Credit data storage method and device based on block chain, equipment and medium

Abstract

The invention relates to the technical field of computer software, in particular to a credit data storage method and device based on a block chain, equipment and a medium, and the credit data storagemethod based on the block chain comprises the steps: S10, obtaining credit data of each node on an alliance chain; S20, obtaining a data chaining template, and extracting credit metadata from the credit data according to the data chaining template; S30, calculating the credit metadata by using a hash algorithm to obtain a corresponding data fingerprint; and S40, calculating a current timestamp, taking the current timestamp and the data fingerprint as credit blocks, and storing the credit blocks on the alliance chain. The method has the effect of improving the data richness of the credit investigation system.

Description

technical field [0001] The present invention relates to the technical field of computer software, in particular to a blockchain-based credit data storage method, device, equipment and medium. Background technique [0002] At present, the corporate and personal credit information system is the basic database of financial credit information, also known as the basic database of corporate and personal credit information. Formed a credit investigation product system centered on corporate and personal credit reports, the credit reports issued by the credit investigation center have become the "economic identity card" of domestic enterprises and individuals. [0003] The existing credit information system still faces the following defects: [0004] 1. The problem of isolated islands of information is serious, data is not shared, and there is no effective sharing and cooperation between credit agencies and agencies, so that high-quality data cannot be used to play a role; relevant ...

AI Technical Summary

Problems solved by technology

[0004] 1. The problem of isolated islands of information is serious, data is not shared, and there is no effective sharing and cooperation between credit agencies and agencies, so that high-quality data cannot be used to play a role; relevant agencies do not want to share their own data, but need to obtain third-party data;

[0005] 2. The competition for data sources consumes a lot of cost. Traditional credit agencies actively connect with relevant departments and institutions through self-climbing, cooperation, and purchases, and integrate data from limited scenarios to seize the high ground of data;

[0006] 3. The ownership of user data is not clear, and due to the consideration of user privacy and security, it is difficult for data to circulate and maximize its value;

[0007] 4. Data privacy protection is also facing important problems. The traditional credit system architecture pays little attention to users and cannot guarantee users' data sovereignty from the bottom of the technology;

[0008] 5. There are too few data, the quality is too poor, and the correlation with credit is too low, making it difficult to accurately judge user credit;

[0009] 6. In addition to personal credit, corporate credit is a serious problem. Corporate credit is more difficult to assess than individuals, and the lack of corporate credit information is even more serious.

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