A method, device and medium for monitoring corporate debt

Abstract

The present application discloses a method, device and medium for monitoring enterprise debt, the method comprising: obtaining the current debt information of the enterprise, and determining the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs; conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise; collecting the public opinion information corresponding to the enterprise, and performing text recognition on the public opinion information to extract the public opinion impact characteristics corresponding to the enterprise from the public opinion information; compensating the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level; and executing a corresponding risk strategy on the enterprise according to the compensated debt risk level.

Description

Technical Field

[0001] The present application relates to the technical field of debt monitoring, and in particular to a method, device and medium for monitoring corporate debt. Background Art

[0002] With the continuous development of Internet finance, loan business has been put forward higher and higher requirements and challenges. Post-loan risk management is an important part of credit risk management and an important means to prevent and resolve debt risks. The current risk management method is to evaluate the business conditions of the enterprise and judge whether it can repay the loan on time. However, the debt risk of the enterprise will also be affected by external factors. It is impossible to conduct a more accurate risk assessment of the enterprise only by referring to the business conditions. Summary of the invention

[0003] In order to solve the above problems, this application proposes a corporate debt monitoring method, including:

[0004] Acquire the current debt information of the enterprise, and determine the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs;

[0005] Conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise;

[0006] Collecting public opinion information corresponding to the enterprise, and performing text recognition on the public opinion information to extract public opinion influence features corresponding to the enterprise from the public opinion information;

[0007] Compensating the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level;

[0008] According to the compensated debt risk level, a corresponding risk strategy is implemented for the enterprise.

[0009] In one implementation of the present application, text recognition is performed on the public opinion information to extract the public opinion influence features corresponding to the enterprise from the public opinion information, specifically including:

[0010] Collecting the required public opinion information data set, performing word segmentation processing on the public opinion information data set, and obtaining a plurality of keywords after word segmentation; wherein the public opinion information data set is composed of a plurality of negative public opinion information;

[0011] According to the attributes of each keyword and the mapping relationship set in the preset corpus, determine the effect type corresponding to each keyword on the preset risk assessment benchmark; wherein the effect type includes positive effect and negative effect;

[0012] Determine the frequency corresponding to the effect type of each keyword on the risk assessment benchmark, and filter out keywords whose frequency corresponding to the negative effect is greater than a preset frequency from the keyword set in the risk assessment benchmark where the keyword is located, to obtain a target keyword set corresponding to the risk assessment benchmark;

[0013] Text recognition is performed on the public opinion information according to the target keyword set to extract the public opinion influence features corresponding to the enterprise from the public opinion information.

[0014] In one implementation of the present application, text recognition is performed on the public opinion information according to the target keyword set to extract the public opinion influence features corresponding to the enterprise from the public opinion information, specifically including:

[0015] Segmenting the public opinion information, and deleting the specified words obtained after the segmentation, so as to obtain the corresponding segmentation result;

[0016] Matching the word segmentation results with the target keyword set corresponding to each risk assessment benchmark, and determining the keyword matching rate between each risk assessment benchmark;

[0017] The keyword matching rates corresponding to each of the risk assessment benchmarks are compared, and from each of the risk assessment benchmarks, a designated risk assessment benchmark whose corresponding keyword matching rate is greater than a preset matching rate, and a target keyword in the word segmentation result that matches the designated risk assessment benchmark are selected, and the target keyword is used as the public opinion influence feature corresponding to the enterprise.

[0018] In one implementation of the present application, the debt risk level is compensated according to the public opinion impact characteristics to obtain the compensated debt risk level, specifically including:

[0019] Determine the importance of the specified risk assessment benchmark corresponding to the public opinion impact feature to the current debt information;

[0020] The debt risk level is compensated according to the importance, and the product of the importance and the debt risk level is used as the compensated debt risk level.

