Credible data label construction and traceability method for carbon financial scene

Abstract

The invention discloses a credible data label construction and traceability method for a carbon financial scene, and relates to the technical field of general financial data processing. The method comprises a data label design module, a credible traceability module, a compliance out-of-domain module and an operation debugging module, a report is disassembled according to a carbon evaluation standard to form a full-amount label, and a power grid data index of a green electricity financial evaluation guide rule is 100% covered; a data quality evaluation system is established according to a two-dimensional traceability scheme, and an optimal mapping relation is screened to complete traceability; compliance out-of-domain is realized through the data transaction platform; and finally, outputting a carbon evaluation report through operation debugging. According to the method, the average time from data collection to report is shortened to 2.45 days from 31.1 days, the data quality index score is not lower than 99%, compliance and capitalization are both considered, the efficiency and scale of the common financial business are improved, and the financing cost of an enterprise is reduced.

Description

Technical Field

[0001] This invention relates to the field of inclusive finance data processing technology, specifically to a method for constructing and tracing credible data tags for carbon finance scenarios. It is applicable to data tracing, standardized collection, compliant data export, and efficient generation of carbon assessment reports in the "carbon assessment + finance" scenario, and is particularly suitable for inclusive finance businesses in the upstream and downstream of the power grid enterprise's related industrial chain. Background Technology

[0002] Currently, the demand for green funds in inclusive finance is growing rapidly. However, the entire process from applying for green financing to receiving credit from financial institutions is time-consuming and lengthy. The core bottleneck lies in the data collection and carbon assessment report issuance stage—the existing process takes an average of 31.1 days, accounting for more than 70% of the total process time.

[0003] Existing technologies suffer from three key problems: First, the design of data labels lacks a unified basis, leading to poor communication between banks and carbon assessment agencies, high communication costs, and incomplete indicator coverage, making it difficult to meet the requirements of standards such as the "Green Electricity Finance Evaluation Guidelines." Second, data traceability lacks standardized methods, failing to form a complete mapping system of "field-data item-table-system," making it difficult to guarantee data quality (completeness, accuracy, timeliness, etc.), causing financial institutions to question the credibility of the data. Third, the data outbound path is not standardized, with a disconnect between enterprise-level data label output and data asset entry requirements. Either the data is excessively anonymized, failing to meet accurate credit granting, or the compliance is insufficient to support asset ownership confirmation, ultimately hindering the expansion of inclusive finance business scale and efficiency improvement.

[0004] While some technologies involve data collection, quality control, or credit assessment, they do not provide an integrated solution for data label design, reliable traceability, and compliant export for the specific scenario of "carbon assessment + finance." This fails to address the core pain points of low efficiency in issuing carbon assessment reports and insufficient data credibility. Summary of the Invention

[0005] (I) Purpose of the Invention

[0006] This invention aims to provide a reliable data tag construction and traceability method for carbon finance scenarios, solving the problems of time-consuming carbon assessment report issuance, low data standardization, unreliable traceability, and non-compliance in the existing inclusive finance business. It achieves efficiency in the data collection and carbon assessment report issuance process, reliability of data quality, and compliance of the outbound process, ultimately shortening the business cycle and expanding the scale of inclusive finance business.

[0007] (II) Technical Solution

[0008] This invention provides a method for constructing and tracing trusted data tags for carbon finance scenarios. The method includes a data tag design module, a trusted traceability module, a compliant data export module, and an operation and debugging module. These modules work collaboratively to achieve standardized collection, trusted traceability, compliant data export, and efficient generation of carbon assessment reports for inclusive finance data. The specific technical solution is as follows:

[0009] I. Data Tag Design Module

[0010] Based on the mature evaluation standards of carbon credit assessment agencies, and targeting the green order financing products of the Finance Department's inclusive finance business, the carbon assessment output results of the assessment agencies are sorted out and broken down into three core modules: material carbon emission reduction contribution report, carbon emission reduction compliance capability report, and enterprise carbon capability report. Based on the templates of each module and industry standards, supplementary indicators are added to form a complete data tag list:

[0011] (1) Design of labels related to the carbon emission reduction contribution report of materials

[0012] The Material Carbon Emission Reduction Contribution Report is based on a material order carbon emission reduction contribution quantification model. The data labels for the Material Carbon Emission Reduction Contribution Report are shown in Table 1.

