Pushing the boundaries of TCA

S&P Global Market Intelligence finished runner-up in the perennially competitive Transaction-cost analysis (TCA) system provider category of the Waters Rankings 2024. Michael Richter, global head of trading analytics at S&P Global Market Intelligence, discusses the TCA challenges facing the firm’s buy- and sell-side institutions, and how the firm is breaking new ground in asset class support and providing more advanced trading analysis.

TCA practices, and the tools that underpin such endeavors, have been around in the industry for more than two decades. How does S&P Global Market Intelligence’s TCA tool distinguish itself from other similar offerings in what is a mature and highly competitive market? What does S&P Global bring to the TCA table that differentiates it from other providers and tools? 

Michael Richter: You are absolutely correct; TCA has been around in the industry for more than 20 years now. Offerings in certain asset classes have become mature, and the market is more competitive than it has ever been. There has been a significant evolution within the industry, and users have become smarter in the way they use and look at TCA, focusing on key areas of their businesses where they feel they can get additional alpha. Whether it is deep analysis of algorithms and strategies or venue analysis, these are key areas on which the industry has a focus now, but maybe didn’t many years back. We notice that TCA vendors are receiving better data input from users—such as tagging of orders—and algo and strategy fields are more common now, whereas, years ago, this was certainly not the case.

You also have the movement of TCA into other asset classes, a huge expansion driven primarily by the Markets in Financial Instruments Directive II and the changes to best execution requirements. This is really where S&P Global differentiates itself in the TCA space. Foreign exchange and equity TCA are now mature products within the TCA suite, and people are familiar with what can be done on these asset classes.

It’s the newer asset classes that are seeing the most demand, for example, bonds, credit default swaps (CDSs) and over-the-counter (OTC) derivatives. Investment firms still need to provide proof of best execution across hard-to-price assets, using either in-house or vendor solutions. The approach to these asset classes is very different—it has to be.

Each asset class must be taken on its own merits, as each has unique market microstructures and nuances, which have to be taken into account. These asset classes come down to data quality, by which I mean not only the quality of data the client sends across, but the benchmark data you use to benchmark clients’ trades.

With fixed income, loans, CDSs and OTC derivatives, the benchmark data is extremely scarce. S&P Global has the distinct differentiator and advantage of having pricing data from these asset classes already in the building. S&P Global has a suite of mature pricing products that the TCA solution leverages and uses as the fuel to power the TCA across these assets. It makes S&P Global a compelling vendor when firms are looking for a one-stop shop to meet their best execution needs across multiple asset classes. As we build a strong client base in these asset classes, we can start to provide more insightful and varied contexts of analysis—peer groups, for example.

What are your buy- and sell-side clients/users struggling with right now from a TCA perspective, and how, as a business and technology provider, is S&P Global helping them address those challenges?

Michael Richter: Across the buy and sell sides, firms struggled with visibility into what’s occurring outside of their organizations in trading styles, strategies, algorithmic usage and performances. Seeing this common challenge, we launched an algorithmic trading insights solution earlier this year.

Algorithm analysis is becoming a key part of our TCA use-cases. Our solutions address an increasing need for firms that want to look at the algorithm performance data grouped by strategy and counterparty, as well as those who want to gain a deeper understanding of their algo performances. We spent a lot of time building algo analysis reports to enable firms to understand how a broker’s liquidity-seeking algo is performing against other brokers. We then expanded the dataset and started providing a view of the market using our anonymized peer data, which became the first report of its kind.

What does the product road map for S&P Global’s TCA tool look like right now in terms of new features and functions the firm is looking to fold into it? How might those enhancements impact its users practically? 

Michael Richter: Given the flexibility and customizability of our TCA offering, we are always enhancing our suite of products, whether that be introducing new benchmarks and metrics, or offering analysis over an order’s life cycle to ensure we have an ever-evolving product. The larger pieces of work on our road map revolve around an upgrade to the current user interface. This will improve the user experience significantly. The ability to build reports and add additional graphical representations of the data will become a more seamless process. There will be improved functionality and features, as well as an increase in the speed at which the platform functions.

We are also working towards the launch of our listed options TCA, giving us complete coverage across all of the major asset classes, as well as pre-trade analytics on certain asset classes. This launch will provide our clients with detailed insight into an instrument and how it may behave, as well as expected slippages once trading begins.

Further down the line, we will be investigating artificial intelligence (AI) uses within the trading analytics space. We can already look at an order from a pre-trade perspective and ascertain the optimal approach to execute, looking at historical data, patterns in momentum, liquidity, volatility, news stories, and so on. The machine can make these decisions in seconds, whereas a human would have to spend a fair amount of time collating all of this information. We will look to streamline this process in the future and as times, data, technology and regulations evolve, so will our solution. AI will play a part in an intelligent, efficient execution process across all assets, and I see this as a growth area for TCA. 

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