[0021] In one implementation of the present application, a debt risk assessment is performed on the enterprise according to the risk impact level to determine the debt risk level corresponding to the enterprise, specifically including:

[0022] Determine the impact range corresponding to the risk impact level; wherein the impact range includes at least three ranges, namely, a first range higher than a first preset risk impact level, a second range lower than the first preset risk impact level and higher than a second preset risk impact level, and a third range lower than the second preset risk impact level;

[0023] Selecting the specified current debt information whose risk impact level belongs to the first range, and constructing an enterprise model corresponding to the enterprise according to the specified current debt information;

[0024] Using the current debt information as a risk assessment parameter to generate a risk assessment model, wherein the current debt information corresponding to the first range has a higher weight than the current debt information corresponding to the second range and the third range;

[0025] The risk assessment model is integrated with the enterprise model to perform risk assessment on the enterprise through the integrated enterprise model to obtain the debt risk level corresponding to the enterprise.

[0026] In one implementation of the present application, determining the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs specifically includes:

[0027] Determine the purpose of the debt to which the current debt information belongs, and judge the enterprise business type corresponding to the purpose of the debt; wherein the enterprise business type is main business, secondary business and ancillary business;

[0028] According to the business type of the enterprise, determine the risk impact level between the current debt information and the enterprise; wherein the risk impact level corresponding to the main business belongs to the first range, the risk impact level corresponding to the secondary business belongs to the second range, and the risk impact level corresponding to the subsidiary business belongs to the third range.

[0029] In one implementation of the present application, a corresponding risk strategy is implemented for the enterprise according to the compensated debt risk level, specifically including:

[0030] When the debt risk level is greater than the first preset level, determining whether the enterprise has any substantial default behavior, and if so, executing a freezing strategy on the enterprise;

[0031] When the debt risk level is not greater than the first preset level and greater than the second preset level, determine whether the enterprise has committed a substantial default, and if so, implement a collection strategy for the enterprise; wherein the first preset level is greater than the second preset level.

[0032] In one implementation of the present application, executing a collection strategy on the enterprise specifically includes:

[0033] Determine the overdue duration corresponding to the enterprise and the duration interval corresponding to the overdue duration according to the current debt information;

[0034] According to the time interval, the collection intensity corresponding to the current debt information is determined, and according to the collection intensity, a collection frequency matching the collection intensity is adopted to collect debts from the enterprise.

[0035] The embodiment of the present application provides an enterprise debt monitoring device, including:

[0036] at least one processor; and,

[0037] a memory communicatively connected to the at least one processor; wherein,

[0038] The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:

[0039] Acquire the current debt information of the enterprise, and determine the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs;

[0040] Conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise;

[0041] Collecting public opinion information corresponding to the enterprise, and performing text recognition on the public opinion information to extract public opinion influence features corresponding to the enterprise from the public opinion information;

[0042] Compensating the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level;

[0043] According to the compensated debt risk level, a corresponding risk strategy is implemented for the enterprise.

[0044] The embodiment of the present application provides a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured as follows:

[0045] Acquire the current debt information of the enterprise, and determine the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs;

[0046] Conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise;

[0047] Collecting public opinion information corresponding to the enterprise, and performing text recognition on the public opinion information to extract public opinion influence features corresponding to the enterprise from the public opinion information;

[0048] Compensating the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level;

[0049] According to the compensated debt risk level, a corresponding risk strategy is implemented for the enterprise.

[0050] The enterprise debt monitoring method proposed in this application can bring the following beneficial effects:

[0051] According to the debt purpose corresponding to the current debt information, the corresponding repayment risk of the enterprise is evaluated, taking into account the impact of different business types on the progress of the enterprise's debt repayment. Through public opinion information, the company's current potential debt repayment risk can be explored, and the company's debt risk can be evaluated from multiple angles, which is more comprehensive and improves the accuracy of risk assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0053] Figure 1 A flowchart of a method for monitoring corporate debts provided in an embodiment of the present application;

[0054] Figure 2 A schematic diagram of the structure of an enterprise debt monitoring device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0056] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0057] like Figure 1 As shown, an enterprise debt monitoring method provided by an embodiment of the present application includes:

[0058] S101: Obtain the current debt information of the enterprise, and determine the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs.

