Scotiabank’s Perspectives On AI/ML Governance And Future
This is a five-part blog series from an interview that I recently had with Grace Lee, Chief Data and Analytics Officer and Dr. Yannick Lallement, Vice President, AI & ML Solutions at Scotiabank.
Scotiabank is a Canadian multinational banking and financial services company headquartered in Toronto, Ontario. One of Canada’s big five banks, it is the third largest Canadian bank by deposits and market capitalization. With over 90,000 employees globally, and assets of approximately $1.3 trillion Scotiabank has invested heavily in AI, Analytics and Data and aligned an integrated function that is well supported by all business lines. Although their journey has zig zagged in impact along its way, the organization now has a strong foothold in bringing consistent value and impact to the business.
This five-part blog series answers these five questions:
Blog One: How is the advanced analytics function structured and what have been some of the most significant operational challenges in your journey?
Blog Two: What does it take to set up an AI/ML Solutioning Competency Center?
Blog Three: How are some of the operational challenges like Digital Literacy impacting your journey?
Blog Four: What are some of the operationalization lessons learned?
Blog Five: What does the future hold for Scotiabank’s Advanced Analytics and AI function?
Note: This is blog five.
How are you securing visibility at the board level and ensuring AI is integrated into your governance process?
“We do this in a couple of ways, and you actually caught me after my latest board update, which was in April. We go to the board at least annually, if not bi-annually, to present our progress in data and analytics. We partner very closely with the business, as well as Finance, to ensure we are comfortable with the business impact attributable to data and analytics we present to the board. Our board is very supportive of our investments in AI, analytics, and data and understand their value to evolving our business, and to meeting important strategic commitments like ESG,” says Grace Lee.
As you look ahead what is your vision for your Analytics and AI function?
“Beyond the terrific work our teams do every day, we are working on making it easy to do great work. For so many teams, this really centers around operating model and infrastructure. Our Global Data and Analytics Platform continues to be the cornerstone of our strategy, and we are accelerating our strategic partnership with Google to move data and analytics into cloud. We view Google as the leader in AI toolkits to help our teams build and test their AI models in a way that enables speed, scale, and sustainment.
At the end of the day, it has to be about making it easy – making it easy for us to access data and making it easy for our practitioners to be their very best so that we can attract the right talent that continues to produce quality AI models. And AI really is all about learning, whether it be learning from our customers or learning from each other, and ultimately driving a lot of value for the Bank,” says Dr. Yannick Lallement.
What do you think the next phase of AI is?
“The continuation of our journey will continue to focus on making AI more practical and accessible. We are constantly scanning what the next big thing is within AI and how we can best utilize it. Whatever we choose to do, it has to deliver value and be something that we can embed into the way that we operate as a Bank, whether it be in the data and analytics team, in our business teams, or in the teams supporting Technology and Operations. And that’s where that digital literacy is really important.
Identifying where we can be beneficial, what are the good use cases, and how we prioritize what use cases we want to take on. These are all key maturity areas to evolve our solution offerings. We have done a lot of education with our stakeholders. From our perspective, our AI transformation journey is never complete, and we should be ready for perpetual change”, says Grace Lee.