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How to use Crypto Transaction Monitoring?

AI-based Transactions Monitoring allows CeFi business to fulfill regulatory requirements. It allows DeFi Dapps to choose which addresses can interact with Dapp.

Crypto Transactions Monitoring

Crypto Transaction Monitoring is a regulatory requirement for all Virtual Asset Service Providers. It means verifying all platform incoming and outgoing transactions and preventing fraudulent accounts from participating in business transactions.

Transaction monitoring is implemented in traditional finance via Artificial Intelligence; the AI algorithms need a lot of data—addresses, credit card histories, account histories, device databases, etc.

In the blockchain industry, however, we have only the blockchain address. All the enriched data that is available in traditional finance - all this data is missing in the crypto sector.

AI-based Crypto Fraud Score enables Transaction Monitoring for the CeFi (Centralised Finance) companies:

  • CeFi companies can use https://swagger.chainaware.ai in the subscription model

  • This real-time API should validate all transacting addresses (incoming or outgoing).

  • If addresses are flagged as potential fraud addresses, then additional verifications (sometimes manual verifications are required).

AI-based Crypto Fraud Score enables Transaction Monitoring for the DeFi (Decentralized Finance) companies:

  • DeFi companies can subscribe to https://swagger.chainaware.ai

  • Validate the user addresses when they connect to your Decentral Application with this real-time API

  • If addresses are flagged as potential fraud addresses, then do not allow the address to connect via Web3 API

SmartCredit.io has integrated AI-based transaction monitoring:

  • All addresses that connect to the platform are analyzed with the AI-based Crypto Fraud Score API (https://swagger.chainaware.ai )

  • If the address is classified as a potential fraud address, then the business transactions - like borrowing, lending, staking, or fiat conversion - are not enabled for the respective address

What is the predictive power of AI-based Crypto Fraud Score?

The current predictive power of AI-based Crypto Fraud Score is 98%. This means the algorithm correctly predicts 98 cases of 100 fraud. It's not a forensic algorithm based on already listed "bad" addresses or other forensic analytics outputs, but it's a predictive algorithm based on the address interaction patterns.

What data is the AI Algorithm using?

Crypto Fraud Score is calculated only based on the transaction history. It supports Ethereum, Polygon, and Binance Smart Chain.

How can we predict the future?

Every scam is different; there are unlimited potential scams or frauds. But scammers are using specific interaction patterns stored in their transaction history on the blockchain. Our artificial intelligence modules identify these interaction patterns and forecast the future behaviors of the addresses based on past interaction patterns.

Further info

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