[0059] Whether it is a private enterprise or a state-owned enterprise, it will apply for a loan from the bank to support the expansion and operation of its business during the operation process. The business situation of the enterprise will directly affect whether the debt can be repaid on time. The business situation will vary according to the different purposes of the debt. If the borrowed debt is used for the main business of the enterprise, then the enterprise will use most of the funds to develop the main business to support the normal operation of the enterprise. For the relatively marginal secondary business and subsidiary business of the enterprise, the enterprise will invest funds to develop this type of business while ensuring the normal operation of the main business. Therefore, after the server obtains the current debt information of the enterprise, if it wants to manage its risks, it must first clarify the purpose of the debt corresponding to the current debt information, and then determine the risk impact level between the current debt information and the enterprise based on the purpose of the debt.

[0060] Specifically, the current debt information of the enterprise is obtained, the purpose of the debt to which the current debt information belongs is determined, and the business type of the enterprise corresponding to the purpose of the debt is determined; wherein the business types of the enterprise are the main business, the secondary business and the subsidiary business. According to the business type of the enterprise, the risk impact level between the current debt information and the enterprise is determined. After clarifying the risk level corresponding to the current debt information, the impact range corresponding to the risk impact level can be determined; wherein the impact range includes at least three ranges, namely, a first range higher than the first preset risk impact level, a second range lower than the first preset risk impact level and higher than the second preset risk impact level, and a third range lower than the second preset risk impact level. The risk impact level corresponding to the main business belongs to the first range, the risk impact level corresponding to the secondary business belongs to the second range, and the risk impact level corresponding to the subsidiary business belongs to the third range.

[0061] S102: Conduct debt risk assessment on the enterprise based on the risk impact level to determine the corresponding debt risk level of the enterprise.

[0062] According to the risk impact level, the debt risk of the enterprise can be assessed to determine the corresponding debt risk level of the enterprise. First, the specified current debt information whose risk impact level belongs to the first range is selected, and the enterprise model corresponding to the enterprise is constructed according to the specified current debt information. The specified debt information belonging to the first range is used to characterize the main business of the enterprise, and the enterprise model constructed according to the specified debt information can reflect the operating risk of the enterprise. It should be noted that the enterprise model can be a pre-built enterprise portrait, or it can be a digital model constructed according to the correlation between the current debt information. Then, the current debt information is used as a risk assessment parameter to generate a risk assessment model, in which the weight of the current debt information corresponding to the first range is higher than the current debt information corresponding to the second range and the third range. Finally, the risk assessment model is integrated with the enterprise model to conduct risk assessment on the enterprise through the integrated enterprise model to obtain the corresponding debt risk level of the enterprise.

[0063] S103: Collect public opinion information corresponding to the enterprise, perform text recognition on the public opinion information, and extract the public opinion impact features corresponding to the enterprise from the public opinion information.

[0064] The above-mentioned debt risk level is obtained based on the company's own portrait and debt risk assessment. However, external public opinion information will also indirectly affect the company's operating conditions, and thus have a certain impact on the repayment of debts. Therefore, in addition to the company's own risk factors, the embodiment of this application also refers to public opinion information to manage the company's risks in order to improve the accuracy of the risk assessment results.

[0065] The server needs to collect the public opinion information corresponding to the enterprise and perform text recognition on the public opinion information to extract the public opinion impact characteristics corresponding to the enterprise from the public opinion information, and then re-evaluate the debt risk level of the enterprise based on the public opinion impact characteristics.

