BIS Bulletin Proposes Revamping Crypto AML Measures With Compliance Scores

The paper, issued by BIS economists, proposes using blockchain as a transaction history to overcome the limitations faced by current AML measures when dealing with decentralized assets, such as cryptocurrencies and stablecoins, in order to protect off-ramping institutions.

BIS Bulletin Proposes Using Blockchain History to Build Crypto AML Score

The expansion of cryptocurrency and stablecoins is prompting traditional finance institutions to implement new concepts to prevent their usage for illicit purposes. A new paper issued by the Bank for International Settlements (BIS) economists proposes using blockchain to determine an anti-money laundering (AML) score for each crypto address, helping institutions deal with compliance concerns.

The bulletin, titled “An approach to anti-money laundering compliance for cryptoassets,” comments on the inefficiency of current methods to assess whether crypto funds are illicit or not, given their reliance on decentralized, undetermined operators, like validators or miners, to move these funds.

Economists call for using the same structure that makes cryptocurrency immune to traditional AML approaches for assessing the risk associated with dealing with a specific wallet address or transaction.

“As the full history of transactions on the blockchain is publicly available, it could inform an assessment of how closely a particular unit of a cryptoasset is associated with past or current illicit activity,” the bulletin highlights.

The referred AML score could be issued regarding this transaction history. The AML score would be generated on a 0 to 100 point scale, with addresses holding 100 points being the cleanest and 0 being the riskiest. This would help banking platforms used as off-ramps (points where crypto is exchanged into fiat) assess whether they should complete the requested transactions or refuse interaction with a flagged address.

The paper explained:

Different institutions would have differing tolerances for higher-risk addresses depending on their operational principles, jurisdiction, and regulatory frameworks. For example, a store selling gift cards would have a higher tolerance than a bank offering investment options in crypto.

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