Technology credit enhancement methods for science and technology enterprises and their devices, equipment and media

Abstract

The present application discloses a method for technology credit enhancement of a technology enterprise and its device, equipment, and medium, and relates to the field of computer technology. Among them, the method includes: obtaining the first type of data and the second type of data of the evaluation object, the first type of data and the second type of data are different types of data, and the second type of data includes technical flow data; inputting the first type of data into the credit rating model to obtain the credit rating; inputting the second type of data into the credit enhancement rating model to obtain the credit enhancement rating; correcting the credit rating according to the credit enhancement rating to obtain the credit enhancement result of the evaluation object. The embodiment of the present application can improve the objectivity of the credit evaluation of the scientific and technological innovation ability of the evaluation object on the basis of the traditional evaluation method, and thus also help to provide a reliable basis for the determination of the investment and financing plan for the evaluation object. The embodiment of the present application can be applied to the financial field, credit assessment or other fields.

Description

Technical Field

[0001] The present application belongs to the field of computer technology, and in particular, relates to a technology enterprise technology enhancement method and its device, equipment, and medium. Background Art

[0002] In the service field, various institutions usually have evaluation needs. For example, when a financial institution receives a loan request from an enterprise, it may need to evaluate the credit rating of the enterprise; or a credit rating company may need to evaluate the reputation and status of the enterprise.

[0003] In the related art, when evaluation agencies such as financial institutions and credit rating companies evaluate an evaluation object such as a company, they usually focus on the financial data of the evaluation object, but pay less attention to the scientific and technological innovation capabilities of the evaluation object. Summary of the invention

[0004] The embodiments of the present application provide a method for enhancing the technical credit of a technology enterprise and its apparatus, equipment, and medium to solve the problem in related technologies that evaluation agencies rarely describe the scientific and technological innovation capabilities when evaluating the evaluation objects.

[0005] In a first aspect, the present application provides a method for enhancing the credit of a technology enterprise, the method comprising:

[0006] Obtain the first type of data and the second type of data of the evaluation object, the first type of data and the second type of data are different types of data, and the second type of data includes technical flow data;

[0007] Input the first type of data into the credit rating model to obtain the credit rating;

[0008] Input the second type of data into the credit enhancement rating model to obtain the credit enhancement grade;

[0009] The credit rating is modified according to the credit enhancement level to obtain the credit enhancement result of the evaluated object.

[0010] In a second aspect, the embodiment of the present application provides a technology enterprise technology credit enhancement device, the device comprising:

[0011] An acquisition module is used to acquire first-category data and second-category data of the evaluation object, where the first-category data and the second-category data are different types of data, and the second-category data includes technical flow data;

[0012] The first rating module inputs the first type of data into the credit rating model to obtain a credit rating;

[0013] The second rating module is used to input the second type of data into the credit enhancement rating model to obtain the credit enhancement grade;

[0014] The correction module is used to correct the credit rating according to the credit enhancement level to obtain the credit enhancement result of the evaluation object.

[0015] In a third aspect, an embodiment of the present application provides an electronic device, the device comprising: a processor and a memory storing computer program instructions;

[0016] When the processor executes computer program instructions, the technology enterprise technology enhancement method shown in the first aspect is implemented.

[0017] In a fourth aspect, an embodiment of the present application provides a computer storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the technology enterprise technology enhancement method shown in the first aspect is implemented.

[0018] In a fifth aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the technology enterprise technology enhancement method as shown in the first aspect.

[0019] The technology credit enhancement method for technology enterprises provided in the embodiment of the present application obtains the first type of data and the second type of data of the evaluation object, the first type of data and the second type of data are different types of data, and the second type of data includes technology flow data; the first type of data is input into the credit rating model to obtain the credit rating; the second type of data is input into the credit enhancement rating model to obtain the credit enhancement rating; the credit rating is corrected according to the credit enhancement rating to obtain the credit enhancement result of the evaluation object. In this embodiment, the credit enhancement result of the evaluation object is obtained by correcting the credit rating obtained based on the credit rating model by the credit enhancement rating obtained based on the credit rating model. In this way, the objectivity of the credit evaluation of the scientific and technological innovation ability of the evaluation object can be improved on the basis of the traditional evaluation method, and thus it also helps to provide a reliable basis for determining the investment and financing plan for the evaluation object. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] Figure 1 This is a flow chart of a technology enterprise technology credit enhancement method provided in an embodiment of the present application;

[0022] Figure 2 It is another flow chart of the technology credit enhancement method for technology enterprises provided in the embodiment of the present application;

[0023] Figure 3This is another flow chart of the technology credit enhancement method for technology enterprises provided in the embodiment of the present application;

[0024] Figure 4 It is a structural diagram of a technology enterprise technology credit enhancement device provided in an embodiment of the present application;

[0025] Figure 5 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0027] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or equipment. In the absence of further restrictions, the elements defined by the sentence "include..." do not exclude the existence of other identical elements in the process, method, article or equipment including the elements. In addition, it should be noted that the technical solution of the present application complies with the relevant provisions of national laws and regulations on the acquisition, storage, use, processing, etc. of data.