[0066] The public opinion image feature is extracted through keyword comparison. Before extracting the public opinion impact feature, it is necessary to first collect the required public opinion information data set, perform word segmentation on the public opinion information data set, and obtain multiple keywords after word segmentation; among them, the public opinion information data set consists of multiple negative public opinion information. According to the attributes of each keyword and the mapping relationship set in the preset corpus, the effect type corresponding to each keyword on the preset risk assessment benchmark is determined. The risk assessment benchmark refers to external factors that can affect the debt risk of an enterprise, such as industry development, policy impact, media image, etc. The effect type includes positive effect and negative effect. The positive effect refers to the word that the keyword can affect the risk assessment benchmark. For example, if the risk assessment benchmark is the industry development, then the keyword "thunderstorm" can affect the above risk assessment benchmark, while the negative effect means that the keyword cannot affect the credit evaluation standard. For example, the keyword "case" has no impact on the industry development. According to the effect type, keywords can be screened out, that is, the frequency corresponding to the effect type of each keyword on the risk assessment benchmark is determined, and keywords with negative effects corresponding to frequencies greater than the preset frequency are screened out from the keyword set in the risk assessment benchmark where the keyword is located, and the target keyword set corresponding to the risk assessment benchmark is obtained. At this point, the target keyword set obtained contains all the words that can reflect external public opinion. By performing text recognition on public opinion information based on the target keyword set, the public opinion impact characteristics corresponding to the enterprise can be extracted from the public opinion information.

[0067] Specifically, the public opinion information is segmented, and the designated words obtained after the segmentation are deleted to obtain the corresponding segmentation results. The segmentation results are matched with the target keyword set corresponding to each risk assessment benchmark, and the keyword matching rate between each risk assessment benchmark is determined. After obtaining the keyword matching rate corresponding to each risk assessment benchmark, the keyword matching rate corresponding to each risk assessment benchmark is compared, and from each risk assessment benchmark, a designated risk assessment benchmark with a corresponding keyword matching rate greater than a preset matching rate is selected, and then the target keyword matching the designated risk assessment benchmark in the segmentation result is determined, and the target keyword is used as the public opinion impact feature corresponding to the enterprise.

[0068] S104: Compensate the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level.

[0069] After obtaining the public opinion impact characteristics, the debt risk level can be compensated accordingly to obtain the compensated debt risk level. Different risk assessment benchmarks have different importance for debt information. For example, industry development can directly affect the business conditions of the enterprise, while the media image can only indirectly affect the business conditions of the enterprise compared to the industry development. Therefore, when compensating the debt risk level according to the public opinion impact characteristics, it is necessary to determine the importance of the specified risk assessment benchmark corresponding to the public opinion impact characteristics to the current debt information. Then, the debt risk level is compensated according to the importance, and the product between the importance and the debt risk level is used as the compensated debt risk level.

[0070] S105: Implement corresponding risk strategies for the enterprise based on the compensated debt risk level.

[0071] After obtaining the debt risk level after compensation, the server needs to implement the corresponding risk strategy for the enterprise accordingly. When the debt risk level is greater than the first preset level, it means that the current debt risk of the enterprise is relatively large. At this time, it is necessary to determine whether the enterprise has a substantial default. If not, it is necessary to increase the monitoring of the enterprise to ensure that it can repay on time. If there is a substantial default, due to the high risk of the enterprise, a freezing strategy can be implemented on the enterprise at this time until it completes the debt repayment and unfreezes according to the debt repayment progress. When the debt risk level is not greater than the first preset level and greater than the second preset level, it means that although the enterprise has certain risks at this time, the risk level is general. At this time, it is necessary to determine whether the enterprise has a substantial default. If there is a default, a collection strategy needs to be implemented on the enterprise to ensure that the debt is repaid on time. The first preset level is greater than the second preset level. When the debt risk level is less than the second preset level, it means that the enterprise risk level is low. At this time, you can wait for the enterprise to repay according to the pre-planned debt repayment progress. When the enterprise has a substantial default, a collection strategy also needs to be implemented on the enterprise.

[0072] When collecting debts from an enterprise, the server needs to determine the corresponding overdue duration of the enterprise and the time interval corresponding to the overdue duration based on the current debt information. Then, based on the time interval, determine the collection intensity corresponding to the current debt information, and collect debts from the enterprise at a collection frequency that matches the collection intensity. The longer the overdue duration of a debt, the greater the corresponding collection intensity, thereby ensuring that the enterprise's debts are repaid on time through a higher frequency of collection actions.

