Through our Partnerships in Innovation and Technology Program (PIVOT), we work with innovators in the private sector and academia to experiment with digital tools and technologies, such as artificial intelligence and machine learning. This initiative builds on our recent collaborations with private sector firms in fintech, such as Project Jasper, as well as our partnership with the Creative Destruction Lab.
We want to improve
- the quality and breadth of our economic research and analysis
- our day-to-day operations
How we’ll do it
Our staff team up with external partners for a limited time to try to respond to challenges through experiments. We periodically issue these challenges and their desired outcome.
This initiative is part of our commitment to build a culture of innovation at the Bank.
What’s in it for you
By participating in PIVOT, successful partners can
- collaborate with our staff who are at the top of their field
- have a meaningful impact on our economic research and operations
- contribute to improving the economic and financial well-being of Canadians
- leverage the partnership with a leading central bank to attract potential investors and clients
1. Payment fraud detection
One of our core functions is to provide funds-management services to the Government of Canada, ourselves and other clients. This involves the secure inflow and outflow of payments. In addition to the various rules-based tools we have already implemented, we want to see if artificial intelligence and machine learning can further enhance the protection of payments.
Assess whether an artificial intelligence solution could enhance our existing rules-based solution, learn from historical transactions, monitor transactions and block atypical activity when detected.
Applications are closed. Experiment in progress with MindBridge AI.
2. Categorizing sensitive data
Protecting our data is paramount. Our staff must therefore categorize their emails, documents and other corporate records properly. This can be tedious, so we’d like to explore the possibility of using machine learning or artificial intelligence to automatically categorize sensitive information.
Test tools that can automatically differentiate between sensitive and non-sensitive documents. This could involve using a machine learning model built from a training dataset or working with an artificial intelligence technology that effectively simulates human categorization.
Applications are closed. Experiment in progress with PigeonLine.
3. Information management
Information is essential to achieving our operational and strategic objectives and fulfilling our commitment to Canadians as a leading central bank. The information we produce must therefore be managed properly. We want to experiment with new approaches to information management and training that will help improve our record-keeping practices to keep pace with our workplace technologies as they evolve.
Test augmented or mixed reality tools to improve the practice of creating, describing, saving and sharing information. The tool should also promote awareness and understanding of the importance of good information management.
Applications are closed. This challenge may be updated and re-posted at a later date.
Household spending measures
Household spending plays a key role in our economy, and policy measures, including interest rate decisions, that affect Canadian households are regularly introduced at both the national and regional levels.
We’d like to track how these measures affect household spending (consumption and housing) and borrowing over time by exploring innovative approaches to gather, process and analyze data to measure and monitor their impact. This would allow us to create indexes of consumer purchases and sentiment in real time.
Trial of a new tool that assesses, in real time, the impact of rising interest rates in a period of elevated debt levels, and to do so more accurately than with the current traditional data sources.
Applications are closed. Experiment in progress with John Baker, PhD candidate, University of Waterloo.
Cyber security analytics
In a continuously evolving technology and cyber landscape, our Cyber Defence Centre needs to quickly and accurately identify relevant patterns based on diverse data feeds, like context data and activity data—for example, firewall and proxy logs, operating systems logs, intrusion prevention system alerts.
We want to experiment with new approaches to analytics methodologies, with a special interest in machine learning, to help detect potential cyber security threats to the Bank.
Trial of innovative ways to detect malicious activities and enhance our analysis, which may not currently be detected with more traditional tools, or in current alerting platforms.
Applications are closed. Experiment in progress with C3SA Cyber Security Audit CORP.
French language evaluation
Every year, the Bank’s language evaluators perform about 200 French language evaluations for candidates, new employees and existing employees with certification renewals.
Our Human Resources department wants to optimize these services through an artificial intelligence platform. It wants staff to assess their skills through a video interview, where they would respond to work-related questions or talk about work-related topics in French.
Ideally, the platform adjusts to the conversation and differences in accents. The evaluation results are available immediately to each user, and the recordings are archived to help users assess their own progress. We hope that the ability to more frequently self-assess progress will encourage employees as they work toward maintaining their level or attaining the next.
Trial of an artificial intelligence tool to assess and provide an overall second language proficiency level to Bank employees. The assessment includes pronunciation, rate of speech, vocabulary, grammar, comprehension and overall message.
Applications are closed. Experiment in progress with Silver.
For more information about the program, send us an .