[0013] Quantification model of carbon emission reduction contribution of material orders:

[0014] E = E 投资占比 *E 贡献力 ,

[0015] in:

[0016] E = Emission reduction, unit: tCO2

[0017] E 投资占比 =Percentage of this batch of material investment amount to the total investment amount of the provincial company in the current year

[0018] E 贡献力 = Emission reduction amount of the provincial company's "dual carbon contribution" within the year to which this batch of materials is procured

[0019] Table 1. Material Carbon Emission Reduction Contribution Report Data Label Requirements

[0020]

[0021] (2) Design of labels related to carbon emission reduction compliance reports

[0022] Based on the carbon emission reduction compliance capability report template (see Table 2), the carbon emission reduction compliance capability data labels are broken down and shown in Table 3:

[0023] Table 2 Carbon Emission Reduction Compliance Capability Report Template

[0024]

[0025] Table 3. Data Labeling Requirements for Carbon Emission Reduction Compliance Capability Report

[0026]

[0027] (3) Design of labels related to corporate carbon capacity reports

[0028] Based on the grid-side data source of the enterprise carbon capacity report template (Table 4), preliminary data labels are generated (Table 5).

[0029] Table 4 Enterprise Carbon Capacity Report Template

[0030]

[0031]

[0032] Table 5. List of Data Labeling Requirements for Enterprise Carbon Capacity Reports

[0033]

[0034]

[0035] (4) Determining the full data label list

[0036] Verify whether the preliminary data label list covers 80% of the power grid data indicators under the "Green Electricity Finance Evaluation Guidelines". If not, supplement relevant indicators, such as the enterprise's clean energy electricity consumption, the industry's average clean energy electricity consumption, the industry's electricity consumption, the longest period of arrears (in days) in the past 24 months, the enterprise's cumulative arrears amount in the past 24 months, and the enterprise's total electricity bill payable, to ensure that the data labels cover 100% of the power grid data indicators under the "Green Electricity Finance Evaluation Guidelines", forming a complete data label list (Table 7):

[0037] Table 7: Full List of Data Tag Requirements

[0038]

[0039]

[0040] II. Trusted Traceability Module

[0041] A two-dimensional traceability solution combining industry standards and leading technology company practices is adopted to establish a data quality assessment system and complete the reliable traceability link between data tags and data sources.

[0042] (1) Establish a data quality assessment system

[0043] Based on the DAMA Data Management Body of Knowledge Guide and the Guidelines for Data Governance of Banking Financial Institutions as industry standards, and drawing on the data quality control practices of leading technology companies such as Huawei, Alibaba, and ByteDance, a system of six data quality assessment indicators has been established. The definitions of each indicator (Table 8) are as follows:

[0044] Table 8. Definitions of Data Quality Assessment Standards and Indicators

[0045]

[0046] (2) Field decomposition and mapping relationship sorting

[0047] The full data tags were broken down layer by layer to specific fields, covering material carbon emission reduction contribution reports, carbon emission reduction compliance reports, enterprise carbon capacity reports, and related fields for group standard supplements. A statistical table of data field traceability results was developed, and the mapping data items-table-system relationship of each field was sorted out. The credible traceability of all fields was completed, and a data linking table was developed.

[0048] (3) Optimal mapping relationship selection and data traceability table formulation

[0049] Evaluate the scores of six major data quality indicators for each potential data item, select the optimal mapping relationship with a score of no less than 99% for each indicator, and formulate a data traceability table.

[0050] Three-compliance outbound module

[0051] Using the wholesale outbound path of the data trading platform, and in accordance with the rules of the data trading platform, design the entire process of listing data tag results on the platform and the complete outbound process:

[0052] (1) Data product platform listing process

[0053] The data product platform includes three core stages: data product registration, listing, and trading.

