'The new Excel': MBA students flock to machine learning course

With recent instability in some U.S. banks and the crypto “winter” that began last year, experts say it’s more important than ever for finance professionals to understand the innovations – and challenges – in the sector.

“The world is changing quickly, and so too are the skills needed to thrive,” says John Hull, a University Professor of finance at the University of Toronto’s Rotman School of Management.

Hull is the academic director of the Rotman Financial Innovation Hub (FinHub), which is designed to help fintech practitioners, students and faculty to share insights and equip students with best-in-class knowledge of financial innovation. He created the hub five years ago with Andreas Park, professor of finance at U of TMississauga, and the late Peter Christoffersen, who was a professor of finance at Rotman.

“We recognized there were lots of things happening in the financial sector that are transformative and different, and we wanted to develop the knowledge base and pass it on to the students so they can compete in this space,” says Park, who has a cross-appointment to Rotman.

Each year, students can take courses taught by FinHub-affiliated faculty. That includes Hull and Park, who offer courses on machine learning, blockchain, decentralized finance and financial market trading.

One of the most in-demand MBA electives is machine learning and financial innovation, which introduces students to the tools of machine learning. A similar course is compulsory for students in the master of financial risk management and master of finance programs.

Students are required to learn Python in the course, with Hull calling the programming language “the new Excel” as it becomes a common requirement for many jobs in finance.

“I’ve met traders in their 40s who go and learn Python because it simplifies their workflow,” says Park. “It’s all about inferring data and making sense of it, and then predicting future data using machine learning tools. And to do that, you need to learn Python.”

The machine learning course is offered to full-time MBA students in March and April of their first year. It’s also available as an elective in their second year.

“Many MBA students get involved in machine learning as part of their summer internship, so it's important to give them an opportunity to familiarize themselves with machine learning and Python applications prior to that time,” says Hull.

MBA student Cameron Thompson took the course prior to an internship at Boston Consulting Group (BCG) and says the hands-on practice in class was invaluable, with or without an extensive background in computer programming.

“Being familiar with common machine learning terminology from day one on the job was quite useful,” says Thompson, who will be returning to BCG full-time following graduation. “The course builds a solid foundation for using data in a strategic way and then adds the machine learning content – it’s hard to go anywhere without seeing an application.”

In his second year, Thompson pursued an independent FinHub study project – sponsored by the Bank of Canada – that involved working with researchers from Rotman and the Faculty of Applied Science & Engineering on a natural language processing model. 

MBA grad Fengmin Weng, who took the elective course with Hull, says the insights from class prepared her to lead a machine learning project at TD.

“Machine learning is definitely the trend in the financial industry, particularly in the risk management area,” says Weng, who came from an accounting background when she pursued the master of financial risk management program.

“It definitely helps us to make better decisions around our strategy,” she says. “If you want to develop your career in the risk area, machine learning is your weapon.”

Richard Liu, who received his MBA from Rotman three years ago, says the machine learning course was one of the most eye-opening parts of his MBA experience. Today, he says he uses many of the concepts from the course in his work as a financial planner. 

“I’m able to recognize when it’s more effective to train computers to enhance our work, how to coexist with robo-advisors and how to automate some of our financial planning processes,” says Liu.

Students involved with FinHub courses are equipped with the tools to think critically about the implications and benefits of emerging technologies in the financial sector, says Park, adding that “they’re able to enter an organization and use these tools to help improve processes and strategies.”

Hull, meanwhile, says student who take the course gain insight into the direction the finance world is heading – namely “that machine learning is becoming more and more important in business."