Enterprise operation condition evaluation method, device, equipment, medium and program product

Abstract

The embodiment of the invention discloses an enterprise operation condition evaluation method and device, equipment, a medium and a program product, and relates to the field of financial science and technology, and the method comprises the steps: obtaining the basic enterprise information of a debt enterprise and a debt tracking clue in a clue model when it is detected that the debt enterprise meets a default condition; determining a tracking keyword corresponding to each debt tracking clue according to the basic enterprise information of the debt enterprise; inputting the tracking keyword corresponding to each debt tracking clue into a corresponding clue query website for query to obtain a clue tracking result corresponding to each debt tracking clue; and inputting the target clue tracking result meeting the matched debt recovery condition and a target debt tracking clue corresponding to the target clue tracking result into a pre-trained large model for processing to obtain an operation condition evaluation result of the debt enterprise, the debt item of the debt enterprise can be timely and effectively recovered according to the operation condition of the debt enterprise.

Description

Technical Field

[0001] The present invention relates to the field of fintech, and in particular, to a method, device, equipment, medium and program product for evaluating the business status of an enterprise. Background Art

[0002] As a method for comprehensively evaluating and analyzing the financial status of an enterprise, the evaluation of the business status of an enterprise is mainly used to prevent the financial risks of the enterprise and evaluate the solvency of the enterprise. Typically, in the case where an indebted enterprise fails to repay its debts as promised, whether its business status can be accurately evaluated becomes an important factor affecting the efficiency and effect of debt recovery.

[0003] In the prior art, the financial information of the indebted enterprise is usually obtained manually, and the business status of the indebted enterprise is determined based on the financial information.

[0004] However, the method of completely relying on manual determination of the business status of the indebted enterprise is likely to lead to inaccurate determination of the business status of the indebted enterprise, and thus the debts owed by the indebted enterprise cannot be recovered in a timely and effective manner. Summary of the Invention

[0005] The present invention provides a method, device, equipment, medium and program product for evaluating the business status of an enterprise, which can accurately determine the business status of the indebted enterprise and recover the debts owed by the indebted enterprise in a timely and effective manner according to the business status of the indebted enterprise.

[0006] In a first aspect, an embodiment of the present invention provides a method for evaluating the business status of an enterprise, including:

[0007] When it is detected that the indebted enterprise meets the default condition, obtaining the basic enterprise information of the indebted enterprise and the debt tracking clues in a pre-constructed clue model; wherein, the clue model includes an operation clue model, a judicial clue model, a fund clue model and a financing clue model;

[0008] According to the basic enterprise information of the indebted enterprise, determining the tracking keywords corresponding to each debt tracking clue respectively, and obtaining the clue query websites corresponding to each debt tracking clue;

[0009] Inputting the tracking keywords corresponding to each debt tracking clue into the corresponding clue query website for query, and obtaining the clue tracking results corresponding to each debt tracking clue;

[0010] Inputting the target clue tracking results that meet the debt recovery condition and the target debt tracking clues corresponding to the target clue tracking results into a pre-trained large model for processing, and obtaining the evaluation result of the business status of the indebted enterprise.

[0011] Optionally, detecting that the defaulting enterprise meets the default conditions includes: when the detected amount of the arrears owed by the defaulting enterprise is greater than the set arrears amount threshold, calculating the overdue repayment days of the arrears owed by the defaulting enterprise at the set frequency; if the overdue repayment days of the arrears owed by the defaulting enterprise are greater than the set overdue repayment days threshold, it is determined that the defaulting enterprise meets the default conditions.

[0012] Optionally, the arrears tracking clues in the business lead model include at least one of the following: business registration information change clues, abnormal cancellation clues, equity pledge clues, external bidding clues, environmental protection pollution discharge permit clues, external investment clues, invoice clues, charity donation clues, patent application clues, and enterprise information clues; the arrears tracking clues in the judicial clue model include at least one of the following: non-user's application for enforcement of the defaulting enterprise clues, judgment document clues, judgment document party clues, judgment document win-loss clues, and sued or unsued clues; the arrears tracking clues in the fund clue model include at least one of the following: legal person current monthly income total clue, legal person current monthly expenditure total clue, legal person fixed-term clue, treasury bond clue, agency fund clue, agency bond clue, company current account clue, company current account income total clue, company current account expenditure total clue, company fixed-term clue, margin clue, and wealth management agreement clue; the arrears tracking clues in the financing clue model include at least one of the following: recourse party's new collateral clue, non-user's recovery of arrears clue, non-user's loan disbursement clue, user's recovery of arrears clue, and user's loan disbursement clue.

[0013] Optionally, when the arrears tracking clues in the fund clue model include enterprise information clues, input the tracking keywords corresponding to each arrears tracking clue into the corresponding clue query website for query, and obtain the clue tracking results corresponding to each arrears tracking clue, including: input the enterprise name and industry of the defaulting enterprise into the corresponding clue query website for query to obtain the information articles of the defaulting enterprise; input each information article of the defaulting enterprise into the pre-trained article abstract extraction model for processing to obtain the article abstract of each information article.

