Driven by the “fintech”, these young companies who juggle information and communication technologies to grab the slice of the pie, the big traditional financial institutions are trying to catch up, but the sector demanding a delicate treatment – data highly confidential, fraud, regulation – artificial intelligence must put on white gloves to enter the world of finance.
“The Fin-ML network was created at the request of the financial industry for its training needs in AI and machine learning,” says Rheia Khalaf, Director of Collaborative Research and Partnerships for the Network, whose goal is the collaboration between the financial and university worlds. To achieve this, the organization offers training that benefits students, but also industrial and academic members of IVADO, since they meet their needs. Six partner universities participate in Fin-ML: University of Montreal, HEC Montréal, Concordia University, University of Calgary, University of Waterloo, and Queen’s University. “We work with them to facilitate the integration of student trainees, and we offer a scholarship program,” adds the director.
In order to establish a partnership, Fin-ML contacted Finance Montréal, the cluster of Quebec’s financial ecosystem that represents 150,000 jobs and nearly 7% of the province’s GDP. “We are very pleased to be associated with the Fin-ML network, which will enable our universities and financial institutions to work together to develop machine learning solutions for the financial sector,” explains Louis Lévesque organization, which brings together players from the financial community and whose mission is to develop and promote this industry in Quebec. “For us, the AI represents a tremendous opportunity for financial sector transformation, and partnering with Montreal’s talent provides an exciting opportunity for our member institutions to find new solutions that meet the needs of consumers,” he added. he.
New CapacityThe profile of the students participating in the Fin-ML program is quite varied; some are trained in computer science, others in mathematics or even in business intelligence. They study at the master’s or doctoral level and all have a fairly advanced technical background to be able to follow Fin-ML training, and they must have an interest in the world of finance.
This field has always used technology and data analysis, but what is new today is “this new computational capability whose approach allows for quick and effective results,” says Rheia Khalaf. We are witnessing an evolution that will accelerate cost reduction and process automation.
The FIN-ML CRE program for Machine Learning in Quantitative Finance and Business Intelligence was set up to give access to this field to master’s or doctoral students who are not necessarily exposed to this type training. The program, led by Manuel Morales, an associate professor in the Department of Mathematics and Statistics at the Université de Montréal, includes an internship component: “This is where collaboration comes in, since we are responding exactly to the needs of a a company that is paired with a team of professors and students who will work on specific research for three or six months or longer, “says the director.
This training, focused on innovation, collaboration and research experience, is offered through a program funded by the Natural Sciences and Engineering Research Council of Canada (NSERC). It encourages interuniversity collaboration and inter-provincial mobility, bringing academia and industry together in collaborative research. The director states that “the $ 1.6 million funding received over a 6-year period is used to fund students through scholarships, to ensure their interprovincial mobility and to set up training courses”.
Slowly, we see changes appear in companies that, increasingly, develop collaborations: “Today, it is not uncommon to see financial institutions subsidize young Fintech companies for the purpose of an association, to integrate them into their business, “says Khalaf.
