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For finance professionals, knowing the nuts of bolts of machine learning is a must

December 17, 2019

A Rotman professor explains how machine learning fits into the future of business.

Photo of Juliana MontoyaBrace yourself: we are entering the brave new world of machine learning, and we have a lot to learn.

According to Professor John Hull, it’s a crucial time to start thinking about machine learning and its applications.

In the next few years, machine learning — and its potential to make predictions, identify patterns and ‘learn’ from huge data sets — is poised to disrupt many aspects of finance and financial services. Financial services professionals are already making better-informed credit decisions and able to define customer groups more accurately thanks to the predictive capabilities of advanced machine learning. Many are also benefiting from robo-advisors and language translation algorithms.

“While the hype around machine learning is not new, we are finally starting to develop and use machines that can handle large data sets and perform the algorithms the industry has been talking about for years,” says Hull. “The hardware is catching up, and we have to be sure that we are keeping up too.”

Hull, who is a professor in the Finance area at the Rotman School, the academic director of the Financial Innovation Hub (FinHub) and the Maple Financial Group Chair in Derivatives and Risk Management, has a history of immersing himself in the unknown.

Hull started out in corporate finance, but quickly began investigating emerging fields like derivatives and risk management. Eventually, he became an expert in these areas and authored a number of well-known texts (including Risk Management and Financial Institutions; Options, Futures and Other Derivatives; Fundamentals of Futures and Options Markets) and taught courses on these topics at the Rotman School.

“I tell students that they can expect to get a foundation through our graduate programs, but they’ll constantly be learning new concepts and building upon that foundation throughout their careers,” he explains. “With every step of my career and every new topic I’ve dived into, I’ve had to teach myself.”

In recent years, Hull has shifted his focus to machine learning in finance, and he’s eager to share this knowledge with business professionals.


“My advice to students: if you’re after a long and interesting career in the finance industry, you need to know about machine learning.”

—John Hull, Professor of Finance


With others from the FinHub, he has designed new compulsory courses for the Master of Finance and Master of Financial Risk Management programs, and the group offers similar electives for other graduate degree programs at the School. Additionally, when Hull saw the limited resources available for business professionals on machine learning topics, he wrote and published a new text, Machine Learning in Business: An Introduction to the World of Data Science (2019), which serves as the textbook for the courses he teaches.

“Most books on machine learning are written by computer scientists for computer science students. My book is aimed at business professionals. It introduces the algorithms and underlying thinking so that they can work productively with data scientists.”

In his book and in his classroom, Hull clearly explains the fundamental principles of machine learning to the business professional, while highlighting relevant applications.

Hull uses data sets on country risk, housing prices and loan defaults to illustrate the algorithms. Reinforcement learning — which, in addition to its business applications, has been successfully used to beat the best human chess and Go players — is compellingly illustrated with a much simpler game, Nim. One of the attractive features of his book are the accompanying Excel and Python files, available for download on his website, for all the applications described.

The last chapter of the new book deals with the issues machine learning has created for society. There are growing concerns around data privacy, biases in algorithms, ethics, and potential job losses. Still, Hull is optimistic and quick to quell any fears that machine learning will displace talented professionals.

“With every past industrial revolution, some job functions have become obsolete, but many new roles have been created. We should be focused on the interesting applications and new jobs that will emerge,” Hull says.

His advice to students: if you’re after a long and interesting career in the finance industry, you need to know about machine learning.


Rebecca Cheung | More Rotman Insights »


Meet the researcher

John Hull

Professor of Finance
Maple Financial Group Chair in Derivatives and Risk Management
Academic Director, Rotman Financial Innovation Hub

Read his full biography →


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