The Term AI Is Overused: A Conversation With A Chief Data Officer At The Intercontinental Exchange

Steve Hirsch has perhaps one of the most daunting data jobs in the world. As chief data officer at the Intercontinental Exchange and NYSE, his team is faced with massive amounts of data that relate to financial markets around the world, and it all has to be safe, accurate, and usable. It’s a big job, and one that has evolved over recent years with changes and new technology.

One of the biggest changes has been the growth of artificial intelligence, but Steve says we are using the term AI too much and often applying it to technology that doesn’t actually involve artificial intelligence. Steve cites the example of Apple’s Siri, which appears to be AI but is actually just programmed to answer questions in a certain way without taking insights from around and making her own conclusion, which is what actual AI would do.

Automation is playing a large role in the trading spaces, as some exchanges have replaced human traders with computer-based trading machines that use algorithms to find the best deals. Because so much of what happens in finance is driven by models and technology, the industry has faced a number of changes in the past years and decades. To be successful and keep information secure, data experts in the field need to stay informed and on top of the latest trends.

In the data-driven financial world, the Intercontinental Exchange is always looking for ways to incorporate new technology, whether that means building it themselves or going through a good vendor. The main goal of the Intercontinental Exchange is to provide financial data to traders, investors, and academics. That means making sure customers have the information they need to manage their own risks and providing a trusted environment and network that is secure enough for customers to do their required work. The same principles apply to any tech-based business: the goal is always to keep customers’ data safe and secure and provide them the resources to get the job done.

Data, especially related to finances, is particularly prone to volatility. To be successful, organizations need to be prepared for volatility. It shouldn’t be feared, but rather thought of as a way to test that the team has done their jobs properly. Anything from changes in the market to political events, terrorist attacks, and natural disasters can have a big effect on the industry. These events can’t be predicted, so constantly managing data and making sure it is always secure and accurate is incredibly important.

For people wanting to get into the data space, Steve says there are lots of opportunities. Some of the biggest demand now, especially for organizations that analyze massive amounts of data, is for data scientists and data engineers who can understand data and algorithms to make business decisions.

The financial markets affect us all, and having the right data drives smart decisions to keep the markets thriving. Your organization doesn’t have to be as big as the NYSE to take advantage of data—by staying on top of tech trends and avoiding being disrupted with volatile actions, any organization can work towards success.