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“Same risks, same rules”: The SEC’s selective approach to crypto regulation
August 31, 2024
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When it comes to cryptocurrency regulation, the SEC views most cryptocurrencies as securities, favoring the concept of ‘same risks, same rules’.

But is it possible it’s not being consistent itself?

The same rules aren’t being followed when it involves the custody of crypto-assets.

The notorious SEC accounting bulletin SAB 121 changes the accounting rules around the custody of crypto-assets, requiring those assets to be disclosed on the balance sheets of listed firms. That contravenes global accounting norms and has prevented banks from providing cryptocurrency custody. The SEC tries to argue that crypto-assets have elevated cyber risks.

A new heavyweight paper on crypto regulation points out that cyber risks are not new and are well covered by existing regulations. So using the principle of “same risks, same rules”, no additional cyber regulation is necessary for crypto-assets.

Yesterday Steven Schwarcz, Distinguished Professor at Duke University School of Law, published a paper on regulating financial innovation, with a focus on crypto-assets and DeFi.

We’d note that the paper does not directly mention SAB 121, so it is Ledger Insights that’s highlighting the inconsistency. However, the Professor’s cyber risks observation directly follows his discussion of the controversial application of ‘same risks, same rules’ to crypto.

A thought provoking paper on crypto regulation

Most regulations focus on the minutiae, whereas Professor Schwarcz reviews the high level models that can be used in regulating fintech innovation. ‘Same risks, same rules’ is one of six models he explores.

While some may disagree with various suggestions, regulatory clarity is necessary for new industries to flourish.

The Professor selected the salient aspects of the six models to outline a recommended framework to address fintech innovation in general. He then applies it to the crypto sector.

Sandboxes, smart contract audits (not just code)

A first step is to provide regulatory sandboxes. The Professor has a pragmatic view, recognizing that sandbox tests with a few customers won’t highlight all the potential risks.

There’s a need for fintech firms to self monitor their risks. However, that’s not likely to be sufficient, so there should be a system of third party expert monitoring.

In the crypto sector, smart contract audits are already widely used to identify bugs and qualify as a type of third party monitoring. But that only addresses one specific risk. A broader range of risks need exploring – risks to the firm and their customers, to other market participants and the public.

Plus, the automated nature of smart contracts can trigger a vicious cycle. We’ve already witnessed multiple crypto crashes and the impact on crypto lending. The liquidation of collateral leads to price declines, sparking a cascade of additional liquidations.

Stopping a crash

In traditional finance (TradFi) these sorts of issues exist in high frequency trading, where suspending trading helps to address the risk. However, the Professor recognizes that would be tricky to enforce in the crypto sector.

Hence, he recommends that businesses identify their counterparties and disclose the risks to them. If a third party monitor finds the firm’s smart contract usage creates significant risk, then “Regulators should have the power to suspend a business’s right to enter into new smart contracts.”

In other words, if you can’t stop a crash by suspending trading, then try to prevent it from happening in the first place. Although both are desirable.

One can imagine that the suggestion would cause the crypto sector to be up in arms, but it has merit, provided it’s not overused and one appropriately defines ‘significant risk’. TradFi has standard approaches to risk management which can be tweaked and ported to the crypto world. The more responsible players already do this.

For example, we’re aware of at least one exchange that saw the Terra Luna collapse unfolding early on, because they had systems in place. Hence, they protected their clients, although arguably their reaction exacerbated the downward spiral.

DeFi regulation

The Professor’s approach to DeFi resembles discussions already taking place about how to identify responsible people, with holders of governance tokens being one avenue.

An alternative option is to require DeFi platforms to be “provided by centrally registered and well capitalized entities.” At the same time, he acknowledges that could nullify DeFi benefits (low costs), so suggests consulting the DeFi industry before taking steps in this direction.

Regarding crypto-assets, he observes that some have proposed the financial equivalent of the FDA. In other words, all fintech innovations would need approval in advance. He dismisses this as an innovation killer. He wrote that this “reverses the presumption, at least in the context of new financial products, that private-sector freedom of contract produces beneficial societal outcomes”.

In the case of financial stability risks, the Professor notes that fintechs are generally too small to create stability risks. These sorts of risks come from the actions of systemically important institutions. Hence, to address this particular risk, there should be limits on them rather than fintechs.

Surprisingly, he doesn’t mention that this is the approach taken by the Basel Committee for Banking Supervision.