[0014] Optionally, input the target clue tracking results that meet the matching arrears recovery conditions and the target arrears tracking clues corresponding to the target clue tracking results into the pre-trained large model for processing to obtain the business condition assessment result of the defaulting enterprise, including: determining whether the enterprise information clues of the defaulting enterprise are positive information clues according to the article abstract of each information article through the pre-trained information classification model; if so, use the article abstract of each information article as the target clue tracking result, and input the target clue tracking result and the target arrears tracking clues corresponding to the target clue tracking result into the pre-trained large model for processing to obtain the business condition assessment result of the defaulting enterprise.

[0015] Optionally, after inputting the target clue tracking result that meets the debt recovery condition and the target debt tracking clue corresponding to the target clue tracking result into a pre-trained large model for processing to obtain the business condition evaluation result of the debtor enterprise, it further includes: recovering the debts owed by the debtor enterprise according to the business condition evaluation result of the debtor enterprise to obtain a debt recovery result; updating the debt tracking clues in the clue model according to the debt recovery result to obtain an updated clue model.

[0016] In a second aspect, an embodiment of the present invention further provides a device for evaluating the business condition of an enterprise, including:

[0017] A debt tracking clue acquisition module, configured to obtain the basic enterprise information of the debtor enterprise and the debt tracking clues in a pre-constructed clue model when it is detected that the debtor enterprise meets the default condition; wherein, the clue model includes an operation clue model, a judicial clue model, a capital clue model, and a financing clue model;

[0018] A tracking keyword determination module, configured to determine tracking keywords corresponding to each debt tracking clue according to the basic enterprise information of the debtor enterprise, and obtain clue query websites corresponding to each debt tracking clue;

[0019] A clue tracking result determination module, configured to input the tracking keywords corresponding to each debt tracking clue into the corresponding clue query website for query to obtain clue tracking results corresponding to each debt tracking clue;

[0020] A business condition evaluation module, configured to input the target clue tracking result that meets the matching debt recovery condition and the target debt tracking clue corresponding to the target clue tracking result into a pre-trained large model for processing to obtain the business condition evaluation result of the debtor enterprise.

[0021] In a third aspect, an embodiment of the present invention further provides an electronic device, which includes:

[0022] At least one processor; and

[0023] A memory communicatively connected to the at least one processor; wherein,

[0024] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for evaluating the business condition of an enterprise provided in any embodiment of the present invention.

[0025] Fourthly, an embodiment of the present invention further provides a computer-readable storage medium storing computer instructions for causing a processor to implement the enterprise operation status evaluation method provided in any embodiment of the present invention when executed.

[0026] Fifthly, an embodiment of the present invention further provides a computer program product including a computer program that implements the enterprise operation status evaluation method provided in any embodiment of the present invention when executed by a processor.

[0027] In the technical solution of the embodiment of the present invention, when it is detected that a debtor enterprise meets the default condition, the tracking keywords corresponding to each debt tracking clue are input into the corresponding clue query website for querying to obtain the clue tracking results corresponding to each debt tracking clue, and the target clue tracking results that meet the debt recovery condition and the target debt tracking clues corresponding to the target clue tracking results are input into a pre-trained large model for processing to obtain the evaluation result of the operation status of the debtor enterprise. This implementation method avoids completely relying on manual determination of the operation status of the debtor enterprise, which is likely to lead to the situation where the operation status of the debtor enterprise cannot be accurately determined, and can accurately determine the operation status of the debtor enterprise, so as to recover the money owed by the debtor enterprise in a timely and effective manner.

[0028] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0030] Figure 1 is a flowchart of an enterprise operation status evaluation method provided in Embodiment 1 of the present invention;

[0031] Figure 2 is a flowchart of another enterprise operation status evaluation method provided in Embodiment 2 of the present invention;

[0032] Figure 3 is a schematic structural diagram of an enterprise operation status evaluation device provided in Embodiment 3 of the present invention;

[0033] Figure 4 is a schematic structural diagram of an electronic device provided in Embodiment 4 of the present invention. Detailed implementation manners

[0034] In order to enable those skilled in the art of the present technology to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0035] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned accompanying drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data used can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0036] Embodiment 1

[0037] Figure 1 is a flowchart of a method for evaluating the business condition of an enterprise provided according to Embodiment 1 of the present invention. This embodiment is applicable to the situation of evaluating the business condition of an enterprise in arrears. This method can be executed by an enterprise business condition evaluation device, which can be implemented in the form of hardware and / or software, and the enterprise business condition evaluation device can be configured in an electronic device such as a computer.

[0038] As Figure 1 shown, a method for evaluating the business condition of an enterprise disclosed in this embodiment includes:

[0039] S110. When it is detected that the enterprise in arrears meets the default condition, obtain the basic enterprise information of the enterprise in arrears and the debt tracking clues in the pre-constructed clue model.

