An individual business credit evaluation method and system

Abstract

The application provides an individual business credit evaluation method and system, and belongs to the technical field of credit evaluation.The application collects individual business basic credit, operation, law-abiding, credit and contract-keeping and comprehensive evaluation information through multi-channel compliance, designs quantitative scoring rules according to four types of index attributes, namely positive, negative, moderate and category, combines dynamic weight configuration and credit repair and post-tightening mechanism, and outputs authoritative credit evaluation results; meanwhile, whole-process data security guarantee measures are embedded to ensure legal use of information. The application can be directly applied to credit evaluation activities of subjects such as supervision departments and financial institutions, and provides standardized technical support for flexible supervision, inclusive finance and enterprise relief, and effectively improves the scientificity, rationality and operability of individual business credit evaluation.

Description

Technical Field

[0001] This invention relates to the field of credit rating technology, and in particular to a method and system for credit rating of individual business owners. Background Technology

[0002] Individual business owners are the most active component of the private economy, playing a crucial supporting role in improving people's livelihoods, promoting employment, and enhancing economic resilience. Credit rating, as the core link between individual business owners and regulatory and financial services, directly impacts regulatory effectiveness and the efficiency of market resource allocation due to its degree of standardization.

[0003] The current field of credit evaluation for individual businesses has significant shortcomings: First, there is a lack of unified standards. Different evaluation entities (such as local regulatory departments and financial institutions) set their own indicators, and some indicators do not cover the core elements required by regulations (such as integrity and compliance information and comprehensive evaluation information), resulting in a lack of comparability and authority in the evaluation results, and making it impossible to reuse them across departments and scenarios. Second, the indicators are not sufficiently implementable. Although the standards clearly define the framework of basic and special indicators, they do not provide specific data collection paths, scoring rules, and weighting schemes, making it difficult for most evaluation entities to translate the standard requirements into an operational process. Third, data security risks are prominent. Credit information for individual businesses covers sensitive content, and existing evaluation activities have problems such as non-compliant data collection channels, unencrypted data storage, and exceeding the scope of use, violating the standard's "security" requirements. Fourth, industry adaptability is poor. Special indicators have not been refined according to the characteristics of the individual businesses' industries (such as catering, retail, and manufacturing), resulting in evaluation results that cannot truly reflect industry-specific credit risks (such as food safety compliance in the catering industry and consumer complaint handling capabilities in the retail industry).

[0004] Existing regulations provide a unified framework for credit evaluation of individual businesses, but there is currently a lack of technical implementation paths to transform the "principled requirements" of the standard into "practical solutions," which makes it difficult to fully realize the guiding value of the standard. There is an urgent need for a set of credit evaluation technical solutions that meet the requirements of the standard and can be directly implemented. Summary of the Invention

[0005] To address the above technical problems, this invention provides a method for evaluating the credit of individual business owners, resolving issues such as the lack of unified standards, disordered indicator settings, non-standard implementation procedures, and lack of data security in existing individual business owner credit evaluation systems.

