Credit assessment methods, devices, computer equipment and storage media

Abstract

This invention relates to a credit assessment method, apparatus, computer equipment, and storage medium. The method includes: obtaining an initial implicit score based on the original data of a target entity; obtaining an industry coefficient based on the industry prosperity score and the industry entity qualification dispersion coefficient of the target entity's industry; and obtaining a subject model implicit score based on the initial implicit score and the industry coefficient; wherein the subject model implicit score is used to indicate the credit assessment result of the target entity. This invention can make the assessment results more accurate.

Description

Technical Field

[0001] This invention relates to the field of data processing, and more particularly to a credit assessment method, apparatus, computer equipment, and storage medium. Background Technology

[0002] In financial institutions or other entities with risk management, credit assessment is usually conducted, and the traditional method in credit assessment systems is to use manual rating.

[0003] However, manual credit assessment relies heavily on human experience and focuses on manually setting scoring rules. Therefore, when faced with complex and large amounts of financial data, it generally suffers from systemic defects such as low accuracy, poor adaptability, insufficient robustness, and low efficiency.

[0004] It is clear that existing credit rating methods are insufficient to meet the needs. Summary of the Invention

[0005] To solve the above-mentioned technical problems, or at least partially solve them, the present invention provides a credit assessment method, apparatus, computer equipment, and storage medium.

[0006] In a first aspect, the present invention provides a credit assessment method, the method comprising: Based on the target subject's original data, obtain the initial implicit score; The industry coefficient is obtained based on the industry prosperity score of the target entity's industry and the dispersion coefficient of the industry entity's qualifications. Based on the initial implicit score and the industry coefficient, the implicit score of the main model is obtained; The implicit score of the subject model is used to indicate the credit assessment result of the target subject.

[0007] Optionally, after obtaining the initial implicit score based on the target subject's original subject data, the method further includes: Obtain the main adjustment score. Based on the implicit score of the subject model and the subject adjustment score, obtain the adjusted implicit score; The step of obtaining the implicit score of the main model based on the initial implicit score and the industry coefficient further includes: The adjusted implicit score is used as the initial implicit score, and the implicit score of the main model is obtained based on the initial implicit score and the industry coefficient.

[0008] Optionally, obtaining the initial implicit score based on the target subject's original subject data includes: Obtain the original data of the target entity; The original data of the subject is filtered to obtain indicator data, which includes standard scores for financial indicators and standard scores for operational indicators. Acquire financial weight and operational weight; The model's raw score is obtained based on the standard scores of the financial indicators and the financial weights, as well as the standard scores of the operating indicators and the operating weights. The original scores of the model are mapped to the initial implicit scores.

[0009] Optionally, obtaining the industry coefficient based on the industry prosperity score and the industry entity qualification dispersion coefficient of the target entity's industry includes: Obtain the actual value of the economic climate; Based on the actual economic climate value, obtain the economic climate forecast value; After standardizing the predicted business climate value, a standard business climate value is obtained, and the standard business climate value is used as the industry business climate score; The coefficient of variation of the subject's qualifications is obtained based on the maximum weighted implied score of the industry subject, the minimum implied score of the industry subject, the average weighted implied score of the industry subject, and the number of industry sample subjects. The industry coefficient is obtained based on the industry prosperity score and the entity qualification dispersion coefficient.

[0010] Optionally, the actual value of the economic climate is obtained in the following manner:

[0011]

[0012]

[0013]

[0014] in, Based on the first principal component's first economic sentiment result, This represents the second principal component's second economic activity result within the current assessment period. Let m be the coefficients of the first principal components of the financial indicators. Let m be the second principal component coefficients of the financial indicators. Let m be the standardized results of the financial indicators within the current evaluation period. This represents the actual economic sentiment level for the current assessment period. As the first principal component contribution, Contribution to the second principal component This is a standardized result of the first economic climate index. This is a standardized result of the second economic climate index. The first principal component and the second principal component are obtained based on the original data of the target subject.

[0015] Optionally, obtaining the predicted economic climate value based on the actual economic climate value includes: Based on the actual economic climate value during the T-assessment period, obtain the factor coefficients for the T-assessment period. Based on the significant principal component screening threshold, forward-looking operating factors within the T+3 evaluation period are screened from effective operating indicators. Based on the factor coefficients within the T assessment period and the forward-looking business factors within the T+3 assessment period, the predicted business climate value for the T+3 assessment period is obtained.