Given the gravitas of this paper, who knows, perhaps he was the one that suggested banks have a maximum crypto exposure of 1% of Tier 1 capital.

 

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The Great Onboarding: US Government Anchors Global Economy into Web3 via Pyth Network

For years, the crypto world speculated that the next major cycle would be driven by institutional adoption, with Wall Street finally legitimizing Bitcoin through vehicles like ETFs. While that prediction has indeed materialized, a recent development signifies a far more profound integration of Web3 into the global economic fabric, moving beyond mere financial products to the very infrastructure of data itself. The U.S. government has taken a monumental step, cementing Web3's role as a foundational layer for modern data distribution. This door, once opened, is poised to remain so indefinitely.

The U.S. Department of Commerce has officially partnered with leading blockchain oracle providers, Pyth Network and Chainlink, to distribute critical official economic data directly on-chain. This initiative marks a historic shift, bringing immutable, transparent, and auditable data from the federal government itself onto decentralized networks. This is not just a technological upgrade; it's a strategic move to enhance data accuracy, transparency, and accessibility for a global audience.

Specifically, Pyth Network has been selected to publish Gross Domestic Product (GDP) data, starting with quarterly releases going back five years, with plans to expand to a broader range of economic datasets. Chainlink, the other key partner, will provide data feeds from the Bureau of Economic Analysis (BEA), including Real Gross Domestic Product (GDP) and the Personal Consumption Expenditures (PCE) Price Index. This crucial economic information will be made available across a multitude of blockchain networks, including major ecosystems like Ethereum, Avalanche, Base, Bitcoin, Solana, Tron, Stellar, Arbitrum One, Polygon PoS, and Optimism.

This development is closer to science fiction than traditional finance. The same oracle network, Pyth, that secures data for over 350 decentralized applications (dApps) across more than 50 blockchains, processing over $2.5 trillion in total trading volume through its oracles, is now the system of record for the United States' core economic indicators. Pyth's extensive infrastructure, spanning over 107 blockchains and supporting more than 600 applications, positions it as a trusted source for on-chain data. This is not about speculative assets; it's about leveraging proven, robust technology for critical public services.

The significance of this collaboration cannot be overstated. By bringing official statistics on-chain, the U.S. government is embracing cryptographic verifiability and immutable publication, setting a new precedent for how governments interact with decentralized technology. This initiative aligns with broader transparency goals and is supported by Secretary of Commerce Howard Lutnick, positioning the U.S. as a world leader in finance and blockchain innovation. The decision by a federal entity to trust decentralized oracles with sensitive economic data underscores the growing institutional confidence in these networks.

This is the cycle of the great onboarding. The distinction between "Web2" and "Web3" is rapidly becoming obsolete. When government data, institutional flows, and grassroots builders all operate on the same decentralized rails, we are simply talking about the internet—a new iteration, yes, but the internet nonetheless: an immutable internet where data is not only published but also verified and distributed in real-time.

Pyth Network stands as tangible proof that this technology serves a vital purpose. It demonstrates that the industry has moved beyond abstract "crypto tech" to offering solutions that address real-world needs and are now actively sought after and understood by traditional entities. Most importantly, it proves that Web3 is no longer seeking permission; it has received the highest validation a system can receive—the trust of governments and markets alike.

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US Dept of Commerce to publish GDP data on blockchain

On Tuesday during a televised White House cabinet meeting, Commerce Secretary Howard Lutnick announced the intention to publish GDP statistics on blockchains. Today Chainlink and Pyth said they were selected as the decentralized oracles to distribute the data.

Lutnick said, “The Department of Commerce is going to start issuing its statistics on the blockchain because you are the crypto President. And we are going to put out GDP on the blockchain, so people can use the blockchain for data distribution. And then we’re going to make that available to the entire government. So, all of you can do it. We’re just ironing out all the details.”

The data includes Real GDP and the PCE Price Index, which reflects changes in the prices of domestic consumer goods and services. The statistics are released monthly and quarterly. The biggest initial use will likely be by on-chain prediction markets. But as more data comes online, such as broader inflation data or interest rates from the Federal Reserve, it could be used to automate various financial instruments. Apart from using the data in smart contracts, sources of tamperproof data 👉will become increasingly important for generative AI.

While it would be possible to procure the data from third parties, it is always ideal to get it from the source to ensure its accuracy. Getting data directly from government sources makes it tamperproof, provided the original data feed has not been manipulated before it reaches the oracle.

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