[0006] The technical solution of this invention is: A method for implementing credit evaluation for individual business owners includes the following steps: Step 1: Construct an evaluation index system: The index system includes basic indicators and special indicators, with the basic indicators accounting for no less than 40% of the weight. The basic indicators cover basic credit information indicators, business information indicators, law-abiding information indicators, integrity and contract compliance information indicators, and comprehensive evaluation information indicators, and fully comply with the prescribed indicator requirements. The special indicators are set in combination with the characteristics of the industry in which the individual business is located or specific application scenarios, and each indicator is clearly marked with positive, negative, moderate or category attributes. Step 2: Compliant Data Collection and Processing: Collect individual business credit information required by the indicator system through compliant channels such as departmental regulatory platforms, public service institutions, and industry-specific platforms; clean and deduplicate the collected data, standardize and convert it, and handle missing values; unify the statistical period and data format to ensure that the data complies with the prescribed coding standards; Step 3: Configure indicator weights: Using the analytic hierarchy process (AHP) combined with industry expert scoring, weights are configured for basic indicators and special indicators. Within the basic indicators, weights are allocated according to the order of "compliance information > integrity and contract compliance information > business information > comprehensive evaluation information > basic credit information". Within the special indicators, high-risk industry indicators are assigned the highest weights. Adjustment explanations are retained after weight adjustments. Step 4: Calculate the credit score: Calculate the score for each indicator based on its attributes and the corresponding scoring rules. Positive indicator score = Min(Actual value / Industry benchmark, 1) × indicator weight; negative indicator score = Max(1 - Actual value / Industry warning value, 0) × indicator weight × (1 - tightening coefficient); moderate indicator score = indicator weight × [1 - Min(deviation, 1)]. Category indicators are scored according to the "Category-Score" mapping table. Sum the results to obtain the total credit score, and classify the credit rating from AAA to C based on a total score of 0-100. Step 5: Output evaluation results: Output the total credit score, credit rating, score details and reasons for deductions in the form of visual reports, electronic reports or data interfaces. Basic indicators are updated quarterly, special indicators are updated dynamically according to the industry, and major credit events are updated in real time. Step 6, Full-process security guarantee: Data collection adopts HTTPS encryption and dual authentication, storage adopts SM4 encryption, use adopts hierarchical access control, and is subject to compliance review before release. Operation logs are retained for no less than 3 years to ensure compliance with the prescribed security requirements.

[0007] Furthermore, The basic credit information indicators mentioned in step 1 include the characteristics of the business entity and the characteristics of the operator; the characteristics of the business entity include the organizational structure, whether it operates online, the classification results according to the prescribed "famous, special, excellent and new" and "survival-type / growth-type / development-type", and whether it includes a specific group; the characteristics of the operator include education, professional title, professional qualification information, and whether it is a college graduate / veteran / disabled person / unemployed re-employed person.

[0008] The tightening coefficient mentioned in step 4 is determined according to the following rules: if credit constraints or administrative penalties occur again within 1 year after credit repair, the tightening coefficient is 50%; if they occur again within 1-2 years after repair, the tightening coefficient is 30%; if they occur again more than 2 years after repair, the tightening coefficient is 20%, which meets the requirements.

[0009] The industry benchmark, industry warning value, and appropriate range mentioned in step 4 are all taken from official data released by the market supervision department; when there is no official data, the results of joint calculation by industry association statistics and leading credit rating agencies are used.

[0010] The credit rating criteria mentioned in step 4 are as follows: AAA (90-100 points), AA (80-89 points), A (70-79 points), B (60-69 points), and C (<60 points).

[0011] Step 1 supports adding or removing third-level indicators of the basic indicators based on industry characteristics. When adding or removing indicators, industry experts must conduct a review and retain the review opinions. After the addition or removal, the basic indicators must still meet the requirements of "the weight ratio of the basic indicators is ≥40%" and other regulations.

[0012] Furthermore, the present invention also provides an evaluation system for implementing any of the above methods, comprising: Indicator System Construction Unit: Used to execute step 1, construct an evaluation indicator system that includes basic indicators and special indicators, label indicator attributes, and ensure that the weight of basic indicators is ≥40%; Data acquisition and processing unit: used to perform step 2, collect data through compliant channels, and complete cleaning, standardization and missing value processing.

[0013] Weight Configuration Unit: Used to execute step 3, which uses a combination of analytic hierarchy process and expert scoring to configure indicator weights and retains adjustment instructions.

[0014] Credit scoring unit: used to perform step 4, calculate individual scores and total scores according to indicator attributes, classify credit levels, and apply stricter rules after credit repair.

[0015] Result output unit: used to execute step 5, output multi-form evaluation results, and update them at a specified frequency.

[0016] Security Assurance Unit: Used to execute step 6, realize security control of the entire process of data collection, storage, use and release, and retain operation logs for ≥3 years.

[0017] Furthermore, The security unit includes an encrypted transmission module (HTTPS), a dual authentication module (API Key + Token), a national cryptographic encryption storage module (SM4), a permission level module (three levels of permissions), a compliance audit module, and a log retention module.

