Rapidly improving data platforms are transforming how the financial services is innovating, whether that's on the regulatory or product side -- and driving some often-unexpected collaborations as a result.
That was the key takeaway from a conversation between New York Stock Exchange (NYSE) President Stacey Cunningham, Western Union's President of Product Shelly Swanback and Snowflake's CEO Frank Slootman at the latter's financial services data summit this week -- with the three pointing to the granularity of risk assessment it is now possible to generate (i.e climate risk by area, assessed down to zip code) using blended data.
“The beautiful thing about data is you never know where it's going to take you" NYSE President Stacey Cunningham noted, pointing to a project on ESG data launched by NYSE parent company ICE and Bank of America in early 2020 that was designed to help investors better assess ESG risk, before growing in scope.
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That project rapidly evolved, she noted: "The project started with a customer saying 'we want to track ESG data, can you collect that data for us?' So we started -- in partnership with Bank of America -- collecting 500 criteria around different ESG metrics for 3,500 companies. That’s data that we then can provide to investors who are looking to make ESG investment decisions, as well as index creators, ratings agencies, and others.
"But because we’re also NYSE we can echo that data back to our listed companies. I think what’s interesting is that this isn’t how it started – it started with Bank of America looking for a product that they wanted us to help with. And it turned out to be something we could give to listed companies to see how their ESG is perceived in the market; are there things they should be disclosing that their peers are disclosing, and they are not?
NYSE President Stacey Cunningham added: "What’s interesting is hearing from companies that they not only use this for their own ESG... they are also using it to see what their vendors and potential partners are reporting as they think through their Scope 3 [pdf] emissions reporting. That's not something that we anticipated."
Chat came as Snowflake launched a 'Financial Services Data Cloud'
As S&P Global’s Warren Breakstone -- a financial services veteran who now leads the data business at its $2 billion market intelligence division -- told The Stack earlier this year: "Clients are increasingly looking to bring data directly into their environments through data feeds, or APIs, the cloud; providers like Snowflake."
Cloud data platform provider Snowflake has positioned itself as a collaboration space for data -- it already runs a data marketplace that it sells as a neutral, user-friendly home for users to pull in third-party data (from providers like S&P), add their own datasets, run analysis, and present findings via a range of dataviz UIs (pick your poison), and the roundtable came as the Snowflake launched a new "Financial Services Data Cloud".
The new platform's been designed to support secure and compliant collaboration on data across the enterprise, with features like "private connectivity for multiple public clouds, enhanced encryption with bring your own key, built-in classification and anonymization of sensitive data, and integration with 3rd party tokenization providers, all offered in compliance with SOX standards" Snowflake said in a September 14 press release -- and has already drawn in users like Allianz, BlackRock, Capital One, NYSE, Refinitiv, State Street, and Wise.
The need for a central, compliant platform to support complex blending of rapidly evolving data has never been more important, Snowflake CEO Frank Slootman noted: "The big difference between where we've been as an industry and where where we are now is that there is almost zero friction, zero latency in terms of overlaying and blending and joining data... for hedge funds it is not uncommon to see them have hundreds and hundreds of external data sources. But it was [previously] brutally hard for them to physically copy, replicate, and transform the data to an analytics-ready format... these are not always nicely manicured datasets."
NYSE President Stacey Cunningham: data is transforming compliance
The ways in which it is getting faster, cheaper and more effective to analyse huge overlapping datasets "really opens up opportunities that didn't exist before" as well, NYSE's Stacey Cunningham noted.
Pointing to the "flash crash" of 2010 as an example, she said: "It took a long time for the regulators to figure out what happened then, because... trading is fragmented across many different exchanges in different locations. Stitching that whole pie back together was a project that at the time we didn't have the tools in existence for."
"The SEC in response announced the consolidated audit trail... that provides a lot of opportunity for us to find bad actors. Because now when you think about insider trading, or other things that occur across different places in different locations, the SEC, or FINRA can go and look at that data and really determine what might be happening that would have been obfuscated before, because it wasn't all in one place."
It's also allowed the creation of tools that in theory can prevent things like the trillion-dollar flash crash happening again. As she put it: "We process 330 billion messages on a busy day. Market makers are setting the prices for securities when markets can move so quickly [so managing] risk becomes an important part of that. That comes back to that observability, what are we seeing in the data... you need to have automated responses when you're talking about that kind of scale, so that you can manage risk in an automated fashion.
"So for us, before those trades even occur on the exchange, we're running calculations across the data based on inputs from our customers -- as well as what's happening on the exchange -- to see what their risk profile is. And if they reach a trigger, it actually prevents those trades from from being entered into the market at all, which is the kind of response that would have prevented the flash crash had they existed back then. So we're using data to solve those problems."
