimization and feedback. They can not only help enterprises prevent potential risks, but also take timely measures when risks occur to reduce losses and impacts;

[0003] The system needs to collect data from multiple sources, clean and integrate various data, build the enterprise's data warehouse, define key indicators, and use statistical analysis, machine learning and other methods to establish risk assessment models. The system analyzes data in real time, detects abnormal situations or trend changes, and sets thresholds. When it detects that the indicators exceed the preset thresholds, the system will automatically issue early warning notifications. The system can inform relevant personnel of risk information through emails, text messages, internal notifications, etc., provide risk reports, recommended measures, and help decision makers develop response strategies. According to the actual situation and the warning effect, the risk assessment model is continuously optimized. With the development of data volume and analysis technology, the system functions and models are regularly upgraded;

[0004] The system determines the functional requirements and warning scope of the system through demand analysis, selects appropriate data analysis technologies and tools through technology selection, designs and develops the system architecture through system development, comprehensively tests the system through testing and verification to ensure its stability and accuracy, deploys the system to the production environment through deployment and training, and trains relevant personnel, continuously monitors system operation through maintenance and upgrades, and performs regular maintenance and functional upgrades.

[0005] The existing enterprise intelligent assessment and abnormal risk warning system and method cannot be adjusted according to the enterprise's data to determine whether the enterprise has abnormal changes such as relocation. It cannot be adjusted according to the data of the enterprise's person in charge to determine whether the enterprise has abnormal risk of relocation, etc. It cannot judge the abnormal risk of the target enterprise based on the relocation of other enterprises in the same industry in the same region, and thus cannot respond to the adverse effects caused by abnormal changes such as enterprise relocation in a timely manner. Its practicality has certain limitations. Summary of the invention

[0006] The present invention provides an enterprise intelligent assessment and abnormal risk early warning system and method, which are used to promote the solution of the problems mentioned in the background technology.

[0007] The present invention provides the following technical solution: an enterprise intelligent assessment and abnormal risk early warning system, comprising:

[0008] Collection module: obtains target information to determine whether the target enterprise has any changes such as relocation;

[0009] Analysis module: Based on the target information and enterprise analysis strategies, analytical data is generated to determine whether the target enterprise has any changes in its business within the target area, and further determine whether the target enterprise has any changes such as relocation;

[0010] Judgment module: Based on the analysis data, the judgment data is formed through the misjudgment analysis strategy to judge the operation mode of enterprises in the target area that are in the same industry as the target enterprise, so as to determine the risk of abnormal movement of the target enterprise;

[0011] Evaluation module: Based on the judgment data, the target enterprise's change risk is evaluated so as to take timely remedial measures and reduce the adverse effects caused by the enterprise change.

[0012] The present invention also discloses a method for using an enterprise intelligent assessment and abnormal risk early warning system, wherein: the acquisition of target information is specifically:

[0013] Obtain the first target data of the target enterprise;

[0014] Obtaining first determination data of the target enterprise;

[0015] If the first determination data = the first target data, then the enterprise analysis strategy is executed;

[0016] If the first judgment data ≠ the first target data, it is determined that the target enterprise has a small risk of abnormal change, and no abnormal risk warning is issued.

[0017] As a method of using the enterprise intelligent assessment and abnormal risk early warning system described in the present invention, wherein: the enterprise analysis strategy is specifically:

[0018] Acquire the second target data of the target enterprise;

[0019] Obtaining second determination data of the target enterprise;

[0020] If the second determination data = the second target data, the target enterprise is determined to have a low risk of change, and no change risk warning is issued;

[0021] If the second determination data ≠ the second target data, the change determination strategy is executed.

