Inside Nasdaq’s AI-fueled pivot to SaaS provider
The company’s pivot to new tech development and SaaS began in 2021 and is keenly focused on the cloud, machine learning, and AI, as well as blockchain for tracking digital assets.
The company’s pivot to new tech development and SaaS began in 2021 and is keenly focused on the cloud, machine learning, and AI, as well as blockchain for tracking digital assets.
As the first company to store data under regulation on the cloud, Nasdaq’s cloud roots go way back, says Peterson, whose IT department embraces Amazon Web Services as its primary cloud provider, relying on Amazon Redshift Spectrum for data analytics and warehousing. Peterson also worked closely with the founders of Databricks and has been on the cutting edge of AI, natural language processing, and Apache Spark, an open-source analytics engine that Nasdaq has used to develop risk management applications.
“When you have to calculate risk, it works really well to spread it horizontally in the cloud,” Peterson says.
To power its pivot, Nasdaq restructured into three divisions: Market Platforms, Capital Access Platforms, and Anti-Financial Crimes. It has also made significant acquisitions, notably of Newfoundland-based Verafin, whose AI-based financial crime management solution supports 2,400 banking customers globally. In June, Nasdaq also acquired Adenza, a risk management innovator that enables financial customers to report to regulatory agencies.
Dual role brought to bear on innovation
Peterson dual role as both CIO and CTO has proved critical for creating tight synergies between Nasdaq’s markets business and its evolving surveillance, security, SaaS, and AI services.
“Having an integrated CIO/CTO role allows our technology teams to implement an integrated strategy both in our products and on our business operations,” Peterson says. “It enables a seamless implementation of our technology strategy and I believe that it’s a key reason why we are leaders in our industry.”
It has also helped enable Nasdaq to “stay ahead” of major technology trends and be more strategic in evolving its identity as both the leader of the exchange and a standalone technology company, he says.
“I quickly realized the potential of SaaS-based solutions because as a customer of those solutions I found them immensely powerful,” says Peterson, who employs another IT exec in a CIO role dedicated to corporate systems and a separate CISO to oversee security. “I knew that if Nasdaq embraced this trend and delivered better SaaS-based solutions to our customers, we would have enormous success.”
By the end of 2022, annualized SaaS revenues exceeded $700 million, representing more than a third of Nasdaq’s recurring revenues.
In terms of synergies, Nasdaq’s expanded business model into security, surveillance, and risk management will strengthen the company’s exchange and trading business while enabling further expansion into SaaS, Peterson says.
Sidhartha Dash, chief researcher of Chartis Research, agrees that the company’s expansion is compatible with its core mission.
“Many of the software tools and applications in its portfolio are closely tied to and directly linked with its transaction and clearing systems, such as execution software for other exchanges, trade surveillance, and real-time risk management — other pieces that address the broader trading services value chain and compliance,” he says.
Peterson acknowledges the risks of AI but assures that Nasdaq’s emerging technologies’ legal compliance and risk management execs are co-leading a group to monitor IP risks and other potentially risky outcomes. Nasdaq, of course, also reports to all regulatory agencies such as the SEC and FINRA.
“Our integrated technology strategy has also enabled us to implement AI solutions quickly and pervasively,” Peterson says. “As a result, we are effectively leveraging AI to improve the resilience of our markets, provide better intelligence to our customers, and as a way to help banks fight crime every day.”
FINRA, for example, informed CIO.com that NASDAQ reported to the SEC in April that it “proposes to further refine the length of the holding periods for M-ELOs [Midpoint Extended Life Order] and M-ELO+CBs [M-ELO plus Continous Book] using innovative and patent pending machine learning technology as it has found that shorter periods could achieve the same, if not better results for participants in terms of mark-outs, although not in periods of heightened price volatility.”
Such efforts to help ensure market resiliency using AI are core to Nasdaq’s traditional mission, but the company’s foray into surveillance and security technology is where AI is rapidly coming to bear, as the technology is only going to strengthen defenses against bad actors who challenge the market and banks, Peterson says.
Market surveillance was “kind of rules-based in the early days but now it’s becoming more and more AI,” he says, noting that while there will be those who use AI to try to find weaknesses in the market, Nasdaq has security products in place for the exchange and for many banks and will be “putting AI close to that. We think it’ll always be a little bit of a race, right?”
“The piece we’re most worried about,” Peterson adds, “is the threat of someone trying to disrupt capitalism.”
Nasdaq’s generative future
At a recent industry conference, Peterson extolled the possible impact of generative AI on Nasdaq’s new business strategy.
“There is so much opportunity for innovation,” Peterson said at Reuters Momentum in Austin, Texas, in July. “We thought it would be a missed opportunity if we just said no. We’re getting it across the company. Not just the technology group.”
Peterson notes that there is great interest in the co-pilot capabilities of gen AI and among content creators who would naturally benefit from the LLM capabilities, such as marketing departments, and a big benefit for the legal team.
“We will continue to work in areas where you have to create content, and there’s a whole body of extra opportunities around how you actually work as a company,” Peterson says. “That’s huge productivity. Code is content.”
Nasdaq is moving ahead with using generative AI for dynamic order types and other applications that improve trading as well.
“It’ll recalculate what is the best threshold to set the life of the order and you’ve got large numbers of symbols so it’s not something that a human could do every 30 seconds,” Peterson says. “AI will look at these factors, do a calculation and automatically reset it. If you improve liquidity, you get better fill rates and you can eliminate some of the negative things that happen in the market. It improves outcomes.”
So, no, Nasdaq isn’t pushing pause on AI over recent concerns — and can always stop in the event it becomes necessary, Peterson maintains. Peterson’s dual role at Nasdaq and long history with technology has given him just the right experience for this moment as AI emerges further in business.
“It’s having that opinion about how we build products and how we transitioned so seamlessly … to see the cloud as a much better delivery mechanism as a precursor to being able to really prepare yourself for using AI,” Peterson says.
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