[0028] The method provided in the embodiment of the present application can be applied to a system for credit evaluation of technology enterprises. The system may include a first rating module, a second rating module and a correction module. Among them, the first rating module is used to determine the credit rating of the technology enterprise based on the financial data of the technology enterprise, the second rating module is used to determine the technological innovation level (or referred to as the credit enhancement level) of the technology enterprise, and the correction module can be used to correct the credit rating of the technology enterprise determined by the first rating module according to the technological innovation level of the technology enterprise determined by the second rating module, and obtain the final credit rating of the technology enterprise.

[0029] The embodiments of the present application are improvements on the overall implementation scheme of the credit evaluation of technology enterprises. The construction and calculation methods of the rating models are not specifically limited. Any available type of rating model can be applied to the embodiments of the present application, such as mathematical calculation models based on statistics, rules or decision trees, or models based on machine learning algorithms.

[0030] The following first describes an application scenario of the technology enterprise technology credit enhancement method provided in the embodiment of the present application. The technology enterprise technology credit enhancement method can be applied in the application scenario of financial institutions granting credit to corporate customers.

[0031] Generally speaking, financial institutions usually need to conduct a credit evaluation on corporate customers before granting them credit.

[0032] In related technologies, the credit evaluation of corporate customers adopts a rating model, which comprehensively evaluates the customer's default risk through a combination of qualitative and quantitative methods. In qualitative evaluation, financial institutions understand the current business status of the enterprise through due diligence and conduct a comprehensive evaluation; in quantitative evaluation, financial data often plays an important role because the financial data is a true and intuitive reflection of the company's business development and key financial indicators directly depict the risk characteristics and debt repayment ability of the enterprise.

[0033] Most technology companies are small and medium-sized enterprises. Some companies with strong innovation capabilities and advanced technologies may have a long R&D investment period, market prospects, but weak profitability. In the rating model dominated by financial evaluation, such companies do not have an advantage and have difficulty in financing.

[0034] In the relevant technology, the indicators related to the evaluation of scientific and technological innovation attributes may be adjusted in the existing rating model to improve the final credit evaluation results of technology companies. However, this method has the following problems: first, it is difficult to unify the adjustment of relevant indicators, and there are many special cases, which makes it difficult to ensure the fairness of credit evaluation results, and thus there are problems such as corporate moral risk and credit personnel operational risk; second, it is difficult to grasp the proportion of financial indicators and scientific and technological innovation attribute evaluation indicators in the rating model, and it is still easy for financial data to obscure scientific and technological innovation capabilities.

[0035] In other examples, credit evaluation methods can also be used in the application scenarios of credit rating companies evaluating enterprises. In the process of evaluating technology companies, credit rating companies may also overemphasize the capital flow of technology companies, resulting in low evaluation results for technology companies.

[0036] In order to solve the existing technical problems, such as Figure 1 As shown, the technology credit enhancement method for technology enterprises provided in the embodiment of the present application includes:

[0037] Step 101, obtaining first-category data and second-category data of the evaluation object, where the first-category data and the second-category data are different types of data, and the second-category data includes technical flow data;

[0038] Step 102, inputting the first type of data into a credit rating model to obtain a credit rating;

[0039] Step 103, inputting the second type of data into the credit enhancement rating model to obtain the credit enhancement grade;

[0040] Step 104, correct the credit rating according to the credit enhancement rating to obtain the credit enhancement result of the evaluation object.

[0041] The technology enterprise's technical credit enhancement method can be applied in electronic devices, wherein the electronic devices can be portable electronic devices such as mobile terminals and tablet computers, or non-fixed electronic devices such as servers and personal computers, without specific limitation here.

[0042] In combination with actual application scenarios, electronic equipment can be equipment on the evaluation institution side used to evaluate the evaluation object. Accordingly, the executor of the technology credit enhancement method for technology enterprises can be the evaluation institution. The evaluation institution can be a financial institution or a credit rating company, etc., which is not specifically limited here.

[0043] To simplify the description, the following will mainly illustrate the embodiments of the present application in conjunction with the application scenario in which a financial institution grants credit to a corporate client. On this basis, the subject of the technology enterprise technical credit enhancement method can be the above-mentioned financial institution.

[0044] In step 101, the financial institution may obtain the first type of data and the second type of data of the evaluation object.

[0045] In the scenario where the above-mentioned financial institutions provide technical credit enhancement for technology enterprises to clients who have intentions, are preparing to grant credit, or provide guarantees, the evaluation objects can be legal entities, non-legal entities, non-resident enterprises that have established institutions or places in China, technology enterprises among overseas enterprises, or natural persons related to technology enterprises, etc., and no specific restrictions are made here.

