Blockchain-based enterprise green credit checking method and system

By combining blockchain technology and encryption algorithms, the problems of data tampering and insufficient transparency in traditional green credit verification have been solved, achieving efficient and reliable green credit scoring and transparent recording of corporate environmental performance, thus improving the accuracy and fairness of credit scoring.

CN120258961BActive Publication Date: 2025-11-04BEIJING MUNICIPAL RES INST OF ENVIRONMENT PROTECTION
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Patent Information

Application Number
CN202510325970.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-03-19
Publication Date
2025-11-04
Estimated Expiration
2045-03-19

AI Technical Summary

Technical Problem

Traditional green credit verification relies on manual recording and centralized databases, which are prone to data tampering and lack of transparency, making it difficult to ensure the fairness and reliability of the data and affecting the accuracy and impartiality of green credit scoring.

Method used

Blockchain technology is used for data storage, and multiple verification mechanisms are used to ensure the authenticity and integrity of the data. Encryption algorithms are used to protect the data during the on-chain process, and multiple on-chain time windows are set for dynamic monitoring to identify and correct early signs of insufficient data quality. Convolutional neural networks are used for green credit scoring.

Benefits of technology

This improves the accuracy and fairness of green credit scoring, ensures the immutability and transparency of data, enhances the credibility of corporate environmental performance, and promotes corporate environmental responsibility.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a blockchain-based enterprise green credit checking method and system, and particularly relates to the technical field of blockchains. First, green behavior data is collected from data sources of multiple enterprises, initial data is obtained by summarizing and is subjected to authenticity and integrity checking to form a chained data collection. In the chaining process, chained information is obtained and a chained time window is analyzed to determine whether there are early signs of insufficient data quality. If insufficient quality is found, feature extraction is performed on the chained time window, the efficiency and resistance of the encryption algorithm are analyzed, and the time window is divided into a high-quality or low-quality window through fuzzy logic reasoning, and the low-quality window data is re-chained. Finally, the enterprise is given a green credit score through the high-quality chained data. The application can detect potential problems in data transmission and encryption in advance, automatically re-chain the window data with signs of insufficient quality, and ensure the consistency and reliability of the system data.
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Citation Information

Patent Citations

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