[0016] Optionally, the factor coefficients for the evaluation period T are obtained based on the actual economic climate value within the evaluation period T, in the following manner:

[0017]

[0018] The predicted business climate value for the T+3 assessment period is obtained based on the factor coefficients within the T assessment period and the forward-looking business factors within the T+3 assessment period, in the following manner:

[0019]

[0020] in, T represents the actual economic sentiment value during the assessment period. For the intercept term, T represents the factor coefficients within the evaluation period. ... Forward-looking operational factors within the evaluation period T. This represents the predicted economic climate value for the T+3 assessment period. Forward-looking operating factors within the T+3 assessment period.

[0021] Secondly, a credit assessment apparatus is provided, which applies the method described above, the apparatus comprising: The implicit scoring model is used to obtain an initial implicit score based on the original data of the target subject. The business climate model is used to obtain industry coefficients based on the business climate score of the target entity's industry and the dispersion coefficient of the entity's qualifications. An evaluation unit is used to obtain the implicit score of the main model based on the initial implicit score and the industry coefficient; The implicit score of the subject model is used to indicate the credit assessment result of the target subject.

[0022] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as described in any of the preceding claims.

[0023] Fourthly, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the preceding claims.

[0024] This invention provides a solution. Attached Figure Description

[0025] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 The diagram shown illustrates the application environment of the credit assessment method according to an embodiment of the present invention. Figure 2 The diagram shown is a flowchart of the credit assessment method according to an embodiment of the present invention. Figure 3 The diagram shown is a structural block diagram of a credit assessment device according to an embodiment of the present invention. Figure 4 The diagram shown is an internal structural diagram of a computer device in an embodiment of the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Figure 1 This is a diagram illustrating the application environment of a credit assessment method according to one embodiment. (Refer to...) Figure 1This credit assessment method is applied to a credit assessment system. The credit assessment system includes a terminal 110 and a server 120. The terminal 110 and server 120 are connected via a network. The terminal 110 can be a desktop terminal or a mobile terminal; a mobile terminal can be at least one of a mobile phone, tablet, or laptop. The server 120 can be a standalone server or a server cluster consisting of multiple servers.

[0030] The credit assessment method of this invention can be used for credit assessment in the industrial and financial fields.

[0031] like Figure 2 As shown, in one embodiment, a credit assessment method is provided. This embodiment mainly applies this method to the above-mentioned... Figure 1 Let's take terminal 110 or server 120 as an example for illustration. (Refer to...) Figure 2 The credit assessment method specifically includes: Step 210: Obtain the initial implicit score based on the original subject data of the target subject; Step 220: Obtain the industry coefficient based on the industry prosperity score of the target entity's industry and the industry entity qualification dispersion coefficient; Step 230: Obtain the implicit score of the main model based on the initial implicit score and the industry coefficient; The implicit score of the subject model is used to indicate the credit assessment result of the target subject.

[0032] The implicit scoring of the main model is performed in the following way:

[0033]

[0034] in, The implicit score for the main model. For the initial implicit score, This is the industry coefficient.

[0035] In this embodiment of the invention, an initial implicit score is obtained based on the original data of the target entity; an industry coefficient is obtained based on the industry prosperity score and the industry entity qualification dispersion coefficient of the target entity's industry; and an entity model implicit score is obtained based on the initial implicit score and the industry coefficient. The entity model implicit score is used to indicate the credit assessment result of the target entity. In the method of this embodiment, the industry prosperity score and the target entity's implicit score are fully considered when obtaining the credit assessment result. This ensures that credit assessment is not merely a single-entity assessment but takes into account the impact of the entire industry, making the assessment result more accurate. Furthermore, using the prosperity score in the credit assessment can eliminate differences between industries and achieve direct comparability between different industries.

[0036] In this embodiment of the invention, an indicator pool can be established by comprehensively considering multiple aspects such as company size, operational efficiency, profitability, and cash flow management. Specific indicators may include gross profit margin, return on net assets, net profit margin, gross profit, cash received from sales of goods and services, and historical data of quarterly return on total assets.

[0037] In this embodiment of the invention, the original data of the target subject is filtered out from the index pool data.

[0038] The original data of the target entity is filtered out, including: Sort the indicator pool data from largest to smallest; Obtain the correlation coefficients between the data in the indicator pool; Based on the correlation coefficient and indicator coverage, the indicator pool data is filtered to extract the original data of the target subject.

[0039] In one embodiment of the present invention, to eliminate the impact of differences in data size, such as total assets measured in hundreds of millions of yuan, a debt-to-asset ratio as a percentage, or the inability to regress using the original data, the indicator pool data can be converted into a sorted format for processing. All indicators are sorted in descending order, meaning the larger the indicator value, the higher the ranking; for example, the indicator with the largest total assets is ranked first.

