Calastone Goes Live With World's Largest Financial Services Community on Blockchain

- Calastone has successfully launched its blockchain-enabled Distributed Market

Infrastructure (DMI)

- The migration sees the largest group of financial services organisations ever

to connect and transact on a live distributed ledger

- The entire global funds network of more than 1,800 customers across 41

countries and territories have been migrated onto the blockchain-based network

- The DMI enables friction-free trading, stripping out cost, risk and

operational inefficiencies

Calastone, the largest global funds transaction network, today announces the successful go-live of its blockchain Distributed Market Infrastructure (DMI).

The technology underpinning Calastone's network has now been migrated to a blockchain-enabled market infrastructure. The migration of Calastone's global network of more than 1,800 customers across 41 markets is a world-first and represents the largest community of global financial services organisations connecting and transacting via distributed ledger technology.

Less than two years since Calastone announced the completion of its first phase to test the feasibility of using blockchain to develop a common global marketplace for the trading and settlement of funds, the company's DMI is today live. This represents a major step in enabling digitalisation and friction-free trading at a significant global scale. Calastone has highlighted the scale of tangible value the DMI could bring to the industry, forecasting more than 3.4bn in savings per year for the mutual funds market worldwide, achieved through the technological mutualisation of the distribution model.

Financial services organisations around the world - whichever size and scale - can, through the DMI, now access a fully mutualised global funds marketplace whereby the trading, settlement and servicing of funds is conducted in real-time. This will play a key role in stripping out the ever-increasing costs, operational burdens and risks inherent within the current model.

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