[0046] The first category of data and the second category of data may be different types of data, or two groups of data with different contents.

[0047] With some examples, the first type of data may include the financial data of the evaluation object, such as the cash flow, asset mortgage or pledge of the enterprise, etc. The second type of data may include the technical flow data of the evaluation object, such as the application, authorization or licensing data of the enterprise's intellectual property rights, etc., which can reflect the scientific and technological innovation capabilities of the evaluation object.

[0048] In some other examples, the first type of data can be the conventional data used in the process of enhancing the technology credit of technology enterprises in the related art, that is, the first type of data can be the conventional data mainly composed of financial data. And the second type of data can include technical flow data, etc.

[0049] In step 102, the financial institution can input the first type of data into a preset credit rating model to obtain a credit rating.

[0050] The credit rating model can be a pre-established rating model, which can be a mathematical calculation model based on statistics, rules or decision trees, or a model based on machine learning algorithms, etc., and no specific limitation is made here.

[0051] In one example, the credit rating model can focus on the financial evaluation of enterprises.

[0052] Of course, in actual applications, the credit rating model can also be adjusted as needed to ensure the match between the first type of data and the credit rating model. That is to say, the credit rating model can output a credit rating according to the input first type of data.

[0053] For the sake of simplicity of description, the credit rating output by the credit rating model can be hereinafter referred to as the first credit rating.

[0054] The representation method of the first credit rating can be set as needed. For example, the first credit rating can be represented in the form of "A, B, C, D...", "C1, C2, C3,..." or "Jia, Yi, Bing, Ding,...". Or, in some feasible ways, the first credit rating can also be represented in the form of numerical values, etc., and no detailed examples are given here.

[0055] In step 103, the financial institution can input the second type of data into a preset credit enhancement rating model to obtain a credit enhancement rating.

[0056] The credit enhancement rating model can be pre-set, which can be a mathematical calculation model based on statistics, rules or decision trees, or a model based on machine learning algorithms, etc., and no specific limitation is made here.

[0057] The second type of data can include technical flow data, and the credit enhancement rating model can be matched with the second type of data. Correspondingly, the credit enhancement rating output by the credit enhancement rating model can effectively reflect the technological innovation ability of the evaluation object.

[0058] The representation method of the credit enhancement rating can be similar to that of the first credit rating; or, the credit enhancement rating can also be the increment for the first credit rating, etc., and no specific limitation is made here.

[0059] In practical applications, the above step 102 and step 103 may be performed simultaneously or sequentially, which is not specifically limited here.

[0060] Since the first credit rating and the credit enhancement rating can be considered to be obtained based on two relatively independent model outputs, therefore, combined with the example of the application scenario in the above text, the credit enhancement rating model can obtain the credit enhancement rating based on the second type of data, which can effectively isolate the impact of the company's financial data. Therefore, the credit enhancement rating can more effectively reflect the company's technological innovation capabilities and avoid the phenomenon that financial data obscures its scientific and technological innovation capabilities.

[0061] In step 104, the financial institution may revise the first credit rating according to the credit enhancement rating to obtain a credit enhancement result of the evaluation object.

[0062] To simplify the description, the credit enhancement result may be referred to as the second credit rating hereinafter.

[0063] Taking an example, the credit rating may include N main ratings such as A, B, C, D, etc. (N is a positive integer). If the first credit rating obtained is C, and the credit enhancement rating is an increase of one level, then in step 104, the first credit rating is corrected by the credit enhancement rating, and the second credit rating obtained may be B.

[0064] In another example, if the first credit rating is C and the credit enhancement rating is B, then in step 104, the first credit rating is corrected by the credit enhancement rating, and the second credit rating obtained may be C+.

[0065] That is to say, in actual application, the method of correcting the first credit rating according to the credit enhancement rating can be to add the ratings, or to average or weighted sum, etc., which can be selected according to actual needs.

[0066] Combined with the application scenario of financial institutions granting credit to corporate customers in the above text, in step 104 of this embodiment, the credit enhancement level used to reflect the technological innovation capability of the enterprise can directly modify the first credit level, which in turn directly affects the determination of the second credit level. In this way, the credit level of the technology enterprise can be effectively improved, the flexibility of credit evaluation can be increased, and the financing difficulty of the technology enterprise can be reduced.

[0067] The technology credit enhancement method for technology enterprises provided in the embodiment of the present application obtains the first type of data and the second type of data of the evaluation object, the first type of data and the second type of data are different types of data, and the second type of data includes technology flow data; the first type of data is input into the credit rating model to obtain the credit rating; the second type of data is input into the credit enhancement rating model to obtain the credit enhancement rating; the credit rating is corrected according to the credit enhancement rating to obtain the credit enhancement result of the evaluation object. In this embodiment, the credit enhancement result of the evaluation object is obtained by correcting the credit rating obtained based on the credit rating model by the credit enhancement rating obtained based on the credit rating model. In this way, the objectivity of the credit evaluation of the scientific and technological innovation ability of the evaluation object can be improved on the basis of the traditional evaluation method, and thus it also helps to provide a reliable basis for determining the investment and financing plan for the evaluation object.

