BIS Calls Blockchain Indicators 'Noise' Rather Than Accurate Metrics. Why?

The Bank for International Settlements (BIS) has published a report on measuring real economic data in public blockchains. The authors of the study stated that the scale, fragmentation, and complexity of the ecosystem hinder the acquisition of objective economic indicators for the cryptocurrency market. The 26-page document is available on the BIS website.

<<The findings suggest that blockchain indicators should be viewed as approximate data containing noise, rather than as direct indicators of economic activity>>, wrote BIS analysts.

Their research utilizes data from the Mercurius platform, developed by De Nederlandsche Bank (DNB) in collaboration with the BIS Innovation Hub and Deutsche Bundesbank. The platform processes complete data from Bitcoin, Ethereum, and Tron network nodes—totaling 100 billion records.

Despite the open nature of information recording in blockchains, the conclusions heavily depend on the methodological choices and assumptions of the analysts, experts believe. The BIS also highlighted structural data sources where measurements often vary: Bitcoin transactions, decentralized finance, and assets across multiple networks.

Bitcoin Transactions

In the Bitcoin blockchain, there are no conventional account balances. Instead, balance records are stored in so-called unspent transaction outputs (UTXO). When a user sends Bitcoin to someone, the transaction often creates two outputs: one for the recipient and another that returns to the sender as <>.

If all transaction outputs are counted as transfers, the volumes are artificially inflated. The BIS study also provided an example where the cost of Bitcoin transactions can differ by up to six times depending on the counting method.

The charts show average monthly values of daily transactions. The left panel shows Bitcoin transferred in millions, while the right shows Bitcoin transferred in US dollars. An example of three different methods for calculating Bitcoin transfer volumes (lines of different colors). Data: BIS

Market capitalization is also sensitive to assumptions: whether to account for lost coins or to assess capitalization based on prices at the time of the last Bitcoin movements (realized). During price increases, simple capitalization reached four times the realized value, significantly distorting the assessment, experts write.

Smart Contracts

Classifying and identifying economic activity requires careful technical analysis at scale, according to BIS. They classified 13 million active smart contracts based on common technical standards, while 54 million smart contracts remained unclassified.

Token issuance on Ethereum is vast, but real activity is concentrated in a small number of projects, the authors write. About 1.4 million smart contracts issue tokens, but most transfers and trades on decentralized exchanges are concentrated in just a few of them.

Moreover, the same token designations are often reused. For example, USDT appears in approximately 7,000 different contracts that mimic the issuance contract of the largest stablecoin. Since 2020, the increase in activity with stablecoins has seemingly become one of the factors contributing to a large amount of non-substantial activity in smart contracts.

Comparability Between Blockchains

The same asset issued on different blockchains can serve different economic functions. As an example, researchers cited the stablecoin USDT, whose share among assets held in Ethereum smart contracts reached over 20% of the total capitalization. Meanwhile, in the Tron network, this figure remained extremely low—around 1%.

As researchers note, this is related to the architectural differences of the networks and the different fee structures. The activity of USDT in Tron is more associated with small transactions and indicates the use of the stablecoin for savings and storage on cryptocurrency exchanges. In Ethereum, USDT, on the contrary, is more frequently used in DeFi services, primarily for trading.

Thus, the BIS clarified that it is important for global regulators to more accurately identify assets considering the goals of the analysis. Effective use of blockchain data for monitoring financial stability, payment oversight, and monetary analysis will require more precise methodology.

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