[0040] In one embodiment of the present invention, it can be set that a correlation coefficient with an absolute value greater than or equal to 0.5 is selected; a correlation coefficient with an absolute value less than 0.5 but with an indicator coverage capability greater than or equal to a preset value is also selected.

[0041] In this embodiment of the invention, after obtaining the initial implicit score based on the original subject data of the target subject, the method further includes: Obtain the main adjustment score. Based on the implicit score of the subject model and the subject adjustment score, obtain the adjusted implicit score; The step of obtaining the implicit score of the main model based on the initial implicit score and the industry coefficient further includes: The adjusted implicit score is used as the initial implicit score, and the implicit score of the main model is obtained based on the initial implicit score and the industry coefficient.

[0042] The entity adjustment score refers to a supplementary item that, based on the quantitative scoring results, incorporates qualitative factors such as the entity's unique business characteristics, external support, risk events, industry differences, policy impacts, financial anomalies, and public opinion information to reasonably adjust the initial score / rating of the model. This adjustment item can improve rating accuracy, align with actual business operations, and compensate for non-financial information that the quantitative model cannot cover, resulting in a more objective and prudent final rating.

[0043] In this embodiment of the invention, obtaining the initial implicit score based on the original subject data of the target subject includes: Obtain the original data of the target entity; The original data of the subject is filtered to obtain indicator data, which includes standard scores for financial indicators and standard scores for operational indicators. Acquire financial weight and operational weight; The model's raw score is obtained based on the standard scores of the financial indicators and the financial weights, as well as the standard scores of the operating indicators and the operating weights. The original scores of the model are mapped to the initial implicit scores.

[0044] In this embodiment of the invention, obtaining the industry coefficient based on the industry prosperity score of the target entity's industry and the industry entity qualification dispersion coefficient includes: Obtain the actual value of the economic climate; Based on the actual economic climate value, obtain the economic climate forecast value; After standardizing the predicted business climate value, a standard business climate value is obtained, and the standard business climate value is used as the industry business climate score; The coefficient of variation of the subject's qualifications is obtained based on the maximum weighted implied score of the industry subject, the minimum implied score of the industry subject, the average weighted implied score of the industry subject, and the number of industry sample subjects. The industry coefficient is obtained based on the industry prosperity score and the entity qualification dispersion coefficient.

[0045] The coefficient of variation for the main qualification is determined as follows: The coefficient of variation of the main qualification =

[0046] Industry coefficients are calculated as follows:

[0047]

[0048] Where C is the industry coefficient, A is the prosperity score, and B is the entity qualification dispersion coefficient.

[0049] When conducting credit assessments in industries, finance, and other fields, industry prosperity is one of the important indicators. Therefore, in this embodiment of the invention, prosperity is taken into account during the assessment, and a prosperity model is constructed to obtain the actual prosperity value, the predicted prosperity value, and the standard prosperity value.

[0050] In the business climate model, this invention reclassifies industries into 23 major business climate categories based on existing primary and secondary classifications and considering upstream and downstream conditions and business models. For example, the three secondary sub-industries of electricity, water, and gas / heat supply, although within the same primary industry, have weak business correlations and are therefore split into three major categories for separate business climate calculations. The eight secondary sub-industries of public transportation, rail transit, aviation, shipping, logistics, ports, airports, and highways, although within different primary industries, have strong business correlations and are therefore integrated into the "Transportation" major category for unified calculation. The three secondary sub-industries of auto parts, complete vehicles, and auto services, within the same primary industry and with strong business correlations, are directly calculated using the primary industry "Automotive" as the business climate category.

[0051] After classifying the industries as described above, this invention can obtain the maximum weighted implicit score, minimum implicit score, average weighted implicit score, and number of sample entities in the industry to which the target entity belongs.

[0052] In this embodiment of the invention, the actual value of the economic climate is obtained in the following manner:

[0053]

[0054]

[0055]

[0056] in, Based on the first principal component's first economic sentiment result, This represents the second principal component's second economic activity result within the current assessment period. Let m be the coefficients of the first principal components of the financial indicators. Let m be the second principal component coefficients of the financial indicators. Let m be the standardized results of the financial indicators within the current evaluation period. This represents the actual economic sentiment level for the current assessment period. As the first principal component contribution, Contribution to the second principal component This is a standardized result of the first economic climate index. This is a standardized result of the second economic climate index. The first principal component and the second principal component are obtained based on the original data of the target subject.

[0057] When obtaining actual economic indicators, principal component analysis is mainly used. This involves orthogonally transforming a set of potentially correlated variables into a set of linearly uncorrelated variables. The transformed set of variables is called principal components. The "dimensionality reduction technique" of principal component analysis can reduce multiple variables to a few principal components (comprehensive variables). These principal components can reflect most of the information of the original variables, and they are usually represented as a linear combination of the original variables.