[0040] In this embodiment, the default condition may be a condition that allows the recovery of the amount owed by the enterprise in arrears. There can be various default conditions. For example, the overdue time of the amount owed by the enterprise in arrears exceeds the set overdue time threshold, the enterprise in arrears refuses to pay interest, and the enterprise in arrears publicly states that it is unable to repay the amount it owes. The basic enterprise information of the enterprise in arrears may include the enterprise name, unified social credit code, industry category, and contract number signed by the enterprise in arrears, etc.

[0041] The lead models may include an operation lead model, a judicial lead model, a fund lead model, a financing lead model, etc. The operation lead model can be used to track the operation of the debtor enterprise. The judicial lead model can be used to track the winning or losing situation of judicial cases in which the debtor enterprise is a party. The fund lead model can be used to track the financial status of the debtor enterprise. The financing lead model can be used to track the financing situation of the debtor enterprise.

[0042] In this step, specifically, the basic enterprise information of the debtor enterprise and the debt tracking leads in all pre-constructed lead models can be directly obtained. Alternatively, after obtaining the basic enterprise information of the debtor enterprise, at least one lead model can be selected from all pre-constructed lead models as the target lead model according to the basic enterprise information of the debtor enterprise, and the debt tracking leads in the target lead model can be obtained.

[0043] In a specific example, when it is determined that the debtor enterprise is a small and micro enterprise according to the enterprise name of the debtor enterprise, the judicial lead model, the fund lead model, and the financing lead model can be used as the target lead models, and the debt tracking leads in the judicial lead model, the fund lead model, and the financing lead model can be obtained.

[0044] S120. According to the basic enterprise information of the debtor enterprise, determine the tracking keywords corresponding to each debt tracking lead, and obtain the lead query websites corresponding to each debt tracking lead.

[0045] In this embodiment, the tracking keyword can be a keyword that can query the lead tracking result corresponding to the debt tracking lead. The lead query website can be understood as a website used to query the debt tracking lead, such as a website for querying enterprise judicial information, a website for querying enterprise operation status, and a website for querying enterprise information, etc.

[0046] In this step, specifically, the tracking keywords corresponding to each debt tracking lead can be determined according to the basic enterprise information and the extended dimension information of the debtor enterprise. Among them, the extended dimension information can be determined according to the basic enterprise information of the debtor enterprise. For example, the trading counterpart of the debtor enterprise can be determined according to the trade contract number signed by the debtor enterprise. Alternatively, the tracking keywords used to query each debt tracking lead can be obtained from the basic enterprise information of the debtor enterprise.

[0047] Exemplarily, assuming that the debt tracking clue is a judgment document clue, the company name of the indebted enterprise and the company name of the trading partner can be used as the tracking keywords for the judgment document clue. Assuming that the debt tracking clue is a clue of changes in industrial and commercial registration information, the enterprise name and unified social credit code in the basic enterprise information of the indebted enterprise can be used as the tracking keywords for the clue of changes in industrial and commercial registration information.

[0048] S130. Input the tracking keywords corresponding to each debt tracking clue into the corresponding clue query website for query, and obtain the clue tracking results corresponding to each debt tracking clue.

[0049] In this step, specifically, at least one tracking keyword corresponding to the debt tracking clue can be input into the clue query website for query to obtain the clue tracking result corresponding to the debt tracking clue. Exemplarily, the number of tracking keywords input into the corresponding clue query website can be determined according to the number of tracking keywords corresponding to the debt tracking clue, which is from 1 to the number of tracking keywords, and the 1 to the number of tracking keywords are input into the clue query website for query in sequence according to the importance of the tracking keywords, and the clue tracking results corresponding to the 1 to the number of tracking keywords are obtained.

[0050] The advantage of such a setting is that by inputting the 1 to the number of tracking keywords into the clue query website for query in sequence, the clue tracking results can be made more abundant, providing a basis for accurately determining the business condition evaluation result of the indebted enterprise in the future.

[0051] S140. Input the target clue tracking result that meets the matching debt recovery condition and the target debt tracking clue corresponding to the target clue tracking result into a pre-trained large model for processing to obtain the business condition evaluation result of the indebted enterprise.

[0052] In this embodiment, the debt recovery condition may be the condition under which the amount owed by the indebted enterprise can be recovered. The large model can be trained using historical target debt tracking clues and target clue tracking results as training samples. The business condition evaluation result can be used to reflect the repayment ability of the indebted enterprise.

[0053] In a specific example, assuming that the debt tracking clue is the total income of the company's current account, when the monthly income of the indebted enterprise exceeds 100,000 yuan, the total income of the company's current account can be used as the target debt tracking clue, and the total income of the company's current account and the monthly income of the indebted enterprise are input into a pre-trained large model for processing.