[0022] As a method of using the enterprise intelligent assessment and change risk early warning system described in the present invention, the change determination strategy is specifically:

[0023] Acquire determination data of a target enterprise, wherein the determination data includes first determination data and second determination data;

[0024] Get the target database;

[0025] Extracting all enterprise data sets corresponding to the third data identical to the first determination data in the target database as determination enterprise data;

[0026] Extract the time data corresponding to each determined enterprise data and set it as the target time;

[0027] Get the current time;

[0028] Set the judgment time;

[0029] Calculate the judgment time, judgment time = current time - judgment duration;

[0030] The determination time is taken as the start time and the current time is taken as the end time to form a collection period;

[0031] If the target time is within the collection period, the target time is identified as an abnormal target time;

[0032] If the target time is not within the collection period, the target time is considered as the normal target time;

[0033] Get all target times to form a target time set;

[0034] If there is an abnormal target time in the target time set, the analysis and judgment strategy is executed;

[0035] If there is no abnormal target time in the target time set, the target enterprise is judged to have a small risk of abnormal movement, and no abnormal risk warning is issued.

[0036] As a method of using an enterprise intelligent assessment and abnormal risk early warning system according to the present invention, wherein: the acquisition of a target database is specifically:

[0037] Acquire all enterprises in the overall target area to form an enterprise set;

[0038] Get the first data of each enterprise;

[0039] Obtaining the second data of each enterprise;

[0040] Obtain third-party data for each enterprise;

[0041] Obtain time data for each enterprise;

[0042] Obtain structural data for each enterprise;

[0043] Integrate the first data, the second data, the third data, the time data and the structure data to form an enterprise data set for each enterprise;

[0044] According to each element in the enterprise set and the enterprise data set corresponding to each element, a regional enterprise set is formed by integration.

[0045] As a method of using the enterprise intelligent assessment and abnormal risk early warning system described in the present invention, the analysis and judgment strategy is specifically:

[0046] Obtaining second determination data of the target enterprise;

[0047] Obtain the determination enterprise data of the target enterprise;

[0048] Extract the structural data corresponding to each determined enterprise data and define it as the target structure;

[0049] If the target structure = the second determination data, the target structure is identified as an abnormal target structure;

[0050] If the target structure ≠ the second determination data, the target structure is identified as a normal target structure;

[0051] Obtain all target structures to form a target structure set;

[0052] If there is an abnormal target structure in the target structure set, the misjudgment analysis strategy is executed;

[0053] If there is no abnormal target structure in the target structure set, the target enterprise is judged to have a small risk of abnormal change, and no abnormal risk warning is issued.

[0054] As a method of using the enterprise intelligent assessment and abnormal risk early warning system described in the present invention, the misjudgment analysis strategy is specifically:

[0055] Obtain the attribution data of the target enterprise and set it as the target attribution data;

[0056] Obtain all enterprises in the target area and define them as analysis enterprises;

[0057] Obtain the attribution data of each analyzed enterprise and define it as the analyzed attribution data;

[0058] Extract the analysis enterprise corresponding to the analysis attribution data that is consistent with the target attribution data and set it as the target analysis enterprise;

[0059] Obtain the change status of each target analysis enterprise respectively, wherein the change status includes whether the enterprise has relocated or not;

[0060] Extract all the target analysis enterprises with changes that have been relocated and define them as relocated enterprises;

[0061] Get the number of all relocated enterprises and define it as the number of relocated enterprises;

[0062] Obtain the number of all target analysis enterprises and set it as the number of enterprises;

[0063] If the number of relocations divided by the number of enterprises is less than 60%, the target enterprise is judged to have a low risk of change, and no change risk warning is issued;

[0064] If the number of relocations ÷ the number of enterprises ≥ 60%, the relocation data will be obtained for each relocated enterprise;

[0065] The number of relocated enterprises with low relocation risk is extracted as the judgment number;

[0066] If the determination number ÷ the relocation number is less than 60%, the target enterprise is judged to have a low risk of change, and no change risk warning is issued;

[0067] If the number of determinations ÷ the number of relocations ≥ 60%, then the risk of enterprise relocation in the target area is high;

[0068] It is then determined that the target enterprise has a high risk of abnormal changes, and an abnormal change risk warning is issued.

