Masami Johnstone is looking for fintech companies, in particular specialists in artificial intelligence, that can bring to life the big data sets from foreign-exchange markets.
Johnstone recently joined CLS Group in London, a bank-owned firm that helps members settle FX trades by setting the payment instructions used among counterparties. She previously ran buy-side sales at Euronext.
The global currency market trades about $6.6 trillion a day, including spot, forwards, and options, according to the Bank of International Settlements, making it the largest market for anything on the planet. It is however a market fragmented among dealers, and while electronic trading is growing, much of FX is still traded over the phone.
“I can see a huge transformation in foreign exchange coming based on the use of data analytics,” Johnstone said.
Although CLS is owned by its 72 member banks, it facilitates settlement of FX trades across over 25,000 third-party customers, including corporate treasuries, real-money asset managers, central banks, FX dealers, hedge funds and systematic trading shops.
Because CLS is a settlement-risk clearing house, not a trading venue, it has a broader coverage of the market. The data it gets from this is not tick-by-tick trades. Instead it sees more market-level patterns based on settlements.
I can see a huge transformation in forex comingMasami Johnstone, CLS
CLS says its settlement system now captures $1.55 trillion of FX trades a day, far more than primary FX markets operated by the likes of Refinitiv or the CME-owned EBS.
Nonetheless, Johnstone sees a commercial opportunity for CLS to bring its big-data hoard to the trading desks of banks and other participants. But the scale of CLS’s data is such that it needs to make it digestible and actionable.
The group already offers a version of this to hedge funds, systematic quant funds and global banks. It provides aggregated and anonymized trade data to clients looking to enhance to their trading strategies or portfolio decisions.
“A client might want to detect a sign that unusual market conditions are developing before executing their orders,” she said. “They don’t have time to go through a big spreadsheet. We can provide data in a simpler way, such as alerts or rankings.”
CLS wants to deliver more of its big data trove, because despite the size of the FX market, there are fewer places for traders to get sophisticated analytics.
“Even the big banks can be trading blind,” Johnstone said.
Providing a view
Equities markets have long since gone electronic. In the U.S., all markets consolidate information on one “tape”, and other countries have developed their own workarounds. Equities are centralized on exchanges, which sell feeds to vendors or directly to firms. The data is there and available, which is why there are robust industries around pre-trade analytics and post-trade transaction-cost analysis.
Those things do not exist or are modest in scope when it comes to forex. Even parts of the bond markets are now fully electronic. FX has not yet gone this way in part because of the nature of FX trading, which always involves a currency pair – and therefore multiple counterparties, adding to complexity and fragmentation.
CLS believes that because it has a view of about 52% of all FX settlements, it has the chance to create some of these pre- and post-trade data solutions. It already has about a decade’s worth of spot-FX historic data, so even when information isn’t tagged or categorized, CLS’s own algos can interpret the data to see who is trading what, when, and where.
In addition to its current packaged information, CLS sees two uses of its big-data sets. The immediate opportunity is to address market transparency by making CLS data sets more readily available; a medium-term business is around regulatory requirements such as FX-specific market surveillance and reporting.
“We can provide insight into where trades are happening, the relationships among counterparties, and identify unusual patterns or anomalies,” Johnstone said.
It’s a much more granular version of its current packaged solution, but today only the biggest dealing desks with their own teams of data scientists can make sense of the raw data.
Fintech partners wanted
This is where third-party fintechs come in. Before CLS can deploy a market-transparency solution, it needs partners to bring skills such as data visualization. What clients do not want is merely to download a vast spreadsheet. CLS is also looking for partners – fintechs, equity market vendors – that can integrate its big-data insights into a client’s order-management system, execution-management system, or other platform, so they can embed analytics into their decision-making process in real time.
Johnstone says she has been in touch with many vendors from the equities world. They are useful because they have already laid down the systems that she believes will come to the world of FX. However, most of those vendors sell to trading venues, and a lot of their tech is based on low-latency strategies.
While Johnstone expects FX trading will also emphasize speed as it goes more electronic, she says low-latency solutions are not the right fit for CLS, given its focus on settlement data. “We provide an overview of market insights and market dynamics,” she said. “We’re not competing with trading venues.”
On the other hand, she wants to work with fintechs whose software is robust enough to keep pace as trading times and volumes presumably accelerate.
She declined to go into more detail about the products being prepared at CLS but says it intends to go to market sometime this year.