[0054] 1. Data Product Registration: Submit the applicant's legal entity qualification certificate, basic information of the data product, detailed description of the data source and legality certificate, and data registration commitment letter. After the applicant conducts a preliminary review, a secondary review, and handles any objections during the public announcement period, a registration certificate will be obtained.

[0055] 2. Data Product Listing: Enter basic information about the data product, set pricing information, configure interface parameters (data interface products need to provide interface technical documents including architecture design, performance indicators, and security measures), supplement the data product usage instructions, application scenario cases, technical support service descriptions, and pricing basis materials, and complete the listing after submission for review;

[0056] 3. Data Product Transactions: After verifying the identities of the transaction parties, both parties negotiate the transaction details and sign a filing contract. The transaction is authenticated and funds are settled through the platform. The data provider delivers the data according to the contract, and the buyer uses the data after verification. The platform issues a transaction certificate.

[0057] (2) Complete outbound process

[0058] The complete outbound process is as follows: "Power grid enterprise → State Grid credit review → formation of information to be exported → data trading platform entity access review → data tag product / asset registration → registration review → issuance of registration certificate → application for listing → review and listing → demander places order → signing transaction agreement → payment → delivery of data tag product → confirmation of payment voucher → issuance of transaction voucher".

[0059] (3) Verification of trial operation outside the domain

[0060] Conduct pilot operations of green order financing business outside the designated area, and statistically analyze the success rate of power grid data collection in the carbon assessment report under the pilot operation results, ensuring that it is no less than 80%.

[0061] IV. Running the Debugging Module

[0062] Based on the completed trusted data tags, traceability relationships, and outbound processes, a financial inclusive business operation system is built, which executes the following four steps in sequence:

[0063] 1. Data collection: Enterprise information input, form uploading, data collection and verification are carried out according to unified standards, with an average time of less than 0.4 days;

[0064] 2. Data Calculation: The algorithm automatically calculates the data label results and directly outputs the results;

[0065] 3. Data verification: Conduct credit compliance verification outside the domain, with an average processing time of 1.5 days;

[0066] 4. Report Issuance: Carbon assessment agencies quickly generate carbon assessment reports based on data labeling results, with an average processing time of 0.5 days.

[0067] The cumulative time taken at each key process node is calculated. For cases exceeding the 2.5-day target, bottlenecks are identified and adjustments are made. No fewer than 21 operational tests are conducted to ensure that the entire process from data collection to report generation does not exceed 2.5 days, ultimately achieving an average time of ≤2.45 days. A carbon assessment report is then generated.

[0068] (III) Beneficial Effects

[0069] Breakthrough in efficiency: Through standardized data label design, reliable traceability and compliant outbound processes, the average time from data collection to carbon assessment report issuance has been shortened from 31.1 days to 2.45 days, significantly improving the efficiency of inclusive finance business and driving a 100% increase in the scale of green order financing business.

[0070] Data quality credibility: Establish a full-chain control system of "design basis - traceability standards - quality assessment", ensure that data labels cover 100% of the power grid data indicators in the "Green Electricity Finance Evaluation Guidelines", and ensure that the scores of the six major data quality indicators of traceability data items are all no less than 99%. The success rate of power grid data collection on the carbon assessment agency side reaches 99%, solving the core pain point of insufficient data credibility.

[0071] Cross-domain compliance and assetization compatibility: By adopting the wholesale path of the data trading platform, it not only meets the enterprise-level data tagging and accurate output needs, but also ensures the compliance of data crossing the domain through a standardized registration-listing-transaction process, providing direct and fast credentials for data asset entry into the table, and achieving the dual goals of compliance and assetization.

[0072] Significant business value and scalability: The execution interest rate is as low as 3.5% (100 basis points lower than the market average), reducing corporate financing costs; the results can be promoted in the multi-level collection, reporting, statistics, analysis, and decision-making of carbon emission data and carbon reduction project information of provincial, municipal and county power supply companies, realizing the overall management of carbon performance and improving the efficiency of carbon management decision-making and process control. Attached Figure Description

[0073] Figure 1 This is a flowchart of the method of the present invention.

