Matthew Cheung

DB & Nethermind - From Wallet to Chain This joint whitepaper by Nethermind and Deutsche Bank bridges blockchain’s decentralization ethos with the regulated industry’s need for clarity in addressing shared challenges including fraud, inefficiencies, and mistrust. Using Ethereum as a reference public chain, it examines how blockchain attributes can align with compliance, governance, and operational resilience standards expected in regulated financial markets. Ethereum’s core principles include decentralization and resistance to censorship, collusion, and dominance which are essential elements of its operational resilience in a trustless public environment. These approaches should be viewed as complementary to, rather than opposing, traditional regulatory goals like market integrity and governance. Both worlds ultimately aim to create healthy, vibrant markets that serve users effectively. While their methods differ, they share similar objectives and visions of fairness.

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Andrew Bailey’s softer stance on stablecoins is an important signal. It shows UK policymakers are finally starting to see what innovators and businesses already know: stablecoins can coexist with banks and broaden access to money and payments. Rezolve Ai's initiative with Tether.io demonstrates the power of stable digital money to drive trust, efficiency, and innovation. The challenge now is turning regulatory openness into a framework that lets the UK lead. Exciting times. #RezolveAi #AI #CryptoPayments #Stablecoin #Tether #Fintech $RZLV

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2025 promises to see much greater investor participation in the digital asset class beyond bitcoin and ether. But how will investors be able to translate their views of how the public blockchain space will evolve (the use cases and hence software protocols that will thrive) into portfolios of tokens? CF DACS from CF Benchmarks will guide investors through the blockchain economy:

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A new Dune Analytics report reveals that African users, particularly Nigerians, are the most prominent users of several major crypto wallets, including Zerion and MetaMask. Highlights: 🟠 Wallet ownership is high 🟠 Transaction activity is low 🟠 Wallet balances are even lower on average We dug into the report at Mariblock and spoke with local exchanges and builders to gain context. VALR and Quidax say low incomes and high inflation limit sustained engagement. But it’s not just about income levels. It’s also about how people use crypto. As Harrison Obiefule from Superteam Nigeria put it: “Most of the activity is in rapid, utility-driven trades … not long-term holdings.” 🔗 Link to the full piece is in the comment section.

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Greetings from Dubai and TOKEN2049, I want to highlight three items: 1) Great article out from MIT's CS AI lab. See the link below. https://bit.ly/44Jbz6C 2) J.P. Morgan CiSO just put out an open letter to third party vendors on security. This is a critical item that must be addressed as more and more data is being created, it lives at the edge, and what is at the edge is getting smarter. This is the intersection of ai and dlt. https://bit.ly/4cSCgaZ 3) Schroders published a great research article, that I did not agree with a number of their points, but their focus on private equity, smaller private equity targets, the need for price discovery, and that AI remains attractive. I would argue these two thesis will feed each other. https://bit.ly/4kekTEn The next generation of Private Markets will be data driven, decentralized, and agentic. In this high volume data environment you need an immutable ledger to create the audit trail for agents and a tool for agents to reference and prove, proof of origin of data, proof of state of data, and proof of process of data. This decentralized data architecture using zk proofs is how #2 and #3 connect. With this addition of #1 we begin to see a world where asset owners control their own data, have valuable unstructured data that provides the context for AI to understand the assets, and the ability for adversarial agents and methods to double check the work. The outputs of AI can cite the source data, with context, has an audit trail, and with this produce commercially reliable outputs. This will allow the next generation of private markets to be data driven, auditable, transparent, and decentralized. Real time, or near real time agentic survellience of assets will allow you to understand the Gross Asset Value, run a water fall, calculate the carry, allocate expense, and price the capital stack on an automated basis, with full audit trail and can be re-run daily, or as often as new data effecting the calculation Is detected by the agent. We will have these agents in production with our clients in Q3, right now we are in beta and testing them, this is happening fast, it is the intersection of Data, DLT, and AI which will power the price discovery and trading of private market derivatives, interval funds, Actively managed private market ETFs, lending/collateralization, accounting treatment on capital reserves, secondaries, and eventually digital primary distribution. This is Private Markets Real World Asseets, or PrRWA.

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