Noor please tell us about the key products and services that Tradepoint currently offers?
Tradepoint delivers FX front-office solutions to help its clients with their trading and market making objectives. On the sell-side, this includes both making prices for and monetizing order flow from their customers,. On the buy-side, this is all about intelligent execution. In all cases, there is substantial underlying logic between the high performance market adapters and the user interfaces, and this is Tradepoint’s sweet spot: smart order routing to protect relationships and achieve best execution, complex algorithms to limit market impact, streaming and request-based market making, internalization and hedging engines, internal matching, synthetic price triangulation, core price construction, spreading and skewing engines, and so on.
What types of clients are you providing services for?
The lion’s share of Tradepoint’s customers are banks, either regional currency specialists or global tier two players. Tradepoint also has a small but growing presence on the buy side. Our customers each have their own requirements, some of which derive from their unique liquidity profiles, or their regulatory requirements, or the nature of their flow.
Clients also bring unique integration requests, wanting to keep the working parts of legacy systems even as they upgrade, and often wanting to work their own ideas (even IP) into the overall solution. In addition to a mature technology stack, Tradepoint is often selected for its flexibility: we can deliver just those parts the client needs.
Tradepoint’s customers are mainly banks
Last year you launched a new product that employs a flat-rate charging model to challenge the FX market algorithm space. How does that work and what benefits does it provide?
This proposition actually originated in 2016 with a buy-side customer who approached us! They realized they could see significant cost savings without loss of functionality by using Tradepoint’s algorithms with a fixed price model instead of bank algorithms with a brokerage model.
At their volumes, it was a no-brainer, and with their help, we built out our algorithms with all the functionality the buy-side could want. This evolution of our algorithmic offering timed nicely with a market trend whereby tier two banks were aiming to provide algorithmic services to their clients, a business that had historically been exclusive to the largest tier one banks.
Our bank-customers see this as a means to protect their existing relationships and find risk-free brokerage-based revenue.
How important has collaborating with your clients been in helping you to develop FX algo products?
It’s been absolutely critical. Keep in mind that the Tradepoint leadership team has been working in FX for decades, so it’s not our first rodeo, but the mentality of the team, the mantra which drives our development cycles, is that whatever one of our customers wants, another customer will need. So we listen closely to our customers and let them tell us what gaps they need filled.
In the algorithm space, this has been especially true. For example, first we built a standard TWAP. Our clients drove us from there to a curve-based model, then pushed us towards more passive market participation. And it only got more sophisticated from there.
Algorithmic Logic and Smart Order Router Hierarchy
We are starting to see greater use of algos to trade NDFs. How has Tradepoint responded to this demand?
I love this question because it’s one of those cases where it seems like we’re on the cutting edge, and sometimes we get to educate our customers about market opportunities available to them which they didn’t yet know about. Tradepoint is one of the first vendors to certify a full range of streaming NDF products, including all tenors and broken dates, with a dozen or so liquidity providers.
With the increasing automation in the market pushing into NDF territory, LPs who really want to compete for the flow have to offer streaming products now. And once we’re in the streaming world, all the same algorithmic strategies work for NDFs.
Tradepoint offers an Algorithm Container. Please tell us more about that and the toolsets that it offers?
When we started writing algorithms, we made one critical decision for the sake of transparency: we split our team down the middle.
One half wrote a container and an algorithm API, and the other half wrote the algorithms. That enabled us to offer our algorithms open source, against our container’s API, so our customers would always know exactly how our algorithms work.
As a happy side-effect, we found that our customers claimed significant value in the container itself, leveraging it to write their own algorithms. Over time, we’ve seen a pattern emerge: many customers interested in writing “top-level” controller algorithms that rely on our algorithms for market interaction, getting them to market very quickly.
What new products and services can we expect to see this year from Tradepoint?
I’ll give one hint: AI and adaptive algos are very hot right now, and we’ve recently added some relevant quantitative talent to the team…