[0069] As a method of using the enterprise intelligent assessment and change risk early warning system described in the present invention, wherein: the change situation of each target analysis enterprise is obtained separately, specifically:

[0070] Obtain the first risk data of the target analysis enterprise;

[0071] If the target analysis enterprise does not have the first risk data, the change of the enterprise is deemed to have been relocated;

[0072] If the target analysis enterprise has first risk data, obtaining second risk data of the target analysis enterprise;

[0073] Obtain third-party risk data of the target analysis enterprise;

[0074] If the third risk data of the target enterprise = the second risk data, the change of the enterprise is deemed as not relocating;

[0075] If the third risk data of the target analysis enterprise ≠ the second risk data, the change of the enterprise is deemed to have been relocated.

[0076] As a method of using the enterprise intelligent assessment and abnormal risk early warning system described in the present invention, wherein: the relocation data of each relocated enterprise is obtained separately, specifically:

[0077] Obtain the deregistration data of relocated enterprises;

[0078] If there is cancellation data for the relocated enterprise, it is judged that the relocated enterprise has a high risk of relocation;

[0079] If there is no cancellation data for the relocated enterprise, it is judged that the relocation risk of the relocated enterprise is low.

[0080] The present invention has the following beneficial effects:

[0081] 1. The enterprise intelligent assessment and abnormal change risk early warning system and method determines whether the target enterprise has relocated by obtaining the initial registered address and current registered address of the target enterprise. If the registered address of the target enterprise has not changed, the initial business scope and current business scope of the target enterprise are obtained to determine whether the business scope of the target enterprise in the target area has changed, thereby determining whether the target enterprise currently has abnormal changes such as relocation, so as to promptly respond to the adverse effects caused by abnormal changes such as relocation of the enterprise and reduce the economic losses caused by abnormal changes such as relocation of the enterprise.

[0082] 2. The enterprise intelligent assessment and change risk warning system and method obtains all the enterprises under the name of the person in charge of the target enterprise and the registration time of these enterprises to determine whether the person in charge of the target enterprise has registered a new company in a different place recently. If there is no new company registered in a different place, it means that the target enterprise has a low change risk. If there is a new company registered in a different place, it means that the target enterprise may have a change risk and it is necessary to further determine whether there is a misjudgment, so as to promptly respond to the adverse effects caused by changes such as enterprise relocation and reduce the economic losses caused by changes such as enterprise relocation.

[0083] 3. The enterprise intelligent assessment and change risk warning system and method obtains the industry to which the target enterprise belongs and the data of all enterprises in the same industry in the same region as the target enterprise, including enterprises that have been registered in the target area but have moved out. By obtaining the operating modes of enterprises of the same type, it is determined whether the enterprise of this type will move out or open a subsidiary in another place when there is a change, and then the change risk of the target enterprise is determined, so as to promptly respond to the adverse effects caused by changes such as enterprise relocation and reduce the economic losses caused by changes such as enterprise relocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 This is a block diagram of the enterprise intelligent assessment and abnormal risk early warning system of the present invention;

[0085] Figure 2 The present invention is a method flow chart of using the enterprise intelligent assessment and abnormal risk early warning system. DETAILED DESCRIPTION

[0086] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0087] Embodiment 1, an enterprise intelligent assessment and abnormal risk early warning system, see Figure 1-Figure 2 ,include:

[0088] Collection module: obtains target information to determine whether the target enterprise has any changes such as relocation;

[0089] Analysis module: Based on the target information and enterprise analysis strategies, analytical data is generated to determine whether the target enterprise has any changes in its business within the target area, and further determine whether the target enterprise has any changes such as relocation;

[0090] Judgment module: Based on the analysis data, the judgment data is formed through the misjudgment analysis strategy to judge the operation mode of enterprises in the target area that are in the same industry as the target enterprise, so as to determine the risk of abnormal movement of the target enterprise;

[0091] Evaluation module: Based on the judgment data, the target enterprise's change risk is evaluated so as to take timely remedial measures and reduce the adverse effects caused by the enterprise change.

