Bloomberg has continued the integration of its trading automation offering into the buy-side workflow, launching an auto allocation capability. Philippa Thompson and Chris Clodius speak to Global Trading about how this service helps to reduce T+1 stress and why automating just part of the workflow is not enough.
“Historically, we’ve had one main automation focus at Bloomberg,” says Philippa Thompson, global head of buy-side order management product at the firm. “Chris [Clodius, global head of buy-side trade automation] and his team have historically been focused on trading execution, which continues to be an important offering for our customers and an important focus. We’ve now shifted to also provide automation capabilities in other areas of the order lifecycle, like releasing the execution to the post-trade space.”
In between those two points is a somewhat neglected space when it comes to automation: allocation. This crucial part of the trading lifecycle is particularly important in markets that require fair allocation, with firms “required to make sure that they are being fair to all of the underlying representative clients that have been participating in that particular order.“
Automation in this area “is something that clients have been looking for for a while, but was really accelerated by the change in the US market to T+1,” Thompson continues. Bloomberg clients were nervous as the US headed into a shorter settlement cycle, particularly given the firm’s global footprint. “We have a lot of clients who sit in Asia, and this change essentially meant that they lose an entire day to meet timeframes around post-trade workflow,” she explains.
Bringing traders into the office once US markets close – at five in the morning, local time – to complete the allocations workflow was not a particularly attractive option. To remedy the issue, “we were able to offer a rules-based conditional allocation, using our Rule Builder technology that has historically been used for our trading execution”, Thompson says. “Rule Builder understands necessary order management information about the trade and the trade object, and uses that rules-based engine to allow our clients to be able to configure their own rules.”
She continues: “For example, if I do an equity trade and it gets fully filled then I would automatically kick off this post allocation workflow and allocate that price and that quantity back to my target funds.”
“There’s a bit of a feeling from the trader that ‘once my trade is done, then I’m good to go’,” says Thompson, considering why the allocation space has been underserved. “But what happens to the trade next is actually a really critical component of the workflow, and can have financial implications if something fails, or isn’t done in a timely manner,” she warns. With T+1, time is against clients. Automation is key to reduce operational risk, improve communication between teams and make the handoff of the trade from trader to operations more efficient.
“Post-trade allocation, which is a very manual task today, shouldn’t be,” Clodius affirms. However well automated the majority of the trading workflow is, having it remain manual at the end “half defeats the purpose of automation”, he notes. “We are trying to help our clients reduce their number of clicks and the more operational tasks, and provide them with tools to help them with their operations.”
Since its launch, 50 firms have adopted Bloomberg’s rule-based allocation service, the company stated. Over the last 10 days, an average 4600 allocations were completed each day using the solution.
Phoebe Nockolds, senior trader at Independent Franchise Partners and end-user of the service, commented: “At Franchise Partners, we are always looking for ways to harness new technology to deliver better outcomes for our clients. Bloomberg’s automation tools fall firmly into this bracket, helping to ensure that our trades are booked in a consistent manner thus allowing us to focus on value-add tasks.”
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