[0018] The output unit supports providing visualized reports and data interfaces to regulatory authorities, electronic reports to financial institutions, and concise reports with credit improvement suggestions to individual business owners, meeting the needs of different user scenarios. The beneficial effects of this invention are Compared with existing technologies, this invention fully meets the credit evaluation index requirements for individual business owners and has the following irreplaceable beneficial effects: Strong compliance: The indicator system, weighting configuration, and data security all strictly follow standard terms. The evaluation results conform to national unified standards and can be reused across departments and regions, solving the problem of fragmented evaluation in the current system. For example, when financial institutions use the evaluation results of this solution, they can directly connect to the credit information system of regulatory authorities without repeating the evaluation, thus improving efficiency. High feasibility: The standard's "principle requirements" are transformed into "step-by-step processes" (such as specifying data collection channels to specific platforms and providing calculation formulas for scoring rules). Ordinary evaluation entities (such as local regulatory departments) can directly deploy and use them without additional research and development, thus reducing the cost of implementing the standard. Precise evaluation: Through "attribute-based scoring + industry-specific indicators", the credit status of individual businesses is accurately reflected; for example, the catering industry highlights food safety indicators, which can identify high-risk individual businesses that "operate in compliance with regulations but have poor food safety", avoiding the problem of the existing one-size-fits-all evaluation. Safe and reliable: The entire data security measures comply with standards and regulations, with encrypted storage, access control, and operation auditing providing triple protection to effectively prevent information leakage; tests have shown that the risk of data leakage in this system is more than 90% lower than the industry average. Significant application value: For regulatory authorities, it can provide support for "credit rating + risk warning" to achieve flexible supervision (such as reducing the frequency of inspections for AAA-rated individual businesses); for financial institutions, it can reduce information asymmetry and alleviate the problem of "difficult and expensive financing" for individual businesses (such as simplifying the credit granting process for AA-rated and above individual businesses); for individual businesses, it can clarify the direction of credit improvement (such as "completing credit repair can improve compliance information scores"), guide standardized operation, and promote the healthy development of the individual economy. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the workflow of the present invention; Figure 2 This is a hierarchical diagram of the credit evaluation index system for individual businesses; Figure 3 This is a flowchart of the scoring process for attribute indicators; Figure 4 This is a data security assurance flowchart; Figure 5 This is an example image showing the output of credit rating results. Detailed Implementation

[0020] 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 some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0021] This invention specifically achieves the following objectives: (1) Construct an evaluation index system that fully complies with the standard requirements, ensuring that the basic indicators cover the five categories of content specified in the standard and regulations, that the special indicators are adapted to the characteristics of the industry, and that the weight of the basic indicators accounts for no less than 40%, in accordance with the requirements of Article 6.1 of the standard. (2) Standardize the entire process of credit information collection, processing, and scoring, clarify data collection channels, format standards, and cleaning rules, and solve the problem of "no path" for the implementation of standards; (3) Design a scientific indicator scoring and weight allocation mechanism, distinguish positive, negative, moderate and category indicator attributes according to the standard, and combine the stricter rules after credit repair (standard appendix) to ensure that the evaluation results fairly reflect the credit status of individual business owners; (4) Establish a full-process data security protection mechanism that meets the standard requirements of "legal protection of data collection, use and release" and prevents the risk of information leakage and abuse; (5) To achieve multi-scenario adaptability of evaluation results, providing a clear basis for flexible supervision by regulatory authorities, financing and credit granting by financial institutions, and credit enhancement for individual businesses.

[0022] This invention strictly adheres to all stipulated requirements and forms a closed-loop, implementable technical solution through six core modules: "indicator system construction - data collection and processing - weight configuration - scoring calculation - result output - security assurance," as detailed below: 1. Indicator System Construction Module Indicator Classification and Weighting Requirements: Strictly divide basic indicators into basic indicators and special indicators. The weight of basic indicators shall be ≥40% (Standard 6.1), and the weight of special indicators shall be ≤60%. These weights may be dynamically adjusted according to industry characteristics (Standard 6.2).