[0058] Principal component coefficients represent the weights or loadings of the original variables on each principal component. Each principal component is a linear combination of the original variables, and the principal component coefficients describe these linear combinations. Principal component coefficients tell us which variables play a significant role in the direction of the principal components and their positive or negative correlations. Typically, the total contribution of the principal components used should exceed 80%. For example, the first two principal components of the financial indicators for the steel industry should contribute over 80%.

[0059] In this embodiment of the invention, obtaining the predicted economic climate value based on the actual economic climate value includes: Based on the actual economic climate value during the T-assessment period, obtain the factor coefficients for the T-assessment period. Based on the significant principal component screening threshold, forward-looking operating factors within the T+3 evaluation period are screened from effective operating indicators. Based on the factor coefficients within the T assessment period and the forward-looking business factors within the T+3 assessment period, the predicted business climate value for the T+3 assessment period is obtained.

[0060] Among the effective operating indicators, those with significant principal component scores below the significant principal component screening threshold are included, while those with scores greater than or equal to the significant principal component screening threshold are excluded. The significant principal component screening threshold can be set to 0.1.

[0061] In this embodiment of the invention, the factor coefficients for the evaluation period T are obtained based on the actual economic climate value within the evaluation period T, in the following manner:

[0062]

[0063] The predicted business climate value for the T+3 assessment period is obtained based on the factor coefficients within the T assessment period and the forward-looking business factors within the T+3 assessment period, in the following manner:

[0064]

[0065] in, T represents the actual economic sentiment value during the assessment period. For the intercept term, T represents the factor coefficients within the evaluation period. ... Forward-looking operational factors within the evaluation period T. This represents the predicted economic climate value for the T+3 assessment period. Forward-looking operating factors within the T+3 assessment period.

[0066] Actual business climate values ​​reflect the financial performance of each major category. Forecast values ​​represent the general trend of future business climate. Both actual and forecast values ​​are specific to a particular major category, making direct comparisons between different categories impossible. Therefore, standard business climate values ​​are needed to eliminate industry-level differences and make results comparable across categories.

[0067] Based on the economic climate forecast, the maximum and minimum values ​​of the weighted rating are used as benchmarks to map the economic climate forecast values ​​of each major category to the major category benchmarks. Then, the maximum-minimum standardization method is used to standardize the full forecast values ​​of all major categories to 0-100.

[0068] The method of this invention makes the assessment results more accurate. At the same time, by using the economic climate results in credit assessment, the differences between industries can be eliminated, and direct comparability between different industries can be achieved.

[0069] The aforementioned credit assessment method utilizes the unique technical features of credit assessment methods for derivation, achieving the beneficial effect of solving the technical problems raised in the background section.

[0070] The present invention also provides a credit assessment apparatus, which applies the method described in any of the preceding claims, such as... Figure 3 As shown, the device includes: Implicit scoring model 310 is used to obtain an initial implicit score based on the original subject data of the target subject; The business climate model 320 is used to obtain industry coefficients based on the business climate score of the industry in which the target entity is located and the dispersion coefficient of the industry entity's qualifications. Evaluation unit 330 is used to obtain the implicit score of the main model based on the initial implicit score and the industry coefficient; The implicit score of the subject model is used to indicate the credit assessment result of the target subject.

[0071] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the following method: obtaining an initial implicit score based on the original subject data of the target subject; obtaining an industry coefficient based on the industry prosperity score and the industry subject qualification dispersion coefficient of the industry in which the target subject is located; obtaining a subject model implicit score based on the initial implicit score and the industry coefficient; wherein the subject model implicit score is used to indicate the credit assessment result of the target subject.

[0072] This invention also provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the following method: obtaining an initial implicit score based on the original subject data of the target subject; obtaining an industry coefficient based on the industry prosperity score and the industry subject qualification dispersion coefficient of the industry in which the target subject is located; obtaining a subject model implicit score based on the initial implicit score and the industry coefficient; wherein the subject model implicit score is used to indicate the credit assessment result of the target subject.

[0073] The aforementioned credit assessment method achieves the beneficial effect of solving the technical problems raised in the background section.