[0068] It is worth emphasizing again that the technology credit enhancement method for technology enterprises provided in the embodiments of this application can be applied to financial institutions, as well as non-financial institutions such as credit rating companies. The evaluation object can be a legal person organization, an unincorporated organization, a non-resident enterprise with an institution or place established in China, a technology enterprise in a foreign enterprise, or a natural person related to a technology enterprise. It can be seen that the technology credit enhancement method for technology enterprises provided in the embodiments of this application has a relatively broad application prospect.

[0069] In some implementations, when obtaining the credit enhancement results, the financial institution may store, display or send the credit enhancement results to relevant terminals, etc. The manner in which the financial institution handles the credit enhancement results is not described in detail herein.

[0070] Optionally, the first category of data includes at least one of the following:

[0071] Financial data, corporate governance data, risk management data, competitiveness data, market position data, etc.

[0072] Similarly, in the application scenario of financial institutions granting credit to corporate customers mentioned above, in related technologies, financial institutions pay more attention to the cash flow and profitability of enterprises. However, for some small and medium-sized technology companies, they have high R&D investment and low cash flow in the short term, which makes it difficult for them to meet the credit threshold of financial institutions.

[0073] The second type of data includes technology flow data, so that the obtained credit enhancement level can effectively evaluate the technological innovation capabilities of science and technology companies and provide credit enhancement for their technology, emphasizing the organic combination of "technology flow" and "capital flow". This will help financial institutions to explore innovative companies with market potential and sustainable development.

[0074] Combined with the limitations on the first and second types of data in this implementation, in actual applications, the application of the credit rating model + credit enhancement rating model can enable financial institutions to adjust upward the credit rating of technology companies whose technological innovation capabilities meet the requirements before conducting the credit process for the companies, thereby helping to increase credit for these technology companies and boost their development.

[0075] Optionally, the technical flow data includes at least one of the following:

[0076] Equity investment availability data, R&D capability data, technological advantage data, intellectual property quality data, team stability data, market prospects data, etc.

[0077] Taking some examples, credit rating agencies can conduct quantitative analysis of the intellectual property structure, distribution, quantity distribution and so on of the evaluation object over time to obtain information on R&D capabilities, technological advantages, intellectual property quality and market prospects, etc.

[0078] Of course, in actual applications, technology flow data can also be obtained based on other scientific and technological innovation data, such as R&D investment, etc., which will not be illustrated one by one here.

[0079] In this embodiment, the technical flow data can better reflect the scientific and technological innovation capabilities of the evaluation object. Obtaining the credit enhancement level based on the technical flow data can enable the subsequent credit enhancement results to better characterize the scientific and technological innovation capabilities of the evaluation object, thereby improving the objectivity of the credit evaluation.

[0080] like Figure 2 As shown, in some embodiments, the technology credit enhancement method for a technology enterprise includes:

[0081] Step 201, obtaining first-category data and second-category data of the evaluation object, the first-category data and the second-category data are different types of data, and the second-category data includes technical flow data;

[0082] Step 202, inputting the second type of data into the credit enhancement rating model to obtain a credit enhancement rating;

[0083] Step 203, when the credit enhancement level meets the first preset condition, input the first type of data into the credit rating model to obtain the credit rating;

[0084] Step 204, correct the credit rating according to the credit enhancement rating to obtain the credit enhancement result of the evaluation object.

[0085] In this embodiment, step 201 may be the same as step 101, step 204 may be the same as step 104, and step 202 and step 203 may correspond to the above-mentioned step 103 and step 102, respectively. That is, the above-mentioned step 103 and step 102 may be performed successively.

[0086] That is to say, in this example, the credit enhancement level can be used as an entry condition for whether to enter the credit level of the evaluation object to be obtained.

[0087] In combination with some examples, the credit enhancement level may include N main levels such as A, B, C, D, ... (N is a positive integer), and the first preset condition may be higher than or equal to level D. When the credit enhancement level of the evaluation object is C, the financial institution can further obtain the credit rating of the evaluation object based on the credit rating model. In this way, it is helpful for credit rating agencies to provide targeted credit enhancement and credit granting to customers with better technical flow data performance, and to help the development of evaluation objects such as technology companies.

[0088] As a feasible implementation method, when the credit enhancement level does not meet the first preset condition, the credit rating agency may no longer obtain the credit rating of the evaluation object, thereby saving the consumption of related computing resources.

