Many trading desks face increasing pressure to make faster, better-informed execution decisions, particularly during periods of heightened market volatility. Speaking to Trader TV, Vimal Vel of IPC Systems share his views on the value of integrated data and workflows, turning counterparty information, portfolio analysis, and chat and voice communications into actionable insights that enable quicker execution and support automation. He also discusses the growing adoption of AI solutions, emphasizing the importance of a flexible, modular approach to AI-driven automation and analytics, tailored to the buy side’s existing technology infrastructure and trading strategies.
Interview
Dan Barnes – Just start with, I’d be interested to get your perspective on how human traders can avoid becoming a bottleneck in a more automated trading environment.
Vimal Vel – So traders are often managing risk. And to manage that risk, it’s important to make sure that they are not faced with information silos, right? So having access to the right information and having access to the right context around that information is very important to position them for success. So as an example, knowing who the counterparty is helpful, but also understanding their current portfolio positions and then being able to connect that to other prior conversations you might have had with that client or that counterparty, is an important part of avoiding information silos. And then the next step there is being able to bring those information silos together and then surface up some contextual insights on how you engage that counterparty right. So positioning the trader with those tools makes them much more successful and much more effective.
Dan Barnes – So how does that then translate into better trader performance?
Vimal Vel – So when there’s volatility, traders position to move much faster. [Those] Who have automation across their workflows are much better positioned to succeed. So a good example of this March 2020, high volatility traders who were able to increase the level of integration, interoperability between their chat and voice workflow steps were just much more successful. And what we’ve noticed is being able to seamlessly integrate those two modalities and providing a level of automation. A simple example of automation here is being able to pick up the context of the conversation, automate the population of a trade ticket. Those are simple examples of automation helping an integrated workflow, but the net effect is that the trader is positioned to move faster.
Dan Barnes – Now, how do you see technology being applied in order to enable these developments that you’ve mentioned,
Vimal Vel – Technology is going to play a very important role across this. I’m going to use a few of our solution capabilities that we’ve developed as part of IPC to be able to explain this. The first one is in the context of automation. Being able to provide automation to a trading workflow. Second is analytical insights, positioning the trader to move faster but also be more effective. So a couple of examples of this. The first one is we’ve created this application called call list app. This is a call prioritization application that looks at all of those information sources around that counterparty call, right? So who is the counterparty? What is their current portfolio holding? Was there reference to a specific security, a specific asset class that they have exposure to that might have negative sentiment associated with that. Looking at historical call transcripts, and then being able to provide a prioritization of which counterparty you should be calling first is, is an example of where technology positions the trader to move faster. The second component to that is we’ve also got an AI analytics capability overlaid with that application, which provides the trader with summarized insights of what to say. Second example is what we call our head trader dashboard. So heads of trading desks often want to see if there’s misalignment between market sentiment associated with a specific security or an asset class, and trading desk activity associated with that security or the asset class. And when they detect that, they want to have the ability to drop into a call, observe transcription of the call, and those things are made available as part of this head trader dashboard.
Dan Barnes – Really good examples, I think. Now I’m very curious about the way that AI and automation are actually being adopted. Do you see adoption happening uniformly across the market today?
Vimal Vel – It’s a great question. A lot of our clients have AI strategies, understanding where they are in that transformation journey, and being able to provide both automation and AI capabilities in a modular fashion is very important. Clients can consume the full solution, end-to-end from us, or they can consume components of these capabilities that can be easily integrated into their AI platform, or their transformation strategy so they can consume it without disrupting the way they are changing their trading workflows.
Dan Barnes – I think looking at the adoption you’ve outlined there, comparing that to future adoption would be interesting. What’s your vision of adoption going forward?
Vimal Vel – IPC has 100,000 traders worldwide operating on our platform. Our strategy is to be a global cloud based AI-enabled trading communications platform that provides frictionless, seamless interoperability across modalities for the trader. And the way we’re going to do this three components to this. First one is thinking about the trader workflow and making sure the workflow experience is an integrated workflow experience is a very important part of our strategy. The second is ecosystem connectivity. So we are part of an ecosystem. On the trading desk, there are enterprise applications like CRMs (client relationship management systems) and OMS (order management systems). There are critical pieces of information come from. Second is there are workflow applications that sit adjacent to our workflow steps, like chat, and it’s important to provide seamless, frictionless interoperability between these enterprise applications and these workflow applications to our platform, and that’s exactly the way our platform is built. Third is being able to overlay this concept of automation and AI analytics. So the trader has both the automation tools to be successful and move faster, but also these AI analytics tools, should they choose to use them, will make them much more effective. And those AI analytics tools can be ours or their own in house AI application.
Dan Barnes – Well, I think that’s brilliant. Very interesting view of how human trader are fitting into a more automated trading environment and using e-trading and voice trading alike, but still creating greater efficiency going forward. So thank you very much.
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