[0074] Figure 2 This is a flowchart illustrating a credit assessment method in one embodiment. It should be understood that, although... Figure 2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0075] Figure 4 An internal structural diagram of a computer device in one embodiment is shown. Specifically, this computer device may be... Figure 1 Terminal 110 or server 120 in the middle. For example... Figure 4As shown, the computer device includes a processor, memory, network interface, input device, and display screen connected via a system bus. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and may also store computer programs. When executed by the processor, these computer programs enable the processor to implement a credit assessment method. The internal memory may also store computer programs, which, when executed by the processor, enable the processor to perform the credit assessment method. The display screen can be an LCD screen or an e-ink screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0076] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0077] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0078] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0079] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A credit assessment method, characterized in that, The method includes: Based on the target subject's original data, obtain the initial implicit score; The industry coefficient is obtained based on the industry prosperity score of the target entity's industry and the dispersion coefficient of the industry entity's qualifications. Based on the initial implicit score and the industry coefficient, the implicit score of the main model is obtained; The implicit score of the subject model is used to indicate the credit assessment result of the target subject.

2. The method according to claim 1, characterized in that, After obtaining the initial implicit score based on the target subject's original subject data, the method further includes: Obtain the main adjustment score. Based on the implicit score of the subject model and the subject adjustment score, obtain the adjusted implicit score; The step of obtaining the implicit score of the main model based on the initial implicit score and the industry coefficient further includes: The adjusted implicit score is used as the initial implicit score, and the implicit score of the main model is obtained based on the initial implicit score and the industry coefficient.

3. The method according to claim 1, characterized in that, The process of obtaining an initial implicit score based on the target subject's original data includes: Obtain the original data of the target entity; The original data of the subject is filtered to obtain indicator data, which includes standard scores for financial indicators and standard scores for operational indicators. Acquire financial weight and operational weight; The model's raw score is obtained based on the standard scores of the financial indicators and the financial weights, as well as the standard scores of the operating indicators and the operating weights. The original scores of the model are mapped to the initial implicit scores.

4. The method according to claim 1, characterized in that, The process of obtaining the industry coefficient based on the industry prosperity score and the industry entity qualification dispersion coefficient of the target entity's industry includes: Obtain the actual value of the economic climate; Based on the actual economic climate value, obtain the economic climate forecast value; After standardizing the predicted business climate value, a standard business climate value is obtained, and the standard business climate value is used as the industry business climate score; The coefficient of variation of the subject's qualifications is obtained based on the maximum weighted implied score of the industry subject, the minimum implied score of the industry subject, the average weighted implied score of the industry subject, and the number of industry sample subjects. The industry coefficient is obtained based on the industry prosperity score and the entity qualification dispersion coefficient.

5. The method according to claim 4, characterized in that, The actual value of the economic climate index is obtained in the following manner: ， ， ； in, Based on the first principal component's first economic sentiment result, This represents the second principal component's second economic activity result within the current assessment period. Let m be the coefficients of the first principal components of the financial indicators. Let m be the second principal component coefficients of the financial indicators. Let m be the standardized results of the financial indicators within the current evaluation period. This represents the actual economic sentiment level for the current assessment period. As the first principal component contribution, Contribution to the second principal component This is a standardized result of the first economic climate index. This is a standardized result of the second economic climate index. The first principal component and the second principal component are obtained based on the original data of the target subject.

6. The method according to claim 4, characterized in that, The step of obtaining the predicted economic climate value based on the actual economic climate value includes: Based on the actual economic climate value during the T-assessment period, obtain the factor coefficients for the T-assessment period. Based on the significant principal component screening threshold, forward-looking operating factors within the T+3 evaluation period are screened from effective operating indicators. Based on the factor coefficients within the T assessment period and the forward-looking business factors within the T+3 assessment period, the predicted business climate value for the T+3 assessment period is obtained.

7. The method according to claim 6, characterized in that, The factor coefficients for the evaluation period T are obtained based on the actual economic climate value within that evaluation period, in the following manner: ； The predicted business climate value for the T+3 assessment period is obtained based on the factor coefficients within the T assessment period and the forward-looking business factors within the T+3 assessment period, in the following manner: ； in, T represents the actual economic sentiment value during the assessment period. For the intercept term, T represents the factor coefficients within the evaluation period. ... Forward-looking operational factors within the evaluation period T. This represents the predicted economic climate value for the T+3 assessment period. Forward-looking operating factors within the T+3 assessment period.

8. A credit assessment device, characterized in that, The apparatus comprising the method of any one of claims 1 to 7, wherein the method comprises: The implicit scoring model is used to obtain an initial implicit score based on the original data of the target subject. The business climate model is used to obtain industry coefficients based on the business climate score of the target entity's industry and the dispersion coefficient of the entity's qualifications. An evaluation unit is used to obtain the implicit score of the main model based on the initial implicit score and the industry coefficient; The implicit score of the subject model is used to indicate the credit assessment result of the target subject.

9. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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