[0073] The above are embodiments of the method proposed in this application. Based on the same idea, some embodiments of this application also provide devices and non-volatile computer storage media corresponding to the above methods.

[0074] Figure 2 A schematic diagram of the structure of an enterprise debt monitoring device provided in an embodiment of the present application. Figure 2 As shown, including:

[0075] at least one processor; and,

[0076] at least one processor is communicatively connected to a memory; wherein,

[0077] The memory stores instructions executable by at least one processor, the instructions being executed by at least one processor to enable the at least one processor to:

[0078] Obtain the current debt information of the enterprise, and determine the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs;

[0079] Conduct debt risk assessment on enterprises according to risk impact level to determine the corresponding debt risk level of the enterprise;

[0080] Collect the public opinion information corresponding to the enterprise, perform text recognition on the public opinion information, and extract the public opinion impact characteristics corresponding to the enterprise from the public opinion information;

[0081] Compensate the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level;

[0082] According to the compensated debt risk level, corresponding risk strategies are implemented for the enterprise.

[0083] The embodiment of the present application provides a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured as follows:

[0084] Obtain the current debt information of the enterprise, and determine the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs;

[0085] Conduct debt risk assessment on enterprises according to risk impact level to determine the corresponding debt risk level of the enterprise;

[0086] Collect the public opinion information corresponding to the enterprise, perform text recognition on the public opinion information, and extract the public opinion impact characteristics corresponding to the enterprise from the public opinion information;

[0087] Compensate the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level;

[0088] According to the compensated debt risk level, corresponding risk strategies are implemented for the enterprise.

[0089] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0090] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0091] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0092] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0093] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0094] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0095] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0096] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0097] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0098] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity 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, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0099] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for monitoring corporate debt, characterized in that: The method comprises: Acquire the current debt information of the enterprise, and determine the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs; Conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise; Collecting public opinion information corresponding to the enterprise, and performing text recognition on the public opinion information to extract public opinion influence features corresponding to the enterprise from the public opinion information; Compensating the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level; Execute corresponding risk strategies for the enterprise according to the debt risk level after compensation; Performing text recognition on the public opinion information to extract the public opinion impact features corresponding to the enterprise from the public opinion information specifically includes: Collecting the required public opinion information data set, performing word segmentation processing on the public opinion information data set, and obtaining a plurality of keywords after word segmentation; wherein the public opinion information data set is composed of a plurality of negative public opinion information; According to the attributes of each keyword and the mapping relationship set in the preset corpus, determine the effect type corresponding to each keyword on the preset risk assessment benchmark; wherein the effect type includes positive effect and negative effect; Determine the frequency corresponding to the effect type of each keyword on the risk assessment benchmark, and filter out keywords whose frequency corresponding to the negative effect is greater than a preset frequency from the keyword set in the risk assessment benchmark where the keyword is located, to obtain a target keyword set corresponding to the risk assessment benchmark; Performing text recognition on the public opinion information according to the target keyword set to extract the public opinion influence features corresponding to the enterprise from the public opinion information; Conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise, specifically including: Determine the impact range corresponding to the risk impact level; wherein the impact range includes at least three ranges, namely, a first range higher than a first preset risk impact level, a second range lower than the first preset risk impact level and higher than a second preset risk impact level, and a third range lower than the second preset risk impact level; Selecting the specified current debt information whose risk impact level belongs to the first range, and constructing an enterprise model corresponding to the enterprise according to the specified current debt information; Using the current debt information as a risk assessment parameter to generate a risk assessment model, wherein the current debt information corresponding to the first range has a higher weight than the current debt information corresponding to the second range and the third range; The risk assessment model is integrated with the enterprise model to perform risk assessment on the enterprise through the integrated enterprise model to obtain the debt risk level corresponding to the enterprise; Determining the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs, specifically includes: Determine the purpose of the debt to which the current debt information belongs, and judge the enterprise business type corresponding to the purpose of the debt; wherein the enterprise business type is main business, secondary business and ancillary business; According to the business type of the enterprise, determine the risk impact level between the current debt information and the enterprise; wherein the risk impact level corresponding to the main business belongs to the first range, the risk impact level corresponding to the secondary business belongs to the second range, and the risk impact level corresponding to the subsidiary business belongs to the third range.

