How Scotiabank is implementing AI for greater customer retention

As one of Canada’s Big Five banks, the Bank of Nova Scotia is taking an approach to data, analytics, and AI intended to better understand and serve customers, said Grace Lee, its chief data and analytics officer. Her charter is to advance business growth, customer experience, and operational efficiency through the use of AI, machine learning, and data-driven insights at the bank better known as Scotiabank.

The stakes in customer retention are high: Scotiabank has more than 10 million