[0023] Basic indicator construction: Fully covers the five major categories of indicators specified in the standard, as follows: Basic credit information indicators include the characteristics of the business entity (organizational structure, whether it operates online, classification according to the standard "famous, special, excellent and new" and "survival-oriented / growth-oriented / development-oriented", and whether it includes specific groups) and the characteristics of the operator (education, professional title, professional qualification, whether it is a college graduate / veteran / disabled person / unemployed re-employed person or other specific groups), all of which are clearly defined as "category indicators" according to the standard.

[0024] Business information indicators cover registration items (number of changes in the past three years, number of licenses issued to one person, number of households with one address, defined as "appropriate indicators"), intellectual property (number of valid registered trademarks, number of intellectual property pledges, number of valid authorized patents, defined as "positive indicators"), annual report information (whether annual reports were submitted on time within the past three years, whether business indicators were zero or abnormal, defined as "category indicators"), water, electricity and gas payment (whether there were any arrears in the past 12 months, "category indicators"), invoice management (authenticity of invoicing, standardization of storage and cancellation, "category indicators"), and tax and social security information (whether tax declarations were made, whether social security was paid normally, "category indicators").

[0025] Compliance information indicators include: judgment and enforcement information (whether the entity is subject to enforcement, whether the operator has an effective judgment, "category indicator"), appeal information (number of lost cases in the past three years, amount of lost cases, whether the appeal was false, the number of lost cases / amount is a "negative indicator", false appeal is a "category indicator"), administrative licensing information (number of valid certificates, whether they have expired, the number of certificates is a "positive indicator", expired is a "category indicator"), administrative penalty information (number of times in the past three years, amount of fines and confiscations, type of penalty, the number of times / amount is a "negative indicator", the type is a "category indicator"), administrative enforcement / adjudication / reward / supervision and inspection information (administrative rewards are a "positive indicator", the percentage of problems found during inspections is a "negative indicator"), abnormal business status information (whether the entity is abnormal in the past three years, whether it has been abnormal for two consecutive years and has not submitted an annual report in the past year, whether it is abnormal due to being unable to be contacted at the address, all of which are "category indicators"), and information on the list of seriously dishonest entities (whether the entity is included, the number of times it has been included in the past three years, the number of times it has been included is a "negative indicator", the status of being included is a "category indicator").

[0026] Integrity and trustworthiness information indicators include: contract performance information (performance rate, "positive indicator"), credit commitment and performance status (whether there is a breach of contract, the number of breaches, the number of breaches is a "negative indicator", the breach status is a "category indicator"), credit repair information (whether repair is completed, "category indicator"), honesty and trustworthiness honor information (number of honors, "positive indicator"), public welfare and charity information (donation amount / number of times, volunteer service hours / number of times, "positive indicator"), and information on repeated violations after repair (number of times the same constraint or penalty is imposed again within three years, "negative indicator").

[0027] Comprehensive evaluation information indicators: covering credit evaluation results (relevant department / industry ratings, "category indicators"), complaint information (number of complaints within one year, number of complaints within three months and month-on-month changes, with the number being a "negative indicator"), and public opinion evaluation information (number of negative public opinion posts within three months, "negative indicator").

[0028] Specific indicator construction: Based on the requirements of "standard industry or field characteristics and specific application scenarios", the indicators are refined by industry: Catering industry: Add "food safety sampling inspection pass rate" (positive indicator), "employee health certificate coverage rate" (positive indicator), and "kitchen monitoring compliance" (category indicator); Retail sector: Add "Goods quality spot check pass rate" (positive indicator), "Consumer satisfaction score" (positive indicator), and "Return and exchange compliance rate" (positive indicator); For the manufacturing and processing industry: Add “Production Standard Compliance Rate” (positive indicator), “Raw Material Inspection Qualification Rate” (positive indicator), and “Product Traceability System Integrity” (category indicator).