[0092] Through the above modules, based on the data adjustment of the enterprise, it is judged whether the enterprise has any abnormal changes such as relocation. Based on the data adjustment of the person in charge of the enterprise, it is judged whether the enterprise has the risk of abnormal changes such as relocation. Based on the relocation of other enterprises in the same industry in the same region, the risk of abnormal changes of the target enterprise is judged, so as to promptly respond to the adverse effects caused by abnormal changes such as relocation of the enterprise and reduce the economic losses caused by abnormal changes such as relocation of the enterprise.

[0093] Embodiment 2: This embodiment further discloses a method for using an enterprise intelligent assessment and risk early warning system for abnormal changes, wherein the target information is obtained by:

[0094] Acquire first target data of the target enterprise, where the first target data is the initial registration address of the target enterprise;

[0095] Acquire first determination data of the target enterprise, where the first determination data is the current registered address of the target enterprise;

[0096] If the first determination data = the first target data, the enterprise analysis strategy is executed, that is, the target enterprise has not changed its registered address, and it is necessary to further determine whether the enterprise has moved out;

[0097] If the first determination data ≠ the first target data, it is determined that the target enterprise has a small change risk and no change risk warning is issued, that is, the target enterprise has changed its registered address.

[0098] This embodiment also provides that the enterprise analysis strategy is specifically:

[0099] Acquire second target data of the target enterprise, where the second target data is the initial business scope of the target enterprise;

[0100] Acquire second determination data of the target enterprise, where the second target data is the current business scope of the target enterprise;

[0101] If the second judgment data = the second target data, the target enterprise is judged to have a low risk of change, and no change risk warning is issued, which means that the target enterprise has not changed its registered address, nor has it changed its business scope in the current city, indicating that the target enterprise is less likely to relocate.

[0102] If the second determination data ≠ the second target data, the change determination strategy is executed.

[0103] This embodiment also provides that the change determination strategy is specifically:

[0104] Obtaining determination data of the target enterprise, the determination data including first determination data and second determination data, the first determination data being the person in charge of the target enterprise, such as the legal person, directors, shareholders and other leadership, and the second determination data being the company structure of the target enterprise;

[0105] Get the target database;

[0106] Extracting all enterprise data sets corresponding to the third data identical to the first determination data in the target database as determination enterprise data;

[0107] Extract the time data corresponding to each determined enterprise data and set it as the target time;

[0108] Get the current time;

[0109] Setting the judgment period, which is half a year;

[0110] Calculate the judgment time, judgment time = current time - judgment duration;

[0111] The determination time is taken as the start time and the current time is taken as the end time to form a collection period;

[0112] If the target time is within the collection period, the target time is identified as an abnormal target time;

[0113] If the target time is not within the collection period, the target time is considered as the normal target time;

[0114] Get all target times to form a target time set;

[0115] If there is an abnormal target time in the target time set, the analysis and judgment strategy is executed, that is, the person in charge of the target enterprise has recently registered a new company in another city, and it is necessary to further determine whether the enterprise has moved out;

[0116] If there is no abnormal target time in the target time set, it is determined that the target enterprise has a small risk of change and no risk warning is issued. That is, the person in charge of the target enterprise has not registered a new company in other cities recently, indicating that the target enterprise is currently less likely to relocate.

[0117] Wherein, the acquisition of the target database is specifically:

[0118] Acquire all enterprises in the target overall area to form an enterprise set, where the target overall area is nationwide;

[0119] Obtaining first data of each enterprise, where the first data is the registered address of the enterprise;

[0120] Acquire second data of each enterprise, where the second data is the business scope of the enterprise;

[0121] Obtaining third data of each enterprise, wherein the third data is a person in charge of the enterprise;

[0122] Obtaining time data of each enterprise, where the time data is the registration time of the enterprise;

[0123] Acquire structural data of each enterprise, wherein the structural data is the personnel structure of the enterprise;

[0124] Integrate the first data, the second data, the third data, the time data and the structure data to form an enterprise data set for each enterprise;

[0125] According to each element in the enterprise set and the enterprise data set corresponding to each element, a regional enterprise set is formed by integration.