[0089] like Figure 3 As shown, in other implementations, the technology credit enhancement method for a technology enterprise includes:

[0090] Step 301, obtaining first-category data and second-category data of the evaluation object, the first-category data and the second-category data are different types of data, and the second-category data includes technical flow data;

[0091] Step 302, inputting the first type of data into a credit rating model to obtain a credit rating;

[0092] Step 303: when the credit rating meets the second preset condition, input the second type of data into the credit enhancement rating model to obtain the credit enhancement rating;

[0093] Step 304, correct the credit rating according to the credit enhancement rating to obtain the credit enhancement result of the evaluation object.

[0094] In this embodiment, step 301 may be the same as step 101, step 304 may be the same as step 104, and step 302 and step 303 may correspond to the above-mentioned step 102 and step 103, respectively. That is, the above-mentioned step 103 may be considered to be executed after step 102, and at the same time, the execution of step 103 may have corresponding triggering conditions.

[0095] Taking some examples, after obtaining a credit rating, a financial institution may have a process of determining whether the credit rating meets a second preset condition. When the credit rating meets the second preset condition, the financial institution may further input the second type of data into a credit enhancement rating model to obtain a credit enhancement rating.

[0096] In combination with some examples, the credit rating may include N main ratings such as A, B, C, D, ... (N is a positive integer), and the second preset condition may be that the credit rating is higher than or equal to rating D. When the information rating of the evaluation object is C, the financial institution may further obtain the credit enhancement rating of the evaluation object based on the credit enhancement rating model.

[0097] It can be seen that in the above example, the second preset condition may refer to the credit rating being greater than or equal to the rating threshold. Of course, as shown above, the credit rating may also be represented in other ways, and accordingly, the second preset condition may also be adjusted as needed.

[0098] In combination with the application scenario of financial institutions granting credit to corporate customers, in this implementation, the second preset condition can serve as a credit access condition to a certain extent. When the credit rating meets the preset rating condition, it can be considered that the enterprise meets the credit conditions.

[0099] The subsequent process of obtaining the credit enhancement rating based on the credit enhancement rating model and using the credit enhancement rating to correct the credit rating can be considered as the process of enhancing the credit of the enterprise.

[0100] In some embodiments, the second type of data may include technology flow data. Accordingly, when the enterprise's technological innovation capability is strong, it may be further enhanced, thereby helping the development of technology companies.

[0101] In some implementations, when the credit rating does not satisfy the second preset condition, a result of not granting credit may be generated.

[0102] Optionally, after correcting the credit rating according to the credit enhancement rating and obtaining the credit enhancement result of the evaluation object, the method further includes:

[0103] When the credit enhancement level meets the first preset condition, a first investment and financing strategy for the evaluation object is generated according to the credit enhancement result and the classified and layered investment and financing strategy.

[0104] In some examples, the first preset condition may refer to the credit enhancement level being greater than or equal to the level threshold, that is, when the credit enhancement level is greater than or equal to the level threshold, it can be determined that the credit enhancement level meets the first preset condition.

[0105] Combined with some application scenarios, financial institutions determine that the credit enhancement level is greater than or equal to the level threshold based on the company's technology flow data and credit enhancement rating model. In this case, financial institutions can determine that the company is a high-quality technology company and can invest in and finance the company.

[0106] In this embodiment, the classified and layered investment and financing strategies may include a correspondence between credit enhancement results and investment and financing strategies, that is, under different credit enhancement results, financial institutions may determine different investment and financing strategies.

[0107] To simplify the description, the credit enhancement result may also be referred to as the second credit rating below.

[0108] When the credit enhancement level meets the first preset condition, the determined investment and financing strategies can be collectively referred to as the first investment and financing strategy. However, the details of the first investment and financing strategy may be different under different credit enhancement levels.

[0109] Optionally, after inputting the second type of data into the credit enhancement rating model to obtain the credit enhancement grade, the method further includes:

[0110] When the credit enhancement level does not meet the first preset condition, a second investment and financing strategy for the evaluation object is generated.

[0111] In some examples, the first preset condition may also mean that the credit enhancement level is greater than or equal to the level threshold.

[0112] Similarly, combined with the application scenario of financial institutions conducting credit evaluation on enterprises, when the enterprise's credit enhancement level does not meet the first preset condition, the financial institution can judge the enterprise as an enterprise with low innovation ability, or a conventional enterprise, and then provide such enterprises with conventional investment and financing strategies, etc. These investment and financing strategies can be collectively referred to as the second investment and financing strategy.

[0113] For example, the second investment and financing strategy may refer to investment and financing of the enterprise based on the financial data of the enterprise. In this case, the process of determining the second investment and financing strategy may consider the credit rating of the enterprise alone without considering the credit enhancement rating.

[0114] For example, the second investment and financing strategy may also refer to providing non-financing products and services to enterprises.

[0115] In combination with the above embodiments, it can be seen that the technology enterprise technology enhancement method provided in the embodiments of the present application can flexibly and reasonably generate corresponding investment and financing strategies according to the credit rating, enhancement level and enhancement results. While meeting the needs for supporting technology enterprises, it can also take into account the service requirements for ordinary evaluation objects, effectively improving the scope of application of the technology enterprise technology enhancement method.