2. The enterprise debt monitoring method according to claim 1, characterized in that: Performing text recognition on the public opinion information according to the target keyword set to extract the public opinion influence features corresponding to the enterprise from the public opinion information specifically includes: Segmenting the public opinion information, and deleting the specified words obtained after the segmentation, so as to obtain the corresponding segmentation result; Matching the word segmentation results with the target keyword set corresponding to each risk assessment benchmark, and determining the keyword matching rate between each risk assessment benchmark; The keyword matching rates corresponding to each of the risk assessment benchmarks are compared, and from each of the risk assessment benchmarks, a designated risk assessment benchmark whose corresponding keyword matching rate is greater than a preset matching rate, and a target keyword in the word segmentation result that matches the designated risk assessment benchmark are selected, and the target keyword is used as the public opinion influence feature corresponding to the enterprise.

3. The enterprise debt monitoring method according to claim 2, characterized in that: The debt risk level is compensated according to the public opinion impact characteristics, and the debt risk level after compensation is obtained, specifically including: Determine the importance of the specified risk assessment benchmark corresponding to the public opinion impact feature to the current debt information; The debt risk level is compensated according to the importance, and the product of the importance and the debt risk level is used as the compensated debt risk level.

4. The enterprise debt monitoring method according to claim 1, characterized in that: According to the debt risk level after compensation, corresponding risk strategies are implemented for the enterprise, including: When the debt risk level is greater than the first preset level, determining whether the enterprise has any substantial default behavior, and if so, executing a freezing strategy on the enterprise; When the debt risk level is not greater than the first preset level and greater than the second preset level, determine whether the enterprise has committed a substantial default, and if so, implement a collection strategy for the enterprise; wherein the first preset level is greater than the second preset level.

5. The enterprise debt monitoring method according to claim 4, characterized in that: Execute collection strategies against the business, including: Determine the overdue duration corresponding to the enterprise and the duration interval corresponding to the overdue duration according to the current debt information; According to the time interval, the collection intensity corresponding to the current debt information is determined, and according to the collection intensity, a collection frequency that matches the collection intensity is adopted to collect debts from the enterprise.

6. An enterprise debt monitoring device, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to: Acquire the current debt information of the enterprise, and determine the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs; Conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise; Collecting public opinion information corresponding to the enterprise, and performing text recognition on the public opinion information to extract public opinion influence features corresponding to the enterprise from the public opinion information; Compensating the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level; Execute corresponding risk strategies for the enterprise according to the debt risk level after compensation; Performing text recognition on the public opinion information to extract the public opinion impact features corresponding to the enterprise from the public opinion information specifically includes: Collecting the required public opinion information data set, performing word segmentation processing on the public opinion information data set, and obtaining a plurality of keywords after word segmentation; wherein the public opinion information data set is composed of a plurality of negative public opinion information; According to the attributes of each keyword and the mapping relationship set in the preset corpus, determine the effect type corresponding to each keyword on the preset risk assessment benchmark; wherein the effect type includes positive effect and negative effect; Determine the frequency corresponding to the effect type of each keyword on the risk assessment benchmark, and filter out keywords whose frequency corresponding to the negative effect is greater than a preset frequency from the keyword set in the risk assessment benchmark where the keyword is located, to obtain a target keyword set corresponding to the risk assessment benchmark; Performing text recognition on the public opinion information according to the target keyword set to extract the public opinion influence features corresponding to the enterprise from the public opinion information; Conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise, specifically including: Determine the impact range corresponding to the risk impact level; wherein the impact range includes at least three ranges, namely, a first range higher than a first preset risk impact level, a second range lower than the first preset risk impact level and higher than a second preset risk impact level, and a third range lower than the second preset risk impact level; Selecting the specified current debt information whose risk impact level belongs to the first range, and constructing an enterprise model corresponding to the enterprise according to the specified current debt information; Using the current debt information as a risk assessment parameter to generate a risk assessment model, wherein the current debt information corresponding to the first range has a higher weight than the current debt information corresponding to the second range and the third range; The risk assessment model is integrated with the enterprise model to perform risk assessment on the enterprise through the integrated enterprise model to obtain the debt risk level corresponding to the enterprise; Determining the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs, specifically includes: Determine the purpose of the debt to which the current debt information belongs, and judge the enterprise business type corresponding to the purpose of the debt; wherein the enterprise business type is main business, secondary business and ancillary business; According to the business type of the enterprise, determine the risk impact level between the current debt information and the enterprise; wherein the risk impact level corresponding to the main business belongs to the first range, the risk impact level corresponding to the secondary business belongs to the second range, and the risk impact level corresponding to the subsidiary business belongs to the third range.