[0074] Figure 2 This refers to the coverage rate of power grid data indicators in the "Green Electricity Finance Evaluation Guidelines".

[0075] Figure 3 This is a data quality assessment result for reliable traceability.

[0076] Figure 4 This is a complete flowchart of the outbound process.

[0077] Figure 5 This refers to the success rate of power grid data acquisition in the carbon assessment report under the trial operation results.

[0078] Figure 6 The logic diagram for running and debugging.

[0079] Figure 7 The results of the carbon assessment report (1).

[0080] Figure 8 The results of the carbon assessment report (2). Detailed Implementation

[0081] The following section provides a detailed description of the trusted data tag construction and traceability method for carbon finance scenarios based on the actual application scenario of Shandong Taian Company. The specific technical solution is as follows:

[0082] I. Data Tag Design Module

[0083] This embodiment takes the green order financing business of State Grid Shandong Electric Power Company Taian Power Supply Company (hereinafter referred to as "Taian Company") as the application object, and uses Yingda Carbon Asset's carbon assessment standard as the design basis. The data label design is completed according to the following steps:

[0084] The carbon assessment output results of Yingda Carbon Assets for green order financing business are analyzed and broken down into three core modules: material carbon emission reduction contribution report, carbon emission reduction compliance capability report, and enterprise carbon capability report. The business scenario corresponding to each module is the green financing carbon assessment review of upstream and downstream enterprises in the industrial chain of Taian Company.

[0085] (1) Material Carbon Emission Reduction Contribution Report Label Design

[0086] Based on the material order carbon emission reduction contribution quantification model and combined with the distribution network material procurement contracts signed between Taian Company and suppliers (such as "State Grid Shandong Electric Power Company 202X No. X Distribution Network Material Agreement Inventory Public Bidding Procurement Project XXX Procurement Contract", contract number: XX), the material carbon emission reduction contribution report data labels are decomposed as shown in Table 1:

[0087] Quantification model of carbon emission reduction contribution of material orders: E = E 投资占比 *E 贡献力

[0088] in:

[0089] E = Emission reduction, unit: tCO2

[0090] E 投资占比 =Percentage of this batch of material investment amount to the total investment amount of the provincial company in the current year

[0091] E 贡献力 = The emission reduction amount of the provincial company's "dual carbon contribution" within the year to which this batch of materials is procured.

[0092] Table 1 Material Carbon Emission Reduction Contribution Report Labels

[0093] (2) Carbon emission reduction compliance capability report label design

[0094] Based on the carbon emission reduction compliance capability assessment template (Table 2) for Taian Company's green order financing business, and combined with the cooperation data of the past three years and the first phase (the year the business occurred and the three years prior), carbon emission reduction compliance capability data labels were generated (Table 3):

[0095] Table 2 Carbon Emission Reduction Compliance Capability Report Template

[0096]

[0097] Table 3 Data Labels for Carbon Emission Reduction Compliance Capability

[0098]

[0099] (3) Enterprise carbon capacity report label design

[0100] Based on the grid-side data sources (marketing department, materials company, etc.) of the enterprise carbon capacity report template (Table 4), preliminary enterprise carbon capacity report data labels are generated (Table 5), and supplemented with indicators based on the actual situation of electricity consumption management and supplier management of Tai'an Company:

[0101] Table 4 Enterprise Carbon Capacity Report Template

[0102]

[0103]

[0104] Table 5 Data Labels for Enterprise Carbon Capacity Reports

[0105]

[0106]

[0107] (4) Determining labels for all data

[0108] By comparing the grid data indicators under the "Green Electricity Finance Evaluation Guidelines" with the above three preliminary decomposed label lists, it was found that only 40% of the standard indicators are covered. It is necessary to supplement the labels with indicators such as enterprise clean energy electricity consumption, industry average clean energy electricity consumption, industry electricity consumption, the longest period of enterprise arrears (days) in the past 24 months, the cumulative amount of enterprise arrears in the past 24 months, and the total amount of electricity bills payable by the enterprise, to form a complete set of data labels (Table 7).

