Anti-money laundering list sharing system and method based on blockchain

Abstract

The invention provides an anti-money laundering list sharing system and method based on blockchain. The system comprises a master node and at least two slave nodes, wherein each node comprises a management platform and a blockchain platform; the management platform comprises a MySql database server, a Redis database server, an application server and a Web server, wherein the Web server is connected with the application server, and the application server is connected with the MySql database server and the Redis database server; the blockchain platform comprises an Apiserver middleware and a Fabric framework, wherein the Apiserver middleware is connected with the Fabric framework. A sharing mode of decentralized operation is adopted, a data center does not need to be built, the operation andconstruction cost is reduced, encryption and desensitization processing is adopted for data related to personal information, and the risks of illegal use, personal information data providing and personal information data leakage are reduced.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a blockchain-based anti-money laundering list sharing system and method. Background technique [0002] Under the existing financial system, there are few information exchange channels between financial institutions, and there is a lack of effective anti-money laundering cooperation mechanism, which is not conducive to the analysis and screening of suspicious transactions. In the current illegal and criminal activities such as money laundering, terrorist financing, and tax evasion, the internal division of labor of criminal gangs is often very clear. Criminals open multiple accounts in multiple financial institutions and use the accounts of different financial institutions to handle money laundering. of different parts. At present, various financial institutions do not share information on key suspicious transaction reports and customer assessments of money laundering risk...

AI Technical Summary

Problems solved by technology

Although financial institutions can detect suspicious clues in time in abnormal links with obvious money laundering characteristics, when the money laundering characteristics are not obvious, financial institutions often face many difficulties in the analysis and identification of abnormal transactions, such as transaction chain breaks, key Insufficient information about sex etc.

[0003] On the other hand, using traditional database technology to achieve anti-money laundering watch list sharing usually requires a centralized operating organization to build a data center. This centralized data storage method will result in list data being controlled by a few institutions

Once the data is arbitrarily tampered with, the data quality cannot be guaranteed

At the same time, multiple firewalls and other high-security measures are required to protect data from hackers, and its operating costs are extremely high. Once a security hole is breached, the loss will be difficult to estimate, and it will take a lot of manpower to update and maintain the database. Significantly increase the cost of data acquisition by agencies

In addition, the storage and management methods of large or suspicious customer identity data and transaction records of various institutions are relatively independent, and the data quality and security are uneven. It is difficult for the regulatory authorities to achieve a higher level of unified supervision.

Images