ECB tests blockchain, multiparty computation in enabling liquidity matching

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The European Central Bank (ECB) has been experimenting with the adoption of blockchain technology in multiparty computation (MPC) to enable liquidity matching.

A few years ago, the ECB contacted an academic team at KU Leuven to independently explore the feasibility of liquidity matching. Recently, the ECB completed a blockchain experiment for its central bank digital currency (CBDC), the digital euro.

Speaking at the FHE Summit in Brussels on July 10, Zama’s Chief Academic Officer, Nigel Smart, told attendees that the firm had collaborated with the ECB on a test project.

“We did one with the European Central Bank on liquidity matching,” said Smart. “And a number of applications on CBDCs have been actually to remove the central bank out of the equation and replace it with a blockchain.”

Liquidity matching refers to the process of aligning cash inflows with cash outflows to ensure a company has enough funds to meet its short-term obligations, which helps avoid cash shortages or surpluses, and promotes financial stability and efficiency.

This process can be a challenge for multiple parties transacting on the same blockchain network.

“Then the issue is if you have multiple entities on the blockchain and it’s all encrypted stuff, how do you do liquidity matching? That’s a really big issue,” explained Smart.

This is where FHE and MPC—which enable multiple parties to share data for computing without revealing the actual data—come into the picture.

FHE is a technology that enables processing data without decrypting it, which means companies can offer their services without ever seeing their users’ data.

Zama works in this field and, in March, secured a $73 million Series A funding round to “bring FHE to the fore, and give developers tools to tackle data privacy challenges across blockchain and AI use cases.”

The company’s chief academic officer, Smart, revealed that in the firm’s recent MPC experiment with the ECB, it put its FHE expertise into practice on a large scale and to great success:

“We did an experiment with the European Central Bank where we essentially ran the Finnish economy through an MPC engine, and we could keep track. We could actually keep up with Finland.”

This is a substantial achievement for the technology, but there is still work to be done if such a system were to be implemented EU-wide. As Smart pointed out, the test and result were “good, but not on the European scale yet.”

However, he added that in terms of leveling up, the financial sector is increasingly exploring MPC technology, which could bring more use cases to other large financial institutions.

Editor’s Note: This article has been updated to correct the error that KU Leuven, not Zama, independently led the liquidity matching experimentation.

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