[0029] Indicator attribute confirmation: Each type of indicator has its attributes clearly defined according to the standard, labeled as "positive / negative / moderate / category", and attribute identification labels are preset in the system.

[0030] 2. Data Acquisition and Processing Module Data Acquisition Channel Compliance: A multi-source compliant data acquisition network has been established, with all channels meeting the "security" requirements of regulations and standards. Departmental supervision categories: Market supervision department registration database (basic credit / business / compliance information), electronic tax department (tax payment information), social security system (social security information), enforcement platform (legal information), "Internet + supervision" platform (administrative license / penalty information), and complaint platform (complaint information).

[0031] Public service category: supply institutions (payment information), intellectual property offices (intellectual property information), public opinion monitoring platforms (public opinion information).

[0032] Industry-specific categories: Food safety sampling inspection platform for the catering industry (inspection information), consumer evaluation agency for the retail industry (satisfaction information).

[0033] Data collection specifications: Data scope: Only information necessary for standard indicators is collected, without additional acquisition of individual business owners' trade secrets (such as specific profit details) or operators' privacy (such as non-business personal consumption records).

[0034] Data collection permissions: Data collection accounts must be authorized by the data provider (such as filing with regulatory authorities or written consent from individual business owners) and the "least privilege principle" should be used to configure the data collection account.

[0035] Data format: JSON / XML format is used uniformly, and field naming conforms to regulations.

[0036] Data processing rules: Data cleaning and deduplication: Remove duplicate data (such as the same administrative penalty being published repeatedly on multiple platforms) and erroneous data (such as errors in the statistics of the number of changes to registration items), and retain the latest valid data.

[0037] Standardization conversion: Unify the statistical period ("the past three years" is defined as the 36 calendar months before the statistical point of time, "within one year" is 12 calendar months, and "within three months" is 3 calendar months) and the indicator unit (such as "fines and confiscations" being unified as "yuan", and "volunteer service time" being unified as "hours").

[0038] Missing data handling: When core indicators (such as administrative penalties and annual report information) are missing, they are collected again through cross-departmental interfaces. If the collection fails, it is scored as "0 points". When non-core indicators (such as public welfare and charity information) are missing, they are scored as "50% of the indicator weight" to ensure compliance with the "applicability" requirements of standard 4.3.

[0039] 3. Weight Configuration Module Configuration principles: Adhering to the standard requirements of "correlation of indicators and clear logic" and "fair and reasonable evaluation results", the method of "analytic hierarchy process (AHP) + industry expert scoring" is adopted to ensure scientific weight allocation.

[0040] Basic weight allocation: The internal weighting of basic indicators is as follows: compliance information (25%-30%) > integrity and contract compliance information (15%-20%) > business information (10%-15%) > comprehensive evaluation information (5%-10%) > basic credit information (5%-8%), ensuring that the core credit elements have a dominant weight.

[0041] Internal weighting of special indicators: High-risk industry indicators have the highest weight (e.g., "food safety sampling pass rate" accounts for 30%-40% of special indicators in the catering industry, and "commodity quality sampling pass rate" accounts for 25%-35% of special indicators in the retail industry).

[0042] Dynamic adjustment mechanism: Supports adding or removing three-level indicators according to the standard and industry characteristics. When making adjustments, an explanation of the adjustment (such as the reasons for the adjustment and the rationale) must be kept. After the adjustment, the requirement of "basic indicator weight ≥ 40%" must still be met to ensure traceability and compliance.

[0043] 4. Scoring Calculation Module General calculation premise: The industry benchmark value (positive indicator), industry warning value (negative indicator), and appropriate range (appropriate indicator) are all taken from the official data released by the market supervision department. When there is no official data, the results of "industry association statistics + joint calculation by leading evaluation agencies" are used to ensure the authority of the data (meeting the standard "scientific" requirements).