7. A non-volatile computer storage medium storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Acquire the current debt information of the enterprise, and determine the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs; Conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise; Collecting public opinion information corresponding to the enterprise, and performing text recognition on the public opinion information to extract public opinion influence features corresponding to the enterprise from the public opinion information; Compensating the debt risk level according to the public opinion impact characteristics to obtain the compensated debt risk level; Execute corresponding risk strategies for the enterprise according to the debt risk level after compensation; Performing text recognition on the public opinion information to extract the public opinion impact features corresponding to the enterprise from the public opinion information specifically includes: Collecting the required public opinion information data set, performing word segmentation processing on the public opinion information data set, and obtaining a plurality of keywords after word segmentation; wherein the public opinion information data set is composed of a plurality of negative public opinion information; According to the attributes of each keyword and the mapping relationship set in the preset corpus, determine the effect type corresponding to each keyword on the preset risk assessment benchmark; wherein the effect type includes positive effect and negative effect; Determine the frequency corresponding to the effect type of each keyword on the risk assessment benchmark, and filter out keywords whose frequency corresponding to the negative effect is greater than a preset frequency from the keyword set in the risk assessment benchmark where the keyword is located, to obtain a target keyword set corresponding to the risk assessment benchmark; Performing text recognition on the public opinion information according to the target keyword set to extract the public opinion influence features corresponding to the enterprise from the public opinion information; Conducting a debt risk assessment on the enterprise according to the risk impact level to determine the corresponding debt risk level of the enterprise, specifically including: Determine the impact range corresponding to the risk impact level; wherein the impact range includes at least three ranges, namely, a first range higher than a first preset risk impact level, a second range lower than the first preset risk impact level and higher than a second preset risk impact level, and a third range lower than the second preset risk impact level; Selecting the specified current debt information whose risk impact level belongs to the first range, and constructing an enterprise model corresponding to the enterprise according to the specified current debt information; Using the current debt information as a risk assessment parameter to generate a risk assessment model, wherein the current debt information corresponding to the first range has a higher weight than the current debt information corresponding to the second range and the third range; The risk assessment model is integrated with the enterprise model to perform risk assessment on the enterprise through the integrated enterprise model to obtain the debt risk level corresponding to the enterprise; Determining the risk impact level between the current debt information and the enterprise according to the debt purpose to which the current debt information belongs, specifically includes: Determine the purpose of the debt to which the current debt information belongs, and judge the enterprise business type corresponding to the purpose of the debt; wherein the enterprise business type is main business, secondary business and ancillary business; According to the business type of the enterprise, determine the risk impact level between the current debt information and the enterprise; wherein the risk impact level corresponding to the main business belongs to the first range, the risk impact level corresponding to the secondary business belongs to the second range, and the risk impact level corresponding to the subsidiary business belongs to the third range.

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