[0109] Table 6. Statistics on the Coverage of Power Grid Side Data Indicators

[0110]

[0111] Table 7 Full Data Labels

[0112]

[0113]

[0114] After final verification, the complete data label list fully covers the power grid data indicators under the "Green Electricity Finance Evaluation Guidelines," meeting the design objectives. (See attached document.) Figure 2 .

[0115] II. Specific Implementation of the Trusted Traceability Module

[0116] This embodiment adopts a two-dimensional traceability solution combining industry standards and leading technology company practices. It uses the *DAMA Data Management Body of Knowledge Guide* and the *Guidelines for Data Governance of Banking Financial Institutions* as standards, and draws on the data quality control experience of Huawei, Alibaba, and ByteDance to complete the reliable traceability of Taian Company's data tags.

[0117] (1) Data quality assessment system

[0118] A data quality assessment indicator system with six key metrics was established, and the specific assessment methods for each indicator were determined based on the characteristics of Taian Company's business data.

[0119] 1. Completeness: Assessed through missing rate (the proportion of missing data records out of the total number of data records checked), volatility (the proportion of the total number of data records checked to increase or decrease compared to the previous period), and null value rate (the proportion of null data fields out of the total number of data fields checked);

[0120] 2. Accuracy: Assessed by error rate (the proportion of fields with incorrect values ​​or content out of the total number of fields in the checked data);

[0121] 3. Uniqueness: Assessed through the duplication rate (the proportion of data with duplicate primary keys out of the total number of data being checked);

[0122] 4. Consistency: Evaluated by the number of rule violations (the total number of data records or fields with consistency issues);

[0123] 5. Standardization: Assessed through the pass rate (the proportion of fields that meet the requirements for length, format, and accuracy out of the total number of fields checked);

[0124] 6. Timeliness: Assessed through timeliness rate (the proportion of timely generated data to the total amount of verified data).

[0125] (2) Field decomposition and mapping relationship analysis

[0126] The full data tags were broken down layer by layer to specific fields, covering material carbon emission reduction contribution reports, carbon emission reduction compliance reports, enterprise carbon capacity reports and group standard supplements, forming a statistical analysis of data field traceability results (Table 9). The mapping data items-table-system relationship of each field was also sorted out. Taking the "contract amount" field as an example, its data connection results are shown in Table 10.

[0127] Table 9: Data Field Tracing Results

[0128]

[0129]

[0130] Table 10 Data Connection Results

[0131]

[0132] (3) Optimal mapping relationship selection and data traceability table formulation

[0133] The optimal mapping relationship was selected based on the scores of the six major data quality indicators, all of which were no less than 99%. The reliable traceability of all fields was completed, and a dedicated data traceability table for Tai'an Company was created (Table 11).

[0134] Table 11 Data Traceability Table

[0135]

[0136]

[0137]

[0138] The statistical results of the data quality assessment of the selected trusted traceability system are shown below. Figure 3 Upon verification, the minimum score of the six indicators of the selected mapping relationship was 99.02%, meeting the preset target of no less than 99%.

[0139] III. Compliance Outbound Module

[0140] This embodiment adopts the outbound path of the Shandong Taian Data Exchange Platform wholesale and, combined with the inclusive finance business process of Taian Company, designs a complete compliant outbound solution:

[0141] (1) Data product platform listing process

[0142] 1. Data Product Registration: Taian Company submits legal person qualification certificate, basic information of data product, proof of legality of data source (such as data authorization documents from marketing department and materials company) and data registration commitment letter. After the platform conducts preliminary review, secondary review and public announcement and handling of objections, it obtains data product registration certificate.

[0143] 2. Data Product Listing: Enter basic information about the data tag product, set the fee standard, supplement the product usage instructions, green order financing application cases and technical support solutions, and complete the listing after the platform approves the application.

[0144] 3. Data product transactions: After the demand party (such as Yingda Carbon Asset Company) completes the identity verification, it negotiates the transaction details with Tai'an Company and signs a filing contract. The funds are settled through the platform. Tai'an Company delivers the data tag products according to the contract. After the demand party verifies that there are no errors, it uses the products and the platform issues a transaction certificate.