[0054] In the technical solution of this embodiment, when it is detected that the debtor enterprise meets the default conditions, the basic enterprise information of the debtor enterprise and the debt tracking clues in the pre-constructed clue model are obtained; wherein, the clue model includes an operation clue model, a judicial clue model, a fund clue model, and a financing clue model; according to the basic enterprise information of the debtor enterprise, tracking keywords corresponding to each debt tracking clue are determined, and clue query websites corresponding to each debt tracking clue are obtained; the tracking keywords corresponding to each debt tracking clue are input into the corresponding clue query websites for querying to obtain clue tracking results corresponding to each debt tracking clue; the target clue tracking results that meet the debt recovery conditions and the target debt tracking clues corresponding to the target clue tracking results are input into a pre-trained large model for processing to obtain the technical means for the business condition assessment result of the debtor enterprise, which solves the problem that completely relying on manual determination of the business condition of the debtor enterprise is likely to lead to inaccurate determination of the business condition of the debtor enterprise, can accurately determine the business condition of the debtor enterprise, and timely and effectively recover the money owed by the debtor enterprise according to the business condition of the debtor enterprise.

[0055] Embodiment 2

[0056] Figure 2 It is a flowchart of another method for assessing the business condition of an enterprise provided according to Embodiment 2 of the present invention. This embodiment is a further optimization and expansion based on the above embodiments and can be combined with each optional technical solution in the above embodiments.

[0057] As Figure 2 shown, a method for assessing the business condition of an enterprise disclosed in this embodiment includes:

[0058] S210. When it is detected that the amount of money owed by the debtor enterprise is greater than the set debt amount threshold, calculate the overdue repayment days of the money owed by the debtor enterprise at the set frequency.

[0059] In this embodiment, the debt amount threshold can be understood as the maximum amount that the user can tolerate the debtor enterprise to default on. The set frequency can be annually, monthly, or daily, etc., and this embodiment does not limit this.

[0060] S220. If the overdue repayment days of the money owed by the debtor enterprise are greater than the set overdue repayment days threshold, determine that the debtor enterprise meets the default conditions, and obtain the basic enterprise information of the debtor enterprise and the debt tracking clues in the pre-constructed clue model.

[0061] Among them, the clue model includes an operation clue model, a judicial clue model, a fund clue model, and a financing clue model. The overdue repayment days threshold can be understood as the longest time that the user can tolerate the debtor enterprise to default on, such as 5 days, 30 days, or 90 days, etc.

[0062] The advantage of such a setting is that when the amount of arrears of the debtor enterprise is greater than the set arrears amount threshold and the overdue repayment time is greater than the set overdue repayment days threshold, it is determined that the debtor enterprise meets the default conditions, which can avoid directly pursuing the arrears of the debtor enterprise whose amount of arrears is greater than the set arrears amount threshold or the overdue repayment time is greater than the set overdue repayment days threshold, thus improving the efficiency of arrears recovery.

[0063] Optionally, the arrears tracking clues in the business lead model include at least one of the following: clues of changes in industrial and commercial registration information, clues of abnormal cancellation, clues of equity pledge, clues of external bidding, clues of environmental protection pollution discharge permits, clues of external investment, clues of invoices, clues of charitable donations, clues of patent applications, and clues of enterprise information; the arrears tracking clues in the judicial lead model include at least one of the following: clues of the execution application of the debtor enterprise by non - this user, clues of judgment documents, clues of the parties to judgment documents, clues of winning or losing in judgment documents, and clues of pending lawsuits; the arrears tracking clues in the fund lead model include at least one of the following: clues of the total monthly income of the legal person's current account, clues of the total monthly expenditure of the legal person's current account, clues of the legal person's fixed - term, clues of treasury bonds, clues of agency funds, clues of agency bonds, clues of the company's current accounts, clues of the total income of the company's current accounts, clues of the total expenditure of the company's current accounts, clues of the company's fixed - term, clues of margin, and clues of wealth management agreements; the arrears tracking clues in the financing lead model include at least one of the following: clues of new collateral of recourse parties, clues of non - this user recovering arrears, clues of non - this user granting loans, clues of this user recovering arrears, and clues of this user granting loans.

[0064] Specifically, the clues of changes in industrial and commercial registration information can be used to track whether the legal representative of the debtor enterprise has changed. The clues of abnormal cancellation can be used to track whether the debtor enterprise has been abnormally cancelled. The clues of equity pledge can be used to track the equity pledge situation of the debtor enterprise. The clues of external bidding can be used to track the external bidding situation of the debtor enterprise. The clues of environmental protection pollution discharge permits can be used to track the environmental protection pollution discharge consumption of the debtor enterprise. The clues of external investment can be used to track the external investment situation of the debtor enterprise. The clues of invoices can be used to track the expenditure situation of the debtor enterprise. The clues of charitable donations can be used to track the amount of charitable donations of the debtor enterprise. The clues of patent applications can be used to track the patent value of the debtor enterprise. The clues of enterprise information can be used to track the positive and negative enterprise information of the debtor enterprise.

[0065] The execution clue applied by non - this user against the indebted enterprise can be used to track the amount and time of execution applications made by other borrowers against the indebted enterprise. The judgment document clue and the judgment document party clue can be used to track the judicial cases in which the indebted enterprise is a party. The judgment document win - loss clue can be used to track the win - loss situations of the judicial cases in which the indebted enterprise is a party. The clue of cases to be sued but not yet sued can be used to track the cases that the user should sue but has not yet sued.