[0116] Combined with the application scenario of financial institutions granting credit to corporate customers mentioned above, the financing strategy can better provide financing for technology companies and help their development because it takes the credit enhancement level into consideration.

[0117] In some feasible implementations, after generating the financing strategy of the evaluation object, the financial institution may display, store or send the financing strategy to the terminal device of the relevant user.

[0118] Optionally, obtain the credit enhancement level of the evaluation object, including:

[0119] Obtaining technical flow data of the evaluation object within a preset time;

[0120] Perform big data analysis on the technology flow data within the preset time to obtain the continuous innovation capability and technology achievement transformation capability of the technology enterprise;

[0121] The credit enhancement grade is obtained based on the technology enterprise's continuous innovation capability and technology achievement transformation capability.

[0122] With some examples, the scientific and technological innovation attribute data of the evaluation object may include: the number of invention applications, the number and amount of intellectual property implementation licenses, the number of R&D personnel, academic qualifications and awards, etc.

[0123] Based on the scientific and technological innovation attribute data within the preset time, we can obtain data such as intellectual property rights, technology transformation capabilities, and R&D stability, which are used to reflect the company's scientific and technological innovation capabilities, that is, the technology flow data within the above-mentioned preset time.

[0124] To simplify the explanation, we will not give examples of how to obtain technology flow data within a preset time. By analyzing the big data of technology flow data within a preset time, we can obtain the continuous innovation capability and technology achievement transformation capability of technology enterprises. The process of determining relevant capabilities or indicators based on big data analysis technology can be achieved through existing technologies, which will not be elaborated here.

[0125] Based on the technology enterprise’s continuous innovation capability and ability to transform scientific and technological achievements, an enhanced credit rating can be obtained.

[0126] This embodiment uses big data analysis to obtain the continuous innovation capability and scientific and technological achievement transformation capability of science and technology enterprises, which helps to improve the rationality and universality of the technology flow data processing process. Based on the continuous innovation capability and scientific and technological achievement transformation capability of science and technology enterprises, it helps to obtain a credit enhancement level that can objectively reflect the innovation capability of the enterprise.

[0127] Take the application scenario of financial institutions granting credit to technology companies based on the innovation factor of intellectual property rights of technology companies as an example. Financial institutions can use technical means such as big data to evaluate the continuous innovation capabilities of enterprises with a series of quantitative indicators, organically combine the continuous innovation capabilities (technology flow) of big data technology companies and traditional credit evaluation (capital flow), and provide differentiated credit enhancement support to companies with strong innovation capabilities and market potential. This credit enhancement model can solve the dilemma of technology companies that are difficult to obtain financing from financial institutions based on financial indicators alone, and can be widely applied to technology companies of all sizes.

[0128] Combined with the above description, in the related art, due to the lack of evaluation tools, financial services for technology companies were mainly based on the experience judgment of credit personnel, which caused problems such as corporate moral risk and credit personnel operational risk. However, in this embodiment, the traditional experience judgment is transformed into big data driven decision-making, and data-driven and model calculation technology are used to evaluate the innovation ability of technology companies, which greatly makes up for the shortcomings of traditional evaluation methods and provides a powerful tool for accurate credit decision-making.

[0129] In some specific application examples, based on the application of the above-mentioned technology enterprise technology enhancement methods, financial institutions can shift from relying on static intellectual property pledges to dynamic intellectual property big data.

[0130] Specifically, in the relevant technologies, financial services for technology companies use intellectual property pledge as the main risk control method. However, intellectual property as collateral has the disadvantages of being isolated and static, difficult to assess its value, and difficult to liquidate. In this application example, the scientific and technological innovation evaluation sets up quantitative indicators around the big data of corporate intellectual property rights, which helps financial institutions discover technology companies with continuous innovation capabilities.

[0131] In some other specific application examples, before obtaining the first category data and the second category data of the evaluation object, the technology credit enhancement method for a science and technology enterprise may also include: determining a list of science and technology enterprises; and determining the evaluation object from the list of science and technology enterprises.

[0132] In some feasible implementations, financial institutions may determine corporate clients that are technology companies based on the identification standards for technology companies, and form a list of technology companies based on corporate clients that are technology companies according to preset cycles (such as quarterly cycles).

[0133] Financial institutions can sequentially identify all technology enterprises in the list of technology enterprises as evaluation objects. Alternatively, financial institutions can randomly identify some technology enterprises in the list of technology enterprises as evaluation objects, etc. This time, we will not provide an exhaustive explanation of the methods for determining evaluation objects.

[0134] Optionally, the credit enhancement level is obtained according to the technology enterprise's continuous innovation capability and technology achievement transformation capability, including:

[0135] The credit enhancement rating model is used to perform weighted sum calculation on the continuous innovation capability and the scientific and technological achievement transformation capability according to preset weights to obtain the credit enhancement grade.