[0145] (2) Complete outbound process

[0146] The entire process involves: "Tai'an Company → State Grid Credit Review → Formation of Information to be Released → Tai'an Data Trading Platform Entity Access Review → Data Tag Product / Asset Registration → Registration Review → Issuance of Registration Certificate → Application for Listing → Review and Listing → Demand Party Places Order → Signing of Transaction Agreement → Payment → Delivery of Data Tag Product → Confirmation of Payment Voucher → Issuance of Transaction Voucher". For details, please refer to [link to relevant documentation]. Figure 4 .

[0147] (3) Verification of trial operation outside the domain

[0148] The green order financing business of Taian Company was put into trial operation outside the designated area. The success rate of power grid data collection in the carbon assessment report under the trial operation results is shown in the figure. Figure 5 The results showed a success rate of 99%, meeting the target requirement of at least 80% for the State Grid data collection success rate in carbon assessment reports from carbon assessment agencies.

[0149] IV. Operation and Debugging Module

[0150] Based on the aforementioned data tags, traceability relationships, and outbound processes, a Taian Company inclusive finance business operation system was built, and no fewer than 21 operation and debugging sessions were conducted. The operation and debugging logic is as follows: Figure 6 The specific steps are as follows:

[0151] (1) Operation steps

[0152] 1. Data collection: Enter enterprise information according to unified standards, upload data by scanning forms, and complete verification, with an average time of less than 0.4 days;

[0153] 2. Data Calculation: The system uses automated algorithms to calculate the data labeling results and directly outputs the results.

[0154] 3. Data verification: Conduct credit compliance verification and outbound processing, with an average processing time of 1.5 days;

[0155] 4. Report Issuance: Carbon assessment agencies generate carbon assessment reports based on data labeling results, with an average processing time of 0.5 days.

[0156] (2) Time statistics and optimization

[0157] The cumulative time taken at each process node was calculated. For cases exceeding 2.5 days, bottlenecks were identified and optimized. The time statistics for 21 debugging sessions are as follows:

[0158] Table 12 Statistical Results of Cumulative Time Used at Test Points

[0159]

[0160] Ultimately, the average time from data collection to report issuance for Taian Company's inclusive finance business was 2.45 days, meeting the target requirement of no more than 2.5 days. The output carbon assessment report results are available here. Figure 7 , Figure 8 .

[0161] Through the above specific implementation, Taian Company has achieved high efficiency in the collection of inclusive finance data and the issuance of carbon assessment reports, reliable data quality, and compliance of the process of leaving the country. The scale of green order financing business has increased by 100%, and the execution interest rate is as low as 3.5%, which has significantly reduced the financing costs of enterprises. The results can be promoted and applied in similar businesses of provincial, municipal and county power supply companies.

Claims

1. A method for trusted data tag construction and provenance for carbon finance scenarios, characterized in that, The system comprises a data label design module, a trusted traceability module, a compliance domain export module, and a running debugging module, which work together to realize the standardized collection, trusted traceability, compliance domain export, and efficient generation of carbon evaluation reports of inclusive finance data. The specific steps are as follows: (1) Data label design: Based on the evaluation standards of carbon credit evaluation agencies, the evaluation agency's carbon evaluation output results are analyzed for the green order financing products of the Ministry of Finance's inclusive finance business. The results are decomposed into three core modules: material carbon emission reduction contribution report, carbon emission reduction compliance ability report, and enterprise carbon capacity report. Based on the module templates and the supplementary indicators of the Green Electricity Finance Evaluation Guidelines, a full-quantity data label list covering 100% of the grid data indicators of the Guidelines is formed. (2) Trusted traceability: A dual-dimensional traceability scheme combining industry standards and leading technology enterprises is adopted to establish a six-dimensional data quality evaluation system including integrity, accuracy, uniqueness, consistency, standardization, and timeliness. The full-quantity data labels are decomposed layer by layer to specific fields, and the mapping relationship between fields and data items-table-system is analyzed. The optimal mapping relationship with a score of not less than 99% in the six data quality indicators is selected for traceability connection, and a data traceability table is developed. (3) Compliance domain export: The complete domain export process of "grid enterprise -> State Grid credit audit -> data label product / asset registration -> listing -> transaction" is implemented through the data trading platform. The export trial operation is carried out to ensure that the data collection success rate in the carbon evaluation report is not less than 80%. (4) Running debugging: The inclusive finance business operation system is built, and the data collection, data calculation, data audit, and report issuance steps are executed in sequence. Not less than 21 times of running debugging are carried out to ensure that the average time from data collection to carbon evaluation report issuance is ≤2.45 days, and the final output is a carbon evaluation report.

