FinTech

FinTech Innovators: Mike O'Rourke, Vice President, Global Head of Machine Intelligence & Data Services

Mike O'Rourke Headshot

Mike O’Rourke has spent 18 years of his two-decade long career in technology at Nasdaq. Now, as Global Head of Machine Intelligence and Data Services, he leads Nasdaq’s machine intelligence development—Nasdaq’s Innovation Lab—that combines proprietary data with advanced analytics and machine learning to improve firms’ trading behaviors and performance. His mission is to create new products, across the company, built through experimentation and iteration.

Looking back over the last few decades, several technology waves have occurred, all with different drivers. In the eighties and nineties, the focus was on digitizing markets—how we trade, deliver market data, and distribute news. From 2000 until around 2008, the ubiquity of the internet shifted the focus to the interconnection between financial institutions and consumers. Since then, the cloud, big data, and machine intelligence have taken center stage.

Reflecting on the technological advancements he has seen so far in his career, O’Rourke says one of the most significant is the advent of the cloud and what it allows us to do. Cloud computing is not just one technology, he explains, but several technologies that are allowing organizations to store more data, improve time to market and provide access to an unprecedented amount of computing power. A virtually unlimited amount of storage lowers the cost of many technology products and puts within reach certain use cases that were not economically feasible in the past. This innovation is feeding advancements in other areas, especially machine intelligence.

“Machine intelligence is probably my favorite innovation, he says. “Despite being around for a long time, it’s now—with the advent of cloud and maturity of big data technologies—starting to take off.”

Until recently, machine intelligence has only been available to the largest of firms with the resources and willingness to invest in it. Sophisticated firms, including some quant funds, have been using it to drive actionable insights and improve how they invest and trade.

But the cloud is democratizing technologies, like machine intelligence, becoming available to a much broader audience. For example, it is gaining deeper penetration at exchanges and clearing houses, which are using it to increase operational efficiency, create richer data products and provide better services to the market.

In the past, users had to adapt their workflows to extract information from computers. They had to know exactly where the data was on the machine and how to connect it together. To illustrate, they would spend a lot of time pulling data into Excel spreadsheets to manually make connections between data points.

Going forward, instead of humans doing all of the work to connect and trying to get computers to answer their questions, they can simply input their intent, and the machine does the work. With machine intelligence, computers have context aware, user-specific information to pull together the right data and provide better insights to users much faster.

“You're going to see a flip from where humans adapt to the computer to get information, to where computers now adapt to us in order to provide more relevant data,” says O’Rourke.

This capability already exists in applications such as Amazon’s Alexa, which allows users to interact with devices in a more intuitive way using voice. It knows who you are and where you are, so when you ask a question, it has that context-specific information. It can add to the data it needs to pull and the action it needs to take. These types of applications are going to become much more pervasive in the future.

To this end, O’Rourke’s team is working on several machine intelligence project beginning with Nasdaq Trading Insights, which was launched at the end of 2016, and is being expanded. Out of the Innovation Lab, the team is developing additional analytics that launch this year, driven by market data to provide unique, and actionable, insight to market participants at the sovereign, institutional, and retail levels. In addition, projects are underway in surveillance to enhance the Smarts platform, as well as in corporate solutions, specifically in investor relations and advisory, to provide better insights and service to customers.

“Our goal is for machine intelligence to permeate each of our business lines,” says O’Rourke. “We want to make every one of Nasdaq's businesses better and smarter by providing them with richer data and better insights.”

Looking to the future, he expects the rate of technological innovation to accelerate and use cases to move up the value chain quickly. Today, companies use descriptive analytics to explain what happened, sometimes delving into diagnostic analytics to explain why it happened. Soon they will leverage prescriptive analytics to predict what will happen, and importantly, how they can take action to capitalize on future events.

“You're going see more products that are aiming higher up the value chain,” he says. “They’ll have more context-specific information, and be pointed toward specific users and audiences that need that information.”

So what is his secret sauce? O’Rourke says it is all about listening to customers and getting their feedback. Having that living product focus and context before ideating on hypotheses, experimenting and developing the products is the key to success.


Nasdaq will be presenting on Machine Intelligence at this year’s World Exchange Congress in Budapest, including a Roundtable Discussion on ‘Pre-Crime Management and Market Surveillance’ and a Nasdaq-hosted Machine Intelligence Breakfast for C-level Exchange Executives. Click here to register for our breakfast session. Note that we reserve discretion on admitting breakfast participants..

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The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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