This year’s two implementation categories—trading & risk and data & operations—are new to this year’s BST Awards line-up, introduced due to the sheer number and quality of entries to the incumbent “best implementation” category—31 entries in total. Last year’s category was won by SimCorp for its work in replacing Marathon Asset Management’s legacy reporting platform with SimCorp Coric. This year’s trading & risk implementation category goes to New York-based FlexTrade for the deployment of FlexOne, its order and execution management system developed for the buy side, at Boston-based crowd-sourced hedge fund, Quantopian.
At the time of the implementation, FlexOne was new on the market. In business since 1996, FlexTrade is best known for its execution products, underlined by its win in the best buy-side EMS category in this year’s awards (see page 46). “We always had OMS-like functionality within our EMS, more as a one-off development deliverable to clients,” explains Aaron Levine, vice president for OEMS solutions at FlexTrade. Some six years ago, FlexTrade started developing its OMS from the ground up, using Scala and Google’s gRPC for API delivery. After laying the foundation and taking on a number of partners, the product was unveiled two years ago. “At FlexTrade, we have always taken a customized approach to working with clients, doing the due diligence to break down their needs, wants and overall workflows,” says Levine.
When FlexTrade began working with Quantopian, the big unknown for it was the fund’s workflows. That led to the FlexTrade team traveling to Boston and sitting down with Quantopian’s principles, development teams and architects to better understand its technology and operational requirements. It also spent a few days running workshops to analyze the fund’s workflows. The team then returned to New York and ran development estimates and set timeframes for the implementation. The original deliverables estimate was approximately three months, start to finish.
According to Levine, the most crucial requirement Quantopian had was an open architecture that allowed for straight-through processing. Whereas many traditional clients use point-and-click trading, Quantopian wanted a purely systematic approach. Levine considers peer performance through applied latency to have been a notable driver for the platform, while having a low-latency investment process was also key for Quantopian.
An important aspect of the implementation is Quantopian’s ongoing needs after the initial go-live date, according to Levine. “Clients change and adapt over time from a peer business perspective, and that goes hand in hand with our support and implementation model,” he says. “So as a client, whether they onboard a new fund or bring on new asset classes, it kicks in and re-circles back to our implementation policies each time.”
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