2. The method of claim 1, wherein, The data label of the material carbon emission reduction contribution report is based on a quantitative model E=E 投资占比 *E 贡献力 , and the label includes the total investment amount of the provincial company in the current year, the investment amount of the batch of materials, and the "double carbon contribution" emission reduction amount of the provincial company in the year to which the batch of materials belongs. Wherein E 投资占比 (unit tCO2), E 贡献力 is the percentage of the investment amount of the batch of materials to the total investment amount of the provincial company in the current year, and E contribution is the "double carbon contribution" emission reduction amount of the provincial company in the year to which the batch of materials belongs.

3. The method of claim 1, wherein, The data label of the carbon emission reduction compliance ability report includes the cooperation starting year, the cumulative bid year, the number of bids in X years, the order execution in X years, the bid amount in X years, the supply order amount in X years, the historical punishment in the past three years, the punishment subject in execution, and whether it is listed on the blacklist. "X years" correspond to the past three years and one period (the business occurred in the current year and the previous three years).

4. The method of claim 1, wherein, The data label of the enterprise carbon capacity report includes the enterprise's clean energy annual self-use power, the enterprise's annual total power consumption, the enterprise's clean energy annual on-grid power, the enterprise's annual total power generation, the number of times of overdue electricity charges in the past two years, the number of times of default electricity, the number of times of default electricity theft, the bad or punishment record label, the supplier's order amount ranking in the province in the past year and the past three years, the enterprise's clean energy power consumption, the industry's clean energy average power consumption, the industry's power consumption, the longest overdue amount and the cumulative overdue amount of the enterprise in the past 24 months, and the total amount of electricity charges that the enterprise should pay.

5. The method of claim 1, wherein, The index definitions of the six data quality evaluation systems are as follows: the missing rate is the proportion of missing data records in the total number of checked data records, the fluctuation rate is the proportion of the total number of checked data records in the ring ratio increase or decrease, the null value rate is the proportion of null data fields in the total number of checked data fields, the error rate is the proportion of fields with incorrect values or contents in the total number of checked data fields, the repetition rate is the proportion of data with repeated primary keys in the total number of checked data, the number of rule violations is the total number of data records or fields with consistency problems, the qualified rate is the proportion of fields with qualified length, format and precision in the total number of checked fields, and the timely rate is the proportion of timely output data in the total number of checked data.

6. The method of claim 1, wherein, In the out-of-domain process of the data transaction platform, the data product listing includes three core links of registration, listing and transaction: the registration link needs to submit materials such as legal person qualification certificate and data source legality certificate and be audited and publicized; the listing link needs to input product basic information, set charging information and supplement application scenario cases; the transaction link needs to complete subject identity audit, sign a record contract, platform certification settlement and data delivery.

7. The method of claim 1, wherein, In the operation and debugging module, the average time for data collection is controlled within 0.4 days, the average time for data audit is controlled within 1.5 days, and the average time for report issuance is controlled within 0.5 days. For the situation that the cumulative time exceeds 2.5 days, the key points are identified and improved.

8. The method of claim 1, wherein, The industry standards include "DAMA Data Management Knowledge System Guide" and "Banking Financial Institutions Data Governance Guidelines", and the leading technology enterprise practices include the data quality control experience of Huawei, Alibaba and ByteDance.

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