Cryptographic Wallet Risk Scoring for Regulatory Compliance
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Solution Overview
Problem
The distributed nature of cryptocurrencies like Bitcoin and Ethereum makes it difficult for regulatory bodies to comply with laws and identify criminal activities, as transactions are anonymous and lack real-time verification, leading to potential money laundering and funding of criminal activities.
Innovation Solution
Implementing a cryptographic coin with data structures that enable compliance by using Walletscore to measure and monitor wallets' propensity for criminal activity, allowing exchanges and platforms to quarantine risky wallets and prevent transactions with them, while propagating risk scores to determine quarantine decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If cryptocurrency transactions use anonymous addresses, then user privacy is protected, but regulatory compliance and criminal activity detection become difficult
Solution Approach 1:
The patent introduces Walletscore as an intermediary mechanism that mediates between transaction anonymity and regulatory compliance. Instead of directly exposing user identities, the system uses score propagation through wallet interactions to indirectly indicate risk levels, allowing regulators to detect criminal activity without compromising the fundamental anonymity of cryptocurrency addresses
Solution Approach 2:
The system transforms the static anonymous address into a dynamic entity with a risk score parameter. By calculating and propagating Walletscores based on transaction patterns and wallet interactions, the system adds a new dimension (risk assessment) to anonymous addresses, enabling detection of criminal activity while preserving address anonymity
2Reliability
If all wallets are monitored for criminal activity, then regulatory compliance improves, but system complexity and computational resources increase
Solution Approach 1:
Instead of implementing comprehensive monitoring of all wallet transactions with equal depth, the system applies partial action by using score propagation that naturally prioritizes high-risk wallets. The Walletscore mechanism allows regulators to focus monitoring resources on wallets with higher risk scores, reducing overall system complexity while maintaining effective compliance
Solution Approach 2:
The system performs preliminary risk assessment by calculating Walletscores before transactions occur. This preliminary action allows exchanges and platforms to pre-identify risky wallets and implement compliance measures in advance, reducing the need for complex real-time monitoring of all transactions
3Object-affected harmful factors
If risky wallets are quarantined to prevent criminal activity, then security against money laundering improves, but transaction speed and user convenience decrease
Solution Approach 1:
The system implements preliminary quarantine decisions by calculating Walletscores and identifying risky wallets before transactions are processed. Exchanges and platforms can pre-block transactions with high-risk wallets, preventing money laundering attempts while allowing normal transactions to proceed without interruption, thus maintaining transaction speed for legitimate users
Data Source
AI summary
A method for detecting and tracking tainted cryptographic wallets. The method measures a wallet's propensity to engage in criminal or suspicious activity. Naturally, transacting with a criminal is tantamount either to funding crime or laundering its proceeds, so it is in our collective interest to identify—and then monitor or quarantine—any wallet with criminal association. The method also automatically flags risky withdrawal requests in real-time for further review before committing them to the blockchain. In some embodiments, the exchange can quarantine wallets at a certain Walletscore.