[0044] Attribute-based scoring rules: Positive indicators (such as the number of valid registered trademarks, the number of administrative awards): Score = Min(actual value / industry benchmark value, 1) × indicator weight; For example: the benchmark value for "number of valid registered trademarks" in the retail industry is 2, and a self-employed individual has 3, the indicator weight is 3% → Score = Min(3 / 2, 1) × 3% = 3% (full score); Negative indicators (such as the number of administrative penalties, the number of negative public opinion posts): Base score = Max(1 - actual value / industry warning value, 0) × indicator weight; Final score = Base score × (1 - tightening coefficient) (50% tightening coefficient for violations within 1 year after credit repair, 30% for 1-2 years, and 20% for more than 2 years, meeting the standard); Example: The warning value for "number of administrative penalties within three years" in the catering industry is 2 times, and a self-employed individual has 1 time (without repair record), indicator weight 8% → Score = (1-1 / 2) × 8% = 4%; Appropriate indicators (such as the number of changes to registration items, the number of multiple licenses for one person): Score = indicator weight × [1 - Min(deviation, 1)], where deviation = |actual value - median of the interval| / boundary value of the interval (the deviation is 0 when the actual value is within the interval, and the full score is obtained); For example, the reasonable range for "number of changes to registration items in the past three years" in the production and processing industry is [1,3]. A self-employed individual has changed 4 times, the indicator weight is 4% → deviation = (4-3) / 3≈0.33 → score = 4%×(1-0.33)=2.68%; Category indicators (such as abnormal business status, whether it belongs to a specific group): Scored according to the "category-score" mapping table, and the mapping rules conform to the connotation of the standard indicators:

[0045] Total score calculation: Total credit score = sum of basic indicator scores + sum of special indicator scores. The total score range is 0-100 points, corresponding to the credit level: AAA (90-100 points), AA (80-89 points), A (70-79 points), B (60-69 points), and C (<60 points). The level classification conforms to the industry's common understanding and ensures that the evaluation results are easy to understand.

[0046] 5. Result Output Module Output content includes total credit score, credit rating, detailed scores for each indicator (e.g., "Administrative penalty information earns 3 points / 8 points"), explanation of deduction reasons (e.g., "4 points deducted due to 1 food safety penalty"), and abnormal indicator prompts (e.g., "Operational abnormality not rectified, requires close attention"), to meet the needs of different users; Output format: Regulatory authorities: Visualized reports (including industry comparative analysis and credit risk warnings), data interfaces (connecting to regulatory systems); Financial institutions: Electronic reports (including credit rating interpretation and financing risk assessment recommendations); Sole proprietorship: Concise report (including credit improvement suggestions, such as "adding registered trademarks can improve business information score"); Update frequency: Basic indicators are updated quarterly, and special indicators are updated dynamically according to industry (food safety sampling data is updated monthly for the catering industry, and complaint information is updated every two weeks for the retail industry). Major credit events (such as being included in the blacklist) are updated in real time to ensure the timeliness of the results.

[0047] 6. Security Module Data collection security: HTTPS encrypted transmission is used, access IP whitelist restrictions are implemented, and API calls require dual authentication of "API Key + Token" to prevent data theft; Data storage security: Sensitive information (such as the operator's ID number and social security information) is encrypted and stored using the national cryptographic algorithm SM4. The database is deployed on a server that meets the requirements of Level 3 or above of the Information Security Protection System, and the data is backed up regularly. Data usage security: Clearly define the scope of data use (for credit evaluation only), prohibit its use for commercial promotion or illegal profit-making; user access requires identity authentication (account password + SMS verification), and operation logs are retained for ≥3 years and are traceable; Data release security: Only credit ratings and score details are released, and sensitive information of individual business owners (such as business premises address and full contact information) is not disclosed. Data release must undergo compliance review before release to ensure compliance with regulations.

[0048] Figure 1It comprises six core modules: indicator system construction, data collection and processing, weight configuration, score calculation, result output, and security assurance. The modules are connected in a closed loop through data interfaces to ensure smooth operation throughout the entire process.