[0066] The total monthly income clue of legal person current account, the total monthly expenditure clue of legal person current account, the legal person fixed - term clue, the treasury bill clue, the agency fund clue, the agency bond clue, the company current account clue, the total income clue of company current account, the total expenditure clue of company current account, the company fixed - term clue, the margin clue and the wealth management agreement clue can be used to track the capital reserve and flow of the indebted enterprise.

[0067] The clue of newly added collateral of recourse parties, the clue of debt collection by non - this user, the clue of loan issuance by non - this user, the clue of debt collection by this user and the clue of loan issuance by this user can be used to track the loan repayment and new addition of the indebted enterprise.

[0068] The advantage of such a setting is that by evaluating the operating conditions of the indebted enterprise through each debt - tracking clue in the business clue model, judicial clue model, capital clue model and financing clue model, the comprehensiveness and accuracy of evaluating the operating conditions of the indebted enterprise are improved, providing a basis for timely and effective recovery of the debts owed by the indebted enterprise.

[0069] S230. According to the basic enterprise information of the indebted enterprise, determine the tracking keywords corresponding to each debt - tracking clue respectively, and obtain the clue query websites corresponding to each debt - tracking clue respectively.

[0070] S240. Input the tracking keywords corresponding to each debt - tracking clue into the corresponding clue query website for query, and obtain the clue tracking results corresponding to each debt - tracking clue respectively.

[0071] Exemplarily, assuming that the debt - tracking clue is the clue of cases to be sued but not yet sued, the enterprise name and unified social credit code of the indebted enterprise can be input into the corresponding clue query website for query, and the clue tracking results corresponding to each debt - tracking clue can be obtained.

[0072] Optionally, when the debt tracking clues in the fund clue model include enterprise information clues, the tracking keywords corresponding to each debt tracking clue are input into the corresponding clue query website for query, and the clue tracking results corresponding to each debt tracking clue are obtained, including: inputting the enterprise name and industry of the debtor enterprise into the corresponding clue query website for query to obtain the information articles of the debtor enterprise; inputting each information article of the debtor enterprise into a pre-trained article abstract extraction model for processing to obtain the article abstract of each information article.

[0073] Specifically, the information articles can be screened according to the publication time of each information article to obtain the information articles with the publication time within the set time period. Among them, the set time period can be set according to user needs, such as half a year or one year, etc. Then, the information articles of the debtor enterprise within the set time period can be input into a pre-trained article abstract extraction model for processing.

[0074] The advantage of such a setting is that by extracting the article abstract of each information article, it is possible to avoid directly evaluating the operating conditions based on the information articles of the debtor enterprise, thereby improving the efficiency of evaluating the operating conditions of the debtor enterprise.

[0075] S250. Input the target clue tracking result that meets the matching debt recovery conditions and the target debt tracking clue corresponding to the target clue tracking result into a pre-trained large model for processing to obtain the evaluation result of the operating conditions of the debtor enterprise.

[0076] Exemplarily, in the case where the debt tracking clue is a clue of lawsuit not yet filed, if the target clue tracking result is that there is a lawsuit not yet filed against the debtor enterprise and the debtor enterprise has not declared bankruptcy, the clue of lawsuit not yet filed and the corresponding clue tracking result can be input into a pre-trained large model for processing.

[0077] Optionally, when the debt tracking clues in the fund clue model include enterprise information clues, input the target clue tracking result that meets the matching debt recovery conditions and the target debt tracking clue corresponding to the target clue tracking result into a pre-trained large model for processing to obtain the evaluation result of the operating conditions of the debtor enterprise, including: determining whether the enterprise information clue of the debtor enterprise is a positive information clue according to the article abstract of each information article through a pre-trained information classification model; if so, use the article abstract of each information article as the target clue tracking result, and input the target clue tracking result and the target debt tracking clue corresponding to the target clue tracking result into a pre-trained large model for processing to obtain the evaluation result of the operating conditions of the debtor enterprise.

[0078] Specifically, the article abstract of each news article can be input into a pre-trained news classification model for classification to obtain positive and negative article abstracts. Then, the proportion of the number of positive article abstracts in the total number of article abstracts can be calculated, and when the above proportion is greater than the set proportion threshold, the enterprise information clue of the defaulting enterprise can be determined as a positive information clue.

[0079] The advantage of such a setting is that by judging whether the enterprise information clue is a positive information clue and, when the enterprise information clue is a positive information clue, evaluating the operating condition of the defaulting enterprise based on the enterprise information clue, it is possible to evaluate the operating condition of the defaulting enterprise according to the positive trends of the defaulting enterprise, further improving the accuracy of the operating condition evaluation result.

[0080] S260. According to the evaluation result of the operating condition of the defaulting enterprise, recover the amount owed by the defaulting enterprise to obtain a debt recovery result.