[0136] In this embodiment, the continuous innovation capability and scientific and technological achievement transformation capability can be quantified, and the credit enhancement rating model performs weighted sum calculation on the quantified continuous innovation capability and scientific and technological achievement transformation capability, which helps to obtain the credit enhancement level of the evaluation object more conveniently and reliably.

[0137] In some implementations, the weights of continuous innovation capability and scientific and technological achievement transformation capability can be obtained in advance through mathematical statistics or logistic regression, Bayesian, machine learning and other methods.

[0138] For example, financial institutions can conduct statistics on historical data, taking the credit enhancement level (or the score corresponding to the credit enhancement level) of each evaluation object obtained through historical manual evaluation as the dependent variable, and the quantitative values ​​of the continuous innovation capability and scientific and technological achievement transformation capability corresponding to each evaluation object as independent variables, and perform logistic regression processing to obtain the weights of continuous innovation capability and scientific and technological achievement transformation capability.

[0139] In this implementation, the weights used in the credit enhancement rating model are obtained through mathematical statistics, logistic regression, Bayesian or machine learning-based methods, which helps to improve the rationality of the determined weights.

[0140] like Figure 4 As shown, the embodiment of the present application also provides a technology enterprise technology credit enhancement device, the device comprising:

[0141] An acquisition module 401 is used to acquire first-category data and second-category data of an evaluation object, where the first-category data and the second-category data are different types of data, and the second-category data includes technical flow data;

[0142] The first rating module 402 inputs the first type of data into the credit rating model to obtain a credit rating;

[0143] The second rating module 403 is used to input the second type of data into the credit enhancement rating model to obtain a credit enhancement grade;

[0144] The correction module 404 is used to correct the credit rating according to the credit enhancement rating to obtain the credit enhancement result of the evaluation object.

[0145] Optionally, the evaluation object includes at least one of the following:

[0146] Legal entities, non-legal entities, non-resident enterprises that have established institutions or places in China, technology enterprises among overseas enterprises, and natural persons related to technology enterprises.

[0147] Optionally, the technical flow data includes at least one of the following:

[0148] Equity investment availability data, R&D capability data, technological advantage data, intellectual property quality data, team stability data, market prospects data, etc.

[0149] Optionally, the technology enterprise technology credit enhancement device may also include:

[0150] The first generating module is used to generate a first investment and financing strategy for the evaluation object according to the credit enhancement result and the classified and layered investment and financing strategy when the credit enhancement level meets the first preset condition.

[0151] Optionally, the technology enterprise technology credit enhancement device may also include:

[0152] The second generation module is used to generate a second investment and financing strategy for the evaluation object when the credit enhancement level does not meet the first preset condition.

[0153] Optionally, the first preset condition includes that the credit enhancement level is greater than or equal to a level threshold.

[0154] Optionally, the acquisition module 401 includes:

[0155] A first acquisition unit, used to acquire the technical flow data of the evaluation object within a preset time;

[0156] The second acquisition unit is used to perform big data analysis on the technology flow data within the preset time to obtain the continuous innovation capability and scientific and technological achievement transformation capability of the technology enterprise;

[0157] The third acquisition unit is used to obtain the credit enhancement level according to the continuous innovation capability and scientific and technological achievement transformation capability of the science and technology enterprise.

[0158] Optionally, the third acquisition unit is specifically configured to:

[0159] The credit enhancement rating model is used to perform weighted sum calculation on the continuous innovation capability and the scientific and technological achievement transformation capability according to preset weights to obtain the credit enhancement grade.

[0160] It should be noted that the technology enhancement device for science and technology enterprises is a device corresponding to the above-mentioned technology enhancement method for science and technology enterprises. All implementation methods in the above-mentioned method embodiments are applicable to the embodiments of the device and can achieve the same technical effects.

[0161] Figure 5 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application is shown.

[0162] The electronic device may include a processor 501 and a memory 502 storing computer program instructions.

[0163] Specifically, the processor 501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0164] The memory 502 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 502 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 502 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 502 is a non-volatile solid-state memory.

[0165] In certain embodiments, the memory 502 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0166] The processor 501 implements any one of the technology enterprise technology enhancement methods in the above-mentioned embodiments by reading and executing computer program instructions stored in the memory 502.

[0167] In one example, the electronic device may further include a communication interface 503 and a bus 510. Figure 5 As shown, the processor 501, the memory 502, and the communication interface 503 are connected via a bus 510 and communicate with each other.

[0168] The communication interface 503 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0169] Bus 510 includes hardware, software or both, and the parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 510 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0170] In addition, in combination with the technology enterprise technology credit enhancement method in the above embodiment, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the technology enterprise technology credit enhancement methods in the above embodiment is implemented.