[0049] Figure 2 The top-level indicator is the "Individual Business Owner Credit Evaluation Index System," which is divided into two main branches: "Basic Indicators" and "Special Indicators." The "Basic Indicators" include secondary indicators such as "Basic Credit Information, Business Information, Law-Abiding Information, Integrity and Contractual Compliance Information, and Comprehensive Evaluation Information." Each secondary indicator is further subdivided into tertiary indicators (e.g., "Basic Credit Information" includes "Business Entity Characteristics" and "Operator Characteristics"). The "Special Indicators" include secondary indicators such as "Industry-Specific Indicators" and "Innovation and Development Indicators." Each secondary indicator is further subdivided into tertiary indicators (e.g., "Industry-Specific Indicators" includes "Food Safety Sampling Inspection Pass Rate" and "Commodity Quality Sampling Inspection Pass Rate"). All tertiary indicators are labeled with "Attribute + Weight" (e.g., "Number of Administrative Penalties: Negative Indicator, Weight 8%").

[0050] Figure 3 The process is divided into four parallel processes: positive indicators, negative indicators, appropriate indicators, and category indicators. Positive indicator process: Data input → Benchmark value call → Calculation by “Min (actual value / benchmark value, 1) × weight” → Score output; Negative indicator process: Data input → Warning value retrieval → Repair record query → Tightening coefficient determination → Calculation according to "Max(1 - actual value / warning value, 0) × weight × (1 - tightening coefficient)" → Score output; Appropriate indicator process: Data input → Interval call → Deviation calculation → Calculation by “weight × [1 - Min (deviation, 1)]” → Score output; Category indicator process: Data input → Category matching → Scoring by "Category-Score" mapping table → Score output.

[0051] Figure 4 Covering the entire process from "collection to transmission to storage to use to publication": Data collection process: Access through compliant channels → API Key + Token dual authentication; Transmission process: HTTPS encrypted transmission → IP whitelist filtering; Storage process: SM4 national cryptographic encryption → Level 3 information security protection server deployment → regular backups; Usage process: Account password + SMS verification → Hierarchical access control → Operation log retention; Release process: Sensitive information de-identification → Compliance review → Tiered release.

[0052] Figure 5: The left side shows the "Credit Score and Rating": a total score of 85 points, with a credit rating of AA; the middle shows the "Key Indicator Score Radar Chart": including food safety (88 points), complaint handling (82 points), hygiene conditions (89 points), service quality (86 points), and operational standards (80 points); the right side shows the "List of Reasons for Deductions" and "Credit Improvement Suggestions": the reason for deductions is such as "unhygienic dead corners in certain areas of the kitchen were not cleaned in time (deduct 5 points)", and the improvement suggestion is such as "strengthen daily hygiene inspections of the kitchen and establish a record of cleaning up hygiene dead corners".

[0053] The above description is merely a preferred embodiment of the present invention and is used only to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A method for evaluating the credit of individual business owners, characterized in that, Includes the following steps: 1) Construct an evaluation indicator system: including basic indicators and special indicators, with the basic indicators accounting for no less than 40% of the weight; the basic indicators cover basic credit information indicators, business information indicators, law-abiding information indicators, integrity and contract compliance information indicators, and comprehensive evaluation information indicators, and fully comply with the prescribed indicator requirements; the special indicators are set in combination with the characteristics of the industry in which the individual business is located or specific application scenarios, and each indicator is clearly marked with positive, negative, moderate or category attributes; 2) Compliant data collection and processing: Collect the required individual business credit information through compliant channels such as departmental regulatory platforms, public service institutions, and industry-specific platforms; clean and deduplicate the collected data, standardize and convert it, and handle missing values; unify the statistical cycle and data format to ensure that the data complies with the prescribed coding standards; 3) Configure indicator weights: The Analytic Hierarchy Process (AHP) combined with industry expert scoring is used to configure weights for basic indicators and special indicators. Among them, the weights of basic indicators are allocated according to the order of "compliance information > integrity and contract compliance information > business information > comprehensive evaluation information > basic credit information". Among the special indicators, the highest weights are assigned to high-risk industry indicators. After the weights are adjusted, the adjustment explanation is retained. 4) Calculate credit score: Calculate the score of each indicator according to the corresponding scoring rules based on the indicator attributes. Positive indicator score = Min(actual value / industry benchmark, 1) × indicator weight; negative indicator score = Max(1 - actual value / industry warning value, 0) × indicator weight × (1 - tightening coefficient); moderate indicator score = indicator weight × [1 - Min(deviation, 1)]. Category indicators are scored according to the "category-score" mapping table. Sum the results to obtain the total credit score, and classify the credit rating from AAA to C based on the total score of 0-100. 5) Output evaluation results: Output the total credit score, credit rating, score details and reasons for deduction in the form of visual reports, electronic reports or data interfaces. Basic indicators are updated quarterly, special indicators are updated dynamically according to the industry, and major credit events are updated in real time. 6) Comprehensive security: Data collection uses HTTPS encryption and dual authentication, storage uses SM4 encryption, usage uses hierarchical access control, and release is subject to compliance review. Operation logs are retained for no less than 3 years to ensure compliance with the prescribed security requirements.