[0081] In this step, specifically, an evaluation report on the debt of the defaulting enterprise can be generated based on the evaluation result of the operating condition of the defaulting enterprise and the basic enterprise information. Then, the debt evaluation report can be sent to the defaulting enterprise through channels such as email, and the debt recovery result can be determined according to the reply result of the defaulting enterprise. Among them, the debt recovery result can include successful recovery, failed recovery, and the debt recovery result pending.

[0082] S270. Update the debt tracking clue in the clue model according to the debt recovery result to obtain an updated clue model.

[0083] In this step, specifically, when the debt recovery result is a failed recovery, the incorrect target debt tracking clue can be located according to the discrepancy between the actual operating condition of the defaulting enterprise and the evaluation result of the operating condition, and the incorrect debt tracking clue can be removed.

[0084] Through the above setting, the debt tracking clue in the clue model can be updated in a timely manner, avoiding continuously determining the evaluation result of the operating condition based on the incorrect debt tracking clue, and improving the accuracy of the evaluation result of the operating condition.

[0085] In the technical solution of this embodiment, when the amount of arrears of the debtor enterprise is greater than the set arrears amount threshold and the overdue repayment time is greater than the set overdue repayment days threshold, it is determined that the debtor enterprise meets the default conditions, which can avoid directly pursuing the arrears of the debtor enterprise whose amount of arrears is greater than the set arrears amount threshold or the overdue repayment time is greater than the set overdue repayment days threshold, thus improving the efficiency of arrears tracking. Secondly, by updating the arrears tracking clues in the clue model according to the arrears recovery result, the arrears tracking clues in the clue model can be updated in a timely manner, avoiding continuously determining the business condition evaluation result based on incorrect arrears tracking clues and improving the accuracy of the business condition evaluation result.

[0086] In a preferred embodiment of the embodiment of the present invention, when it is detected that the amount of arrears of the debtor enterprise is greater than the set arrears amount threshold, the overdue repayment days of the arrears of the debtor enterprise can be calculated at a set frequency. If the overdue repayment days of the arrears of the debtor enterprise are greater than the set overdue repayment days threshold and the enterprise name of the debtor enterprise is not on the white list of debtor enterprises, a prompt message indicating that the debtor enterprise is a written-off case with outstanding debts or a non-performing loan customer will be sent to the user. Then, according to the basic enterprise information of the debtor enterprise, the information dimensions of the debtor enterprise, including litigation, industrial and commercial registration, fund transactions, and invoices, can be collected from the pre-constructed data lake. At this time, according to the information dimensions of the debtor enterprise and the predefined business condition evaluation rules, an operation clue model, a judicial clue model, a fund clue model, and a financing clue model can be constructed, and the arrears tracking clues in each clue model can be stored in the clue pool.

[0087] After that, the arrears tracking clues can be obtained from the clue pool, and according to the basic enterprise information of the debtor enterprise, the tracking keywords corresponding to each arrears tracking clue can be determined. The tracking keywords corresponding to each arrears tracking clue are input into the corresponding clue query website for query, and the clue tracking results corresponding to each arrears tracking clue are obtained. Finally, the target clue tracking results that meet the matching arrears recovery conditions and the target arrears tracking clues corresponding to the target clue tracking results can be input into the pre-trained large model for processing to obtain the business condition evaluation result of the debtor enterprise. After sending the business condition evaluation result of the debtor enterprise to the debtor enterprise, the arrears recovery result can be determined according to the reply result of the debtor enterprise. When the arrears recovery result is a failure to recover, the incorrect target arrears tracking clue can be located according to the discrepancy between the actual business condition of the debtor enterprise and the business condition evaluation result, and the incorrect arrears tracking clue can be removed.

[0088] It should be noted that the information related to the indebted enterprise collected by the present invention is information and data authorized by the indebted enterprise or fully authorized by all parties. Moreover, for the processing of relevant data such as collection, storage, use, processing, transmission, provision, disclosure, and application, all comply with the relevant laws, regulations, and standards of the relevant countries and regions, necessary confidentiality measures are taken, it does not violate public order and good customs, and a corresponding operation entry is provided for the indebted enterprise to choose to authorize or refuse.

[0089] Embodiment III

[0090] Figure 3 It is a schematic structural diagram of an enterprise operating condition evaluation device provided according to Embodiment III of the present invention. This embodiment is applicable to the situation of evaluating the operating condition of an indebted enterprise. The enterprise operating condition evaluation device can be implemented in the form of hardware and / or software and can be configured in an electronic device such as a computer.

