Data Scientists Play New Role in Financial Services Vertical

Speaking to attendees of the 2018 DataDisrupt conference in New York, Morningstar’s first chief data officer reflected on the recent creation of his role and what it says about the future of financial services.

Back in October 2016, James Rhodes became Morningstar’s first chief data officer; reflecting on his first 18 months in the role, he says the financial services industry is only just beginning to embrace big data.

Rhodes’ hiring actually coincided with another first for the firm—the appointment of Mitch Shue as chief technology officer. The company also expanded its global headquarters in Chicago via the addition of more than 29,000 square feet of space specifically designed for its technology employees.

“Like any firm with an eye for the future, we are focused on transforming our data infrastructure,” Rhodes recently told attendees of the 2018 DataDisrupt conference in New York. “We have an advantage in that we have a nice top-down view of how the data transformation is playing out across the financial services industry, I would add, because our clients and partners range across the full spectrum of providers.”

Rhodes says he was hired by Morningstar to lead its digital transformation thanks in large part due to his deep technical background, having spent 13 years at IBM Research. There, he led the financial modeling research efforts of IBM’s Global Services business units.

“We had a saying that data, plus algorithms, plus action, delivers results,” he said. “Each piece of this puzzle requires the right thinking, the right processes, and the right capabilities.”

Rhodes pointed out that, from his perspective having worked at IBM, big data technology and topics such as “artificial intelligence” and “neural nets” are in fact nothing new.   

“Neural net technology has been around for decades, literally since the 40s and 50s when the first research papers on the topic were published,” he noted. “So, why are we now discussing it so much, both in the context of financial services but also more broadly? Largely because affordable digital memory, computational power and reliable storage are all coming into line today to allow A.I. to redefine business as usual.”

As he explained it, a financial services company can now run a cloud-based data storage and computational system for something like $50 a month through one of many providers, which just 10 years ago would have cost six-figures to run. 

“Leveraging advanced techniques is becoming so much easier and cheaper to do, and we can all benefit from that,” Rhodes said. “At Morningstar, we are using this for our new quantitative fund ratings, as an example. We have been trying to figure out a way to model what our analysts have been doing—that’s what this new quantitative product set is doing. We have been able to dramatically expand our rating capabilities with this approach.”