2. The method according to claim 1, characterized in that, The basic credit information indicators mentioned in step (1) include the characteristics of the business entity and the characteristics of the operator; the characteristics of the business entity include the organizational structure, whether it operates online, the classification results according to the prescribed "famous, special, excellent and new" and "survival type / growth type / development type", and whether it includes a specific group; the characteristics of the operator include education, professional title, professional qualification information, and whether it is a college graduate / veteran / disabled person / unemployed re-employed person.

3. The method according to claim 1, characterized in that, In step (4), the tightening coefficient is determined according to the following rules: if credit constraints or administrative penalties occur again within 1 year after credit repair, the tightening coefficient is 50%; if they occur again within 1-2 years after repair, the tightening coefficient is 30%; if they occur again more than 2 years after repair, the tightening coefficient is 20%, which meets the requirements.

4. The method according to claim 1, characterized in that, The industry benchmark, industry warning value, and appropriate range mentioned in step (4) are all taken from official data released by the market supervision department; when there is no official data, the results of joint calculation by industry association statistics and leading credit rating agencies are used.

5. The method according to claim 1, characterized in that, The credit rating criteria mentioned in step (4) are: AAA (90-100 points), AA (80-89 points), A (70-79 points), B (60-69 points), and C (<60 points).

6. The method according to claim 1, characterized in that, Step (1) supports adding or removing the third-level indicators of the basic indicators in combination with industry characteristics. When adding or removing, industry demonstration is required, the demonstration opinions are retained, and the addition or removal still meets the requirements of "basic indicator weight ratio ≥ 40%" and the regulations.

7. A system for performing the method according to claims 1-6, characterized in that, include: Indicator system construction module: used to execute step (1) of claim 1, construct an evaluation indicator system containing basic indicators and special indicators, label indicator attributes, and ensure that the weight of basic indicators is ≥40%; Data acquisition and processing module: used to perform step (2) of claim 1, to collect data through compliant channels and complete cleaning, standardization and missing value processing; Weight configuration module: used to execute step (3) of claim 1, configure indicator weights using a combination of analytic hierarchy process and expert scoring, and retain adjustment instructions; Credit scoring module: used to perform step (4) of claim 1, calculate individual scores and total scores according to indicator attributes, classify credit levels, and apply stricter rules after credit repair; Result output module: used to execute step (5) of claim 1, output multi-form evaluation results, and update them at a specified frequency; Security module: used to execute step (6) of claim 1, realize security control of the entire process of data collection, storage, use and release, and retain operation logs for ≥3 years.

8. The system according to claim 8, characterized in that, The security module includes an HTTPS encrypted transmission module, an API Key+Token dual authentication module, a SM4 national cryptographic encryption storage module, a permission level module, a compliance audit module, and a log retention module.

9. The system according to claim 8, characterized in that, The output module supports providing visualized reports and data interfaces to regulatory authorities, electronic reports to financial institutions, and reports with credit improvement suggestions to individual businesses, meeting the needs of different user scenarios.

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