[0091] As Figure 3 shown, the enterprise operating condition evaluation device disclosed in this embodiment includes: an arrears tracking clue acquisition module 31, a tracking keyword determination module 32, a clue tracking result determination module 33, and an operating condition evaluation module 34, where:

[0092] The arrears tracking clue acquisition module 31 is used to obtain the basic enterprise information of the indebted enterprise and the arrears tracking clues in the pre-constructed clue model when it is detected that the indebted enterprise meets the default conditions; among them, the clue model includes an operating clue model, a judicial clue model, a capital clue model, and a financing clue model;

[0093] The tracking keyword determination module 32 is used to determine the tracking keywords corresponding to each arrears tracking clue according to the basic enterprise information of the indebted enterprise and obtain the clue query websites corresponding to each arrears tracking clue;

[0094] The clue tracking result determination module 33 is used to input the tracking keywords corresponding to each arrears tracking clue into the corresponding clue query website for query to obtain the clue tracking results corresponding to each arrears tracking clue;

[0095] The operating condition evaluation module 34 is used to input the target clue tracking results that meet the matching arrears recovery conditions and the target arrears tracking clues corresponding to the target clue tracking results into a pre-trained large model for processing to obtain the operating condition evaluation results of the indebted enterprise.

[0096] In the technical solution of this embodiment, through the mutual cooperation of the arrears tracking clue acquisition module, the tracking keyword determination module, the clue tracking result determination module, and the business condition evaluation module, the problem of completely relying on manual determination of the business condition of the arrears enterprise, which is likely to lead to inaccurate determination of the business condition of the arrears enterprise, is solved. The business condition of the arrears enterprise can be accurately determined, and the arrears owed by the arrears enterprise can be recovered in a timely and effective manner according to the business condition of the arrears enterprise.

[0097] Optionally, the arrears tracking clue acquisition module 31 is specifically configured to calculate the overdue repayment days of the arrears owed by the arrears enterprise at a set frequency when it is detected that the arrears amount of the arrears owed by the arrears enterprise is greater than the set arrears amount threshold; if the overdue repayment days of the arrears owed by the arrears enterprise are greater than the set overdue repayment days threshold, it is determined that the arrears enterprise meets the default condition.

[0098] Optionally, the arrears tracking clues in the business clue model include at least one of the following: clues of changes in industrial and commercial registration information, clues of abnormal cancellation, clues of equity pledge, clues of external bidding, clues of environmental protection pollution discharge permits, clues of external investment, clues of invoices, clues of charitable donations, clues of patent applications, and clues of enterprise information; the arrears tracking clues in the judicial clue model include at least one of the following: clues of non-user application for enforcement of the arrears enterprise, clues of judgment documents, clues of parties to judgment documents, clues of winning or losing in judgment documents, and clues of responding or not responding to lawsuits; the arrears tracking clues in the capital clue model include at least one of the following: clues of the total monthly income of the legal person's current account, clues of the total monthly expenditure of the legal person's current account, clues of the legal person's fixed-term, clues of treasury bonds, clues of agency funds, clues of agency bonds, clues of the company's current account, clues of the total income of the company's current account, clues of the total expenditure of the company's current account, clues of the company's fixed-term, clues of margin, and clues of wealth management agreements; the arrears tracking clues in the financing clue model include at least one of the following: clues of new collateral for recourse parties, clues of non-user recovery of arrears, clues of non-user loans, clues of user recovery of arrears, and clues of user loans.

[0099] Optionally, the clue tracking result determination module 33 is specifically configured to: when the arrears tracking clue in the capital clue model includes the enterprise information clue, input the enterprise name and industry of the arrears enterprise into the corresponding clue query website for query to obtain the information articles of the arrears enterprise; input each information article of the arrears enterprise into the pre-trained article abstract extraction model for processing to obtain the article abstract of each information article.

[0100] Optionally, the business condition evaluation module 34 is specifically configured to: determine whether the enterprise information clue of the debtor enterprise is a positive information clue according to the article abstract of each information article through a pre-trained information classification model; if so, use the article abstract of each information article as the target clue tracking result, and input the target clue tracking result and the target debt tracking clue corresponding to the target clue tracking result into a pre-trained large model for processing to obtain the business condition evaluation result of the debtor enterprise.

[0101] Optionally, the device further includes a clue model update module, which is configured to: recover the amount owed by the debtor enterprise according to the business condition evaluation result of the debtor enterprise to obtain a debt recovery result; update the debt tracking clue in the clue model according to the debt recovery result to obtain an updated clue model.

[0102] The enterprise business condition evaluation device provided by the embodiments of the present invention can execute the enterprise business condition evaluation method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method. The content not described in detail in this embodiment can be referred to the description in any method embodiment of this application.

[0103] Embodiment 4

[0104] Figure 4 The structural schematic diagram of the electronic device 10 that can be used to implement the embodiments of the present invention is shown. As Figure 4 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. Among them, the memory stores a computer program executable by at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0105] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0106] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the enterprise operating condition evaluation method.

[0107] In some embodiments, the enterprise operating condition evaluation method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the enterprise operating condition evaluation method described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the enterprise operating condition evaluation method by any other suitable means (e.g., by means of firmware).