[0126] This embodiment also provides that the analysis and determination strategy is specifically:

[0127] Obtaining second determination data of the target enterprise;

[0128] Obtain the determination enterprise data of the target enterprise;

[0129] Extract the structural data corresponding to each determined enterprise data and define it as the target structure;

[0130] If the target structure = the second determination data, the target structure is identified as an abnormal target structure;

[0131] If the target structure ≠ the second determination data, the target structure is identified as a normal target structure;

[0132] Obtain all target structures to form a target structure set;

[0133] If there is an abnormal target structure in the target structure set, the misjudgment analysis strategy is executed;

[0134] If there is no abnormal target structure in the target structure set, it is determined that the target enterprise has a small risk of change and no risk warning is issued. That is, the structure of the new company recently registered by the person in charge of the target enterprise in other cities is different from that of the target enterprise, indicating that the target enterprise is currently less likely to relocate.

[0135] Embodiment 3: This embodiment is an improvement made on the basis of Embodiment 2. The method using the enterprise intelligent assessment and abnormal risk early warning system, the misjudgment analysis strategy, is specifically:

[0136] Obtaining attribution data of a target enterprise, which is defined as target attribution data, wherein the attribution data is the industry type to which the enterprise belongs;

[0137] Obtain all enterprises in the target area and define them as analysis enterprises, wherein the analysis enterprises are all enterprises registered in the target area, including existing operating enterprises and enterprises that have relocated, and the target area is the city where the target enterprise is currently located;

[0138] Obtain the attribution data of each analyzed enterprise and define it as the analyzed attribution data;

[0139] Extract the analysis enterprise corresponding to the analysis attribution data that is consistent with the target attribution data and set it as the target analysis enterprise;

[0140] Obtain the change status of each target analysis enterprise respectively, wherein the change status includes whether the enterprise has relocated or not;

[0141] Extract all the target analysis enterprises with changes that have been relocated and define them as relocated enterprises;

[0142] Get the number of all relocated enterprises and define it as the number of relocated enterprises;

[0143] Obtain the number of all target analysis enterprises and set it as the number of enterprises;

[0144] If the number of relocations ÷ the number of enterprises is less than 60%, the target enterprise is judged to have a low risk of relocation and no risk warning is issued, which means that most enterprises in the target area can continue to operate in the area, indicating that the target area has good preferential policies for enterprises, thus being able to retain enterprises. Therefore, it is judged that the target enterprise is more likely to open subsidiaries in other cities, and its current probability of relocation in the target area is low;

[0145] If the number of relocations ÷ the number of enterprises ≥ 60%, the relocation data will be obtained for each relocated enterprise;

[0146] The number of relocated enterprises with low relocation risk is extracted as the judgment number;

[0147] If the number of determinations ÷ the number of relocations is less than 60%, the target enterprise is judged to have a low risk of relocation and no risk warning will be issued, which means that most enterprises in the target area can continue to operate in the area, indicating that the target area has good preferential policies for enterprises, thus being able to retain enterprises. Therefore, it is judged that the target enterprise is more likely to open subsidiaries in other cities, and its current probability of relocation in the target area is low;

[0148] If the number of determinations ÷ the number of relocations ≥ 60%, then the risk of enterprise relocation in the target area is high;

[0149] It will determine that the target enterprise has a high risk of relocation and issue a risk warning, that is, a timely warning will be given to the department responsible for attracting investment so that they can take timely response measures to prevent the relocation of the enterprise from having a negative impact on the economy of the region.

[0150] The obtaining of the change status of each target analysis enterprise is specifically as follows:

[0151] Acquire first risk data of a target enterprise for analysis, where the first risk data is a current registered address of the enterprise in a target area;

[0152] If the target analysis enterprise does not have the first risk data, the change of the enterprise is deemed to have been relocated;

[0153] If the target enterprise for analysis has first risk data, then obtain second risk data of the target enterprise for analysis, where the second risk data is the business scope of the enterprise when it is first registered in the target area;

[0154] Acquire third risk data of the target analysis enterprise, where the third risk data is the current business scope of the enterprise in the target area;

[0155] If the third risk data of the target enterprise = the second risk data, the change of the enterprise is deemed as not relocating;

[0156] If the third risk data of the target analysis enterprise ≠ the second risk data, the change of the enterprise is deemed to have been relocated.

