Institute for Management & Innovation highlights use of AI to tackle crime
The ways in which financial institutions and law enforcement use artificial intelligence (AI) tools to curb the illegal fentanyl trade was the focus of three recent events that took place on March 22 at the Institute of Management & Innovation (IMI) at University of Toronto Mississauga.
The day began with presentations by the five finalist teams in the Sixth annual IMI Big Data and Artificial Intelligence Competition. The competition is a four-month learning and development opportunity for U of T students to gain hands-on exposure to big data and AI. Open to PhD, masters and undergraduate students from all academic disciplines across all three U of T campuses, this year’s competition attracted 356 participants who formed 72 teams.
The participants were tasked with using AI, including generative AI, to find anomalous transactions that could potentially reflect involvement in the trade of illegal drugs, including fentanyl. The synthetic financial data for the competition was provided by Scotiabank, the event’s primary partner since its inception.
“The annual IMI Big Data & Artificial Intelligence Competition is extremely challenging. The students that participated this year demonstrated particularly advanced skills. Their work was truly excellent and exceeded the expectations of the judges,” says Kevin Yousie, an associate professor in the teaching stream at the IMI, the academic director of the IMI Big Data & Artificial Intelligence Hub (BIGDataAIHUB) and the founder and chair of the annual conference and competition.
“Catching bad actors engaged in the production and distribution of fentanyl” was the theme of the afternoon conference, which was co-sponsored by Scotiabank and the IMI. Experts from multiple financial institutions shared how their organizations are using AI and machine learning to analyze financial transaction data and identify potential bad actors engaged in the illegal production and sale of fentanyl. Fentanyl was involved in more than 50,000 overdose deaths in North America last year.
Three Scotiabank executives delivered keynote presentations. Cameron Jones, vice-president and global lead of financial investigations and high-risk clients, explained how fentanyl became the deadliest narcotic in North America and how it has devastated some communities in Canada. He also summarized recent efforts by the financial sector to monitor drug trafficking-related transactions. Mirela Gondor, vice-president of anti-money laundering (AML) data, discussed how Scotiabank uses big data technology to identify suspicious financial transactions. Meanwhile Duncan Smith-Halverson, director of AML and anti-terrorist financing models and analytics, explained how financial institutions can employ “synthetic” or artificially generated data in their AML systems.
The conference also featured a panel discussion with experts discussing various aspects of fentanyl crime. They included Michelle Sarmiento, the chief anti-money laundering officer at Wealthsimple Inc., and Jason Fleming, an AML expert from CIBC who was directly involved in Project Guardian, a public-private partnership to combat the trafficking of illicit synthetic opioids, particularly fentanyl. The two panelists from Scotiabank were Nunzio Tramontozzi, a seasoned former Toronto police detective, and Trish Villanueva, a cybercrime specialist with deep experience in the dark web, cryptocurrency and sophisticated computer hacking attacks.
“This was a great event to showcase to students the application of big data and data analytics,” says Michelle Sarmiento of Wealthsimple Inc. “Sophisticated data analytics methods have become incredibly important to anti-money laundering (AML) programs and how effectively we can detect anomalies in financial transaction data.”
This was the third annual Fighting Crime with Big Data & Artificial Intelligence Conference. Themes of the previous conferences were human trafficking and the illegal wildlife trade. New at this year’s conference was a poster competition organized graduate students who comprise the IMI’s new Artificial Intelligence Club.
The winners of the 2024-2025 IMI Big Data & Artificial Intelligence Competition were announced at the end of the conference. The winning team consisted of three transportation engineering PhD candidates, a civil engineering master’s student and a computer science undergraduate student. The winners received a total of $30,000 in prize money: the first-place team was awarded $15,000, while the second and third place teams received, respectively, $10,000 and $5,000.
Plans are already underway for next year’s 2025-2026 IMI Big Data & Artificial Intelligence Competition.
“Looking back on the conference, it’s evident that the exchange of ideas and collaboration among participants has been valuable,” Yousie says. “Our combined efforts will help drive future innovations in further leveraging AI technology in crime-fighting.”
2024-2025 IMI BIGDataAIHUB Big Data and Artificial Intelligence Competition: Winners
First Place
Timotéo Frelau, Mwendwa Kiko, Jacob Klimczak, Hesam Rashidi, and Sebastian Villada Rivera
Second Place
Radian Gondokaryono, Paul Kang, Nillan Nimal, and Nirmal Pol
Third Place
Yoyo Gong, Haochuan Jiang, Yuou Lei, and Chuan Liu
Top 5 Finalist
Shaojie Dong, Shuai Jia, Junxiang Mao, Chenkai Zhang, and Qiyi Zhang
Top 5 Finalist
Tanishka Gupta, Ernest Namdar, Tanmay Sethi, Tanish Sharma, and Timothy Williams