[0108] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), systems-on-chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs, which can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0109] The computer program for implementing the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer program can be executed entirely on the machine, partially on the machine, as an independent software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0110] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0111] To provide for interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0112] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0113] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The relationship between the client and the server is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0114] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added or deleted. For example, the steps described in the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0115] The above specific embodiments do not constitute a limitation to the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for evaluating business conditions, characterized in that: The method comprises: When it is detected that the debtor enterprise meets the default conditions, basic enterprise information of the debtor enterprise and debt tracking clues in the pre-built clue model are obtained; wherein the clue model includes an operating clue model, a judicial clue model, a capital clue model and a financing clue model; According to the basic enterprise information of the debtor enterprise, determine the tracking keywords corresponding to each debt tracking clue, and obtain the clue query website corresponding to each debt tracking clue; Input the tracking keywords corresponding to each debt tracking clue into the corresponding clue query website for query, and obtain the clue tracking results corresponding to each debt tracking clue; The target clue tracking results that meet the matching debt recovery conditions and the target debt tracking clues corresponding to the target clue tracking results are input into the pre-trained large model for processing to obtain the operating status evaluation results of the debt-owing enterprises.

2. The method according to claim 1, characterized in that It is detected that the defaulting enterprise meets the default conditions, including: When it is detected that the amount owed by the debtor enterprise is greater than the set amount threshold, the overdue repayment days of the amount owed by the debtor enterprise are calculated according to the set frequency; If the number of days overdue for the amount owed by the debtor enterprise is greater than the set overdue repayment days threshold, it is determined that the debtor enterprise meets the default conditions.

3. The method according to claim 1, characterized in that The debt tracking clues in the business clue model include at least one of the following: Clues on changes in business registration information, abnormal cancellations, equity pledges, external bidding, environmental pollution discharge permits, external investments, invoices, charitable donations, patent applications, and corporate information; The debt tracking clues in the judicial clue model include at least one of the following: Clues of execution applied for by non-users against the debtor enterprises, clues of judgment documents, clues of parties involved in judgment documents, clues of winning and losing cases in judgment documents, and clues of responding to and not filing lawsuits; The debt tracking clues in the fund clue model include at least one of the following: Legal person's monthly current account income clues, legal person's monthly current account expenditure clues, legal person's fixed deposit clues, treasury bill clues, agency fund clues, agency bond clues, company's current account clues, company's current account income clues, company's current account expenditure clues, company's fixed deposit clues, margin clues and financial management agreement clues; The debt tracking clues in the financing clue model include at least one of the following: There are clues of new collaterals added by parties with the right of recourse, clues of debts recovered by non-users, clues of loans issued by non-users, clues of debts recovered by this user, and clues of loans issued by this user.

4. The method according to claim 3, characterized in that When the debt tracking clues of the capital clue model include corporate information clues, the tracking keywords corresponding to each debt tracking clue are input into the corresponding clue query website for query, and the clue tracking results corresponding to each debt tracking clue are obtained, including: Enter the company name and industry of the debtor company into the corresponding clue query website to query and obtain information articles about the debtor company; Each news article of the company in arrears is input into a pre-trained article summary extraction model for processing to obtain an article summary of each news article.

5. The method according to claim 4, characterized in that The target lead tracking results that meet the matching debt recovery conditions and the target debt tracking leads corresponding to the target lead tracking results are input into the pre-trained large model for processing to obtain the operating status evaluation results of the debt-owing enterprises, including: Determine whether the enterprise information clue of the debtor enterprise is a positive information clue based on the article summary of each information article through a pre-trained information classification model; If so, the article summary of each information article is used as the target clue tracking result, and the target clue tracking result and the target debt tracking clue corresponding to the target clue tracking result are input into the pre-trained large model for processing to obtain the operating status evaluation result of the debt-owing enterprise.

6. The method according to claim 1, characterized in that After the target lead tracking results that meet the matching debt recovery conditions and the target debt tracking leads corresponding to the target lead tracking results are input into the pre-trained large model for processing and the operating status evaluation results of the debt-owing enterprises are obtained, it also includes: According to the results of the business status assessment of the debtor enterprise, the debt owed by the debtor enterprise is recovered and the debt recovery result is obtained; The debt tracking clues in the clue model are updated according to the debt collection results to obtain an updated clue model.

7. An enterprise operating status evaluation device, characterized in that: The device comprises: The debt tracking clue acquisition module is used to obtain the basic enterprise information of the debtor enterprise and the debt tracking clues in the pre-built clue model when it is detected that the debtor enterprise meets the default conditions; wherein the clue model includes the business clue model, the judicial clue model, the capital clue model and the financing clue model; A tracking keyword determination module is used to determine the tracking keywords corresponding to each debt tracking clue based on the basic enterprise information of the debtor enterprise, and obtain the clue query website corresponding to each debt tracking clue; A clue tracking result determination module is used to input the tracking keywords corresponding to each debt tracking clue into the corresponding clue query website for query, and obtain the clue tracking results corresponding to each debt tracking clue; The operating status assessment module is used to input the target clue tracking results that meet the matching debt recovery conditions and the target debt tracking clues corresponding to the target clue tracking results into the pre-trained large model for processing to obtain the operating status assessment results of the debt-owing enterprises.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the enterprise business status assessment method described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the enterprise business status assessment method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the method for evaluating business conditions of an enterprise according to any one of claims 1 to 6.

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