[0157] The step of obtaining the relocation data for each relocated enterprise is as follows:

[0158] Obtaining the deregistration data of the relocated enterprise, wherein the deregistration data is the deregistration time of the enterprise in the target area;

[0159] If there is cancellation data for the relocated enterprise, it is judged that the relocated enterprise has a high risk of relocation;

[0160] If there is no cancellation data for the relocated enterprise, it is judged that the relocation risk of the relocated enterprise is low.

[0161] In this embodiment, based on the data adjustment of the enterprise, it is judged whether the enterprise has any abnormal changes such as relocation. Based on the data adjustment of the person in charge of the enterprise, it is judged whether the enterprise has the risk of abnormal changes such as relocation. Based on the relocation of other enterprises in the same industry in the same region, the risk of abnormal changes of the target enterprise is judged, so as to promptly respond to the adverse effects caused by abnormal changes such as relocation of the enterprise and reduce the economic losses caused by abnormal changes such as relocation of the enterprise.

[0162] The embodiments of the present disclosure also provide a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the enterprise intelligent assessment and abnormal risk warning system and method in the aforementioned method embodiment.

[0163] It should be noted that more specific examples of computer-readable storage media may include portable computer disks, hard disks, erasable programmable read-only memories (EPROMs or flash memories), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present disclosure, computer-readable storage media may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device, and the computer-readable medium may be contained in the electronic device; or it may exist independently without being assembled into the electronic device.

[0164] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device can implement the solution provided by the method embodiment.

[0165] Computer program code for performing operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, and may be executed entirely on a user's computer, partially on a user's computer, as a stand-alone software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0166] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0167] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An enterprise intelligent assessment and risk early warning system, characterized by: include: Collection module: obtains target information to determine whether the target enterprise has any changes such as relocation; Analysis module: Based on the target information and enterprise analysis strategies, analytical data is generated to determine whether the target enterprise has any changes in its business within the target area, and further determine whether the target enterprise has any changes such as relocation; Judgment module: Based on the analysis data, the judgment data is formed through the misjudgment analysis strategy to judge the operation mode of enterprises in the target area that are in the same industry as the target enterprise, so as to determine the risk of abnormal movement of the target enterprise; Evaluation module: Based on the judgment data, the target enterprise's change risk is evaluated so as to take timely remedial measures and reduce the adverse effects caused by the enterprise change.

2. A method for using the enterprise intelligent assessment and abnormal risk early warning system according to claim 1, characterized in that: The obtaining of target information is specifically as follows: Obtain the first target data of the target enterprise; Obtaining first determination data of the target enterprise; If the first determination data = the first target data, then the enterprise analysis strategy is executed; If the first judgment data ≠ the first target data, it is determined that the target enterprise has a small risk of abnormal change, and no abnormal risk warning is issued.

3. The method of the enterprise intelligent assessment and abnormal risk early warning system according to claim 2 is characterized by: The enterprise analysis strategy is specifically: Acquire the second target data of the target enterprise; Obtaining second determination data of the target enterprise; If the second determination data = the second target data, the target enterprise is determined to have a low risk of change, and no change risk warning is issued; If the second determination data ≠ the second target data, the change determination strategy is executed.

4. The method of the enterprise intelligent assessment and abnormal risk early warning system according to claim 3 is characterized by: The change determination strategy is specifically as follows: Acquire determination data of a target enterprise, wherein the determination data includes first determination data and second determination data; Get the target database; Extracting all enterprise data sets corresponding to the third data identical to the first determination data in the target database as determination enterprise data; Extract the time data corresponding to each determined enterprise data and set it as the target time; Get the current time; Set the judgment time; Calculate the judgment time, judgment time = current time - judgment duration; The determination time is taken as the start time and the current time is taken as the end time to form a collection period; If the target time is within the collection period, the target time is identified as an abnormal target time; If the target time is not within the collection period, the target time is considered as the normal target time; Get all target times to form a target time set; If there is an abnormal target time in the target time set, the analysis and judgment strategy is executed; If there is no abnormal target time in the target time set, the target enterprise is judged to have a small risk of abnormal movement, and no abnormal risk warning is issued.

5. The method of the enterprise intelligent assessment and abnormal risk early warning system according to claim 4 is characterized by: The obtaining of the target database is specifically as follows: Acquire all enterprises in the overall target area to form an enterprise set; Get the first data of each enterprise; Obtaining the second data of each enterprise; Obtain third-party data for each enterprise; Obtain time data for each enterprise; Obtain structural data for each enterprise; Integrate the first data, the second data, the third data, the time data and the structure data to form an enterprise data set for each enterprise; According to each element in the enterprise set and the enterprise data set corresponding to each element, a regional enterprise set is formed by integration.

6. The method of the enterprise intelligent assessment and abnormal risk early warning system according to claim 4 is characterized by: The analysis and determination strategy is specifically as follows: Obtaining second determination data of the target enterprise; Obtain the determination enterprise data of the target enterprise; Extract the structural data corresponding to each determined enterprise data and define it as the target structure; If the target structure = the second determination data, the target structure is identified as an abnormal target structure; If the target structure ≠ the second determination data, the target structure is identified as a normal target structure; Obtain all target structures to form a target structure set; If there is an abnormal target structure in the target structure set, the misjudgment analysis strategy is executed; If there is no abnormal target structure in the target structure set, the target enterprise is judged to have a small risk of abnormal change, and no abnormal risk warning is issued.

7. The method of the enterprise intelligent assessment and abnormal risk early warning system according to claim 6 is characterized by: The misjudgment analysis strategy is specifically as follows: Obtain the attribution data of the target enterprise and set it as the target attribution data; Obtain all enterprises in the target area and define them as analysis enterprises; Obtain the attribution data of each analyzed enterprise and define it as the analyzed attribution data; Extract the analysis enterprise corresponding to the analysis attribution data that is consistent with the target attribution data and set it as the target analysis enterprise; Obtain the change status of each target analysis enterprise respectively, wherein the change status includes whether the enterprise has relocated or not; Extract all the target analysis enterprises with changes that have been relocated and define them as relocated enterprises; Get the number of all relocated enterprises and define it as the number of relocated enterprises; Obtain the number of all target analysis enterprises and set it as the number of enterprises; If the number of relocations divided by the number of enterprises is less than 60%, the target enterprise is judged to have a low risk of change, and no change risk warning is issued; If the number of relocations ÷ the number of enterprises ≥ 60%, the relocation data will be obtained for each relocated enterprise; The number of relocated enterprises with low relocation risk is extracted as the judgment number; If the determination number ÷ the relocation number is less than 60%, the target enterprise is judged to have a low risk of change, and no change risk warning is issued; If the number of determinations ÷ the number of relocations ≥ 60%, then the risk of enterprise relocation in the target area is high; It is then determined that the target enterprise has a high risk of abnormal changes, and an abnormal change risk warning is issued.

8. The method of the enterprise intelligent assessment and abnormal risk early warning system according to claim 7 is characterized by: The above-mentioned obtaining the change situation of each target analysis enterprise separately is specifically as follows: Obtain the first risk data of the target analysis enterprise; If the target analysis enterprise does not have the first risk data, the change of the enterprise is deemed to have been relocated; If the target analysis enterprise has first risk data, obtaining second risk data of the target analysis enterprise; Obtain the third-party risk data of the target analysis enterprise; If the third risk data of the target enterprise = the second risk data, the change of the enterprise is deemed as not relocating; If the third risk data of the target analysis enterprise ≠ the second risk data, the change of the enterprise is deemed to have been relocated.

9. The method of the enterprise intelligent assessment and abnormal risk early warning system according to claim 7 is characterized by: The relocation data of each relocated enterprise is obtained separately, specifically: Obtain the deregistration data of relocated enterprises; If there is cancellation data for the relocated enterprise, it is judged that the relocated enterprise has a high risk of relocation; If there is no cancellation data for the relocated enterprise, it is judged that the relocation risk of the relocated enterprise is low.

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