[0171] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0172] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0173] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0174] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box 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, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0175] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A technology credit enhancement method for a technology enterprise, characterized in that: Using two models, a credit rating model and a credit enhancement rating model, the method includes: Acquire first-category data and second-category data of the evaluation object, where the first-category data and the second-category data are different types of data, and the second-category data includes technical flow data; Inputting the first type of data into a credit rating model to obtain a credit rating; inputting the second type of data into a credit enhancement rating model to obtain a credit enhancement grade; the credit enhancement rating model is pre-set and matches the second type of data; Modifying the credit rating according to the credit enhancement rating to obtain a credit enhancement result of the evaluation object; The step of inputting the first type of data into a credit rating model to obtain a credit rating includes: In the case where the credit enhancement level satisfies a first preset condition, inputting the first type of data into the credit rating model to obtain the credit rating; the first preset condition includes that the credit enhancement level is greater than or equal to a level threshold; Get the credit enhancement level of the evaluation object, including: Obtaining technical flow data of the evaluation object within a preset time; Perform big data analysis on the technology flow data within the preset time to obtain the continuous innovation capability and technology achievement transformation capability of the technology enterprise; The credit enhancement level is obtained based on the technology enterprise's continuous innovation capability and technology achievement transformation capability; The credit enhancement level is obtained based on the technology enterprise's continuous innovation capability and technology achievement transformation capability, including: The credit enhancement rating model is used to calculate the weighted sum of the continuous innovation capability and the scientific and technological achievement transformation capability according to preset weights to obtain the credit enhancement grade; After inputting the second type of data into the credit enhancement rating model to obtain the credit enhancement grade, the method further includes: In the case where the credit enhancement level meets the first preset condition, generating a first investment and financing strategy for the evaluation object according to the credit enhancement result and the classified and layered investment and financing strategy; the classified and layered investment and financing strategy includes a correspondence between the credit enhancement result and the investment and financing strategy; When the credit enhancement level does not satisfy the first preset condition, a second investment and financing strategy for the evaluation object is generated.

2. The method according to claim 1, characterized in that The evaluation object includes at least one of the following: Legal entities, non-legal entities, non-resident enterprises that have established institutions or places in China, technology enterprises among overseas enterprises, and natural persons related to the aforementioned technology enterprises.

3. The method according to claim 1, characterized in that The technical flow data includes at least one of the following: Equity investment availability data, R&D capability data, technological advantage data, intellectual property quality data, team stability data, and market prospects data.

4. A technology credit enhancement device for a technology enterprise, characterized in that: For adopting two models, a credit rating model and a credit enhancement rating model, the device comprises: An acquisition module, used to acquire first-category data and second-category data of an evaluation object, wherein the first-category data and the second-category data are different types of data, and the second-category data includes technical flow data; A first rating module, inputting the first type of data into a credit rating model to obtain a credit rating; A second rating module, used for inputting the second type of data into a credit enhancement rating model to obtain a credit enhancement grade; the credit enhancement rating model is pre-set and matches the second type of data; A correction module, used to correct the credit rating according to the credit enhancement rating to obtain a credit enhancement result of the evaluation object; The first rating module is specifically used for: In the case where the credit enhancement level satisfies a first preset condition, inputting the first type of data into the credit rating model to obtain the credit rating; the first preset condition includes that the credit enhancement level is greater than or equal to a level threshold; The second rating module comprises: A first acquisition unit, used to acquire the technical flow data of the evaluation object within a preset time; The second acquisition unit is used to perform big data analysis on the technology flow data within the preset time to obtain the continuous innovation capability and scientific and technological achievement transformation capability of the technology enterprise; A third acquisition unit is used to obtain the credit enhancement level according to the continuous innovation capability and scientific and technological achievement transformation capability of the science and technology enterprise; The third acquisition unit is specifically used for: The credit enhancement rating model is used to calculate the weighted sum of the continuous innovation capability and the scientific and technological achievement transformation capability according to preset weights to obtain the credit enhancement grade; The device also includes: A first generating module is used to generate a first investment and financing strategy for the evaluation object according to the credit enhancement result and the classified and layered investment and financing strategy when the credit enhancement level meets the first preset condition; the classified and layered investment and financing strategy includes a corresponding relationship between the credit enhancement result and the investment and financing strategy; The second generating module is used to generate a second investment and financing strategy for the evaluation object when the credit enhancement level does not meet the first preset condition.

5. The device according to claim 4, characterized in that The evaluation object includes at least one of the following: Legal entities, non-legal entities, non-resident enterprises that have established institutions or places in China, technology enterprises among overseas enterprises, and natural persons related to the aforementioned technology enterprises.

6. The device according to claim 4, characterized in that The technical flow data includes at least one of the following: Equity investment availability data, R&D capability data, technological advantage data, intellectual property quality data, team stability data, and market prospects data.

7. An electronic device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the technology enterprise technology enhancement method as described in any one of claims 1-3 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the technology enterprise technology enhancement method as described in any one of claims 1 to 3.

9. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the technology enhancement method for a technology enterprise as described in any one of claims 1 to 3.

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