New York-based LiquidityBook is introducing a trade-matching engine that is scheduled to be rolled out in Q1 2021.
Shawn Samuel, CTO at LiquidityBook, says the vendor has released a beta version of the tool to several clients. “Most of our clients are integrated into Omgeo or another trade-matching service, for which we do all the integration,” Samuel says. “But we are rolling out our own FIX-based trade-matching system as a standalone product over the next five or six months.”
LiquidityBook is primarily targeting buy-side customers, but is also introducing a sell-side version.
The system will be a feature of the vendor’s flagship LBX platform, a portfolio, order and execution management system that serves the buy side and the sell side, and offers an outsourced trading component. LBX also provides FIX network connectivity, compliance, and pre- and post-trade processing solutions, delivered via the Amazon Web Services (AWS) cloud.
The new trade-matching system is built on the same core technology as the rest of LiquidityBook’s products, also leveraging AWS and open-source technologies such as the Java programming language and database service MySQL.
Samuel says that having trade matching native to the vendor’s wider software offering means that clients can speak to a single counterparty if there are reconciliation issues, rather than having to go to multiple parties. He adds that the new system will also make onboarding clients easier, as they will not have to contact a separate provider for trade matching.
The system will be offered as a customizable tool for clients. Samuel says a user “will be able to drag and drop their trade confirmation widgets into their overall dashboard, will be able to mix and match to build a dashboard, or [create] a work surface that is tuned to their workflow needs.”
Last year, the vendor updated its dashboard to be more customizable, with components now appearing on the user interface as widgets that can be dragged and dropped. The aim was for users to have more control over how they interacted with the platform, especially as users were working with multiple screens. For example, different communities of users have different needs: a portfolio manager at a large asset manager has very different requirements to a hedge fund trader who needs to optimize trading around small-cap equities. And so, rather than building a lot of custom screens, the vendor decided to build the customizable dashboard capability.
“It came from onboarding clients: seeing the best of their other, old systems and realizing that the best way to meet [client needs] was with a system that could be designed on a per-client basis with drag and drop, rather than having 5,000 permutations of the screen,” Samuel says.
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