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
Challenges open for application
1. Using mixed reality to engage staff in learning opportunities
A perpetual challenge in our organization is engaging staff to learn how to manage information. From security awareness to document retention and disposal policies, staff at the Bank need to know a great deal outside their core work.
Traditional attempts to train people in these subject areas haven’t increased their engagement or sense of ownership. Employees often see this type of training as disruptive and unnecessary. We are seeking a new, more interactive way to inspire staff to learn.
We want to use virtual reality, augmented reality, gamification, or a combination of these to engage professionals in learning. We could also expand an innovative learning approach that’s sustainable and accessible to facilitate training across Knowledge and Information Services.
Our main goals are to:
- improve employees’ awareness of each subject
- improve subject accuracy
- ensure staff retain as much information as possible
Also, by getting to know these technologies we would better understand how to use them to engage staff in other areas.
The ideal experiment would create a learning environment that’s unlike a traditional classroom or e-learning setting—one that is valued by highly mobile staff of different generations. The benefits of a successful pilot project would include greater staff awareness of subjects that are important to our department and, by extension, to the Bank.
2. Finding innovative technologies to improve data cleaning
The Bank of Canada uses securities-related data from various external sources to monitor financial markets and perform associated research. But we often can’t use the data received from these sources right away—due to, for example, poor data quality or the way they’re presented.
Staff must spend vast amounts of time “cleaning”—organizing and preparing—the information they receive. Data-cleaning efforts fall into two categories: those that require a significant amount of domain knowledge and those that don’t. We are seeking a way to aid in this process.
We are looking for an augmented artificial intelligence solution—designed to complement human intelligence—that staff can use to better understand, automate and accelerate securities data cleaning. The solution should be:
- easy to customize to various types of information
- capable of addressing both categories of data-cleaning efforts
A successful experiment would find a way to implement technology that lets us:
- identify true outliers versus data entry errors
- input missing data
- remove trend and seasonality factors from our research
It’s also important that the solution allow us to ensure data consistency across multiple sources.
Challenges in progress
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.
We partnered with individuals and businesses to come up with innovative ways to solve challenges we face as a central bank. Check out the results.
For more information about the program, send us an .