Big Data & AI Case Competition

Big Data & AI Case Competition

The 2020 Big Data & Artificial Intelligence Case Competition

A Collaboration:

the Institute for Management & Innovation (IMI), and
the BIGDataAIHUB at the University of Toronto Mississauga

The combination of Big Data and Artificial Intelligence is reshaping the way we think, work, and live.  New career opportunities are emerging and traditional ones are being transformed or eliminated.  As Undergraduate students at one of the top universities in the world it is important to stay on top of current and emerging trends, to pursue continual personal development, and to have some fun in the process.  This event is designed to achieve all three.  It is a collaboration between Scotiabank, the Institute for Management & Innovation at the University of Toronto Mississauga (UTM), and UTM’s BIGDataAIHUB.

*FREE and open to ALL UTM undergraduate students*


The 2020 Big Data & Artificial Intelligence Case Competition is a new event for UTM.  It is a multi-faceted competition that is open to any Undergraduate student from any academic discipline, in any year of her or his academic career at UTM. It is only open to UTM students.  No specific prior skills in big data or artificial intelligence are required however participants are expected to attend a three-hour educational briefing session designed to significantly assist them in this competition.

The event is designed as developmental opportunity for students. If selected to compete, they will gain hands on exposure to big data and artificial intelligence as well as an opportunity to practice their formal presentation skills in a safe, fun and collegial yet competitive environment.

Results from the inaugural competition are now in! Read more about the winning teams and the final competition here.


  1. The idea for a campus-wide case competition for UTM undergraduate students was developed in mid-2019 by Soo Min Toh (IMI) and Irene Wiecek (MMPA, UTM BIGDataAIHUB).  They are the primary sponsors.
  1. Prof. Kevin Yousie was asked whether he would be prepared to take the lead on this initiative and he was pleased to do so.
  1. Prof. Yousie met with Scotiabank and the bank agreed to partner with UTM on this initiative.
  1. It was agreed that the task for the students would be to: “Recommend a process that employs big data and artificial intelligence in identifying whether clients are engaged in money laundering, specifically as it relates to human trafficking”.
  1. As per the article in the Globe & Mail newspaper (URL link below), human trafficking is an issue here at home, not just elsewhere. “According to the government’s statistics, approximately two-thirds of Canada’s police-reported human trafficking violations occur in Ontario and the average age of recruitment into sex trafficking is 13”. Collectively participants were encouraged make a positive difference and see if they can contribute to the elimination of human trafficking.
  1. In the fall of 2019 Prof. Yousie consulted with a number of students and others to solicit their thoughts and input.  Input from the student President of the IMI Business Association and the UTM Society for Algorithmic Modelling was particularly helpful.
  1. The 2020 Big Data and Artificial Intelligence Case Competition began in earnest in December with student registration. 
  1. A target of 12 teams of four or 48 students was established as the goal.  The level of interest in this event far exceeded expectations and registration was cut off once 175 registrations had been received.
  1. The format of the event was subsequently changed to ensure every registrant could compete, gain hands on experience with big data and artificial intelligence, and have a first-class personal development opportunity.
  1. This is a UTM only event open to any undergraduate student, in any program and in any year of their academic career.
  1. There was a full-day kick off on Saturday 25th where student learned about human trafficking and money laundering, became familiar with the data and the software. Three Scotiabank executives made presentations and fourteen Scotiabank data scientists were available to provide support.
  1. The event was supported by fourteen IMI Graduate Student volunteers from across virtually all of the IMI Graduate programs.  IMI staff were also key in providing the necessary planning and support.
  1. Initially “fake” Scotiabank data was provided to the students with the help of UTM’s IT group using Jupyterhub technology.  This data had the same variables as the real data that would follow later however the data itself was fictitious. Having said that, the data was such that participants could still use it to formulate an approach for pursuing their assigned task.
  1. In February two optional training sessions were provided by Prof. Gerhard Trippen.  One was a tutorial about Python programming and the second a tutorial with respect to Machine Learning.
  1. The students were required to sign a Student Acknowledgement form confirming that they had read the Non-Disclosure Agreement between Scotiabank and the University of Toronto Mississauga and agreed to abide by it.
  1. Once the signed Student Acknowledgement forms had been submitted, the fake data was replaced with a real-life Scotiabank data set and it was very large.  The data file contained 8.6 million rows of data 8 columns wide which equated to a 1.6GB uncompressed csv file.  The data had been encrypted to prevent students from seeing to the individual client level to protect privacy.
  1. In addition, students were provided with a second way of accessing the data, this time via new “secure enclave” technology. This was made available through a collaboration of the University of California Berkley, Microsoft, Scotiabank and UTM. It is said to be ground-breaking encryption technology that will be implemented at scale shortly.
  1. The purpose of providing access to the Secure Enclave was to give teams a chance to try break through the encryption software. While teams were encouraged to try this, it was positioned as an optional and less important aspect of the overall competition.
  1. Scotiabank provided a custom email address that the competitors can use if they have questions about using the data or the Secure Enclave.  This email is answered by a team of Scotiabank data scientists.
  1. The final competition is on Saturday, March 28th.  It was to be an all-day event at the university with the public invited to observe.  Given the COVID-19 situation however this has been moved to a virtual competition.  Competitors will submit 15 minute voice over PowerPoint presentations and a team of Scotiabank data scientists and executives will select the winning teams.
  1. There are still more than 90 UTM students actively engaged in teams in this competition.
  2. The winners have been announced! The competition ended with virtual presentations, judged by a team of Scotiabank data scientists and executives. Three winning teams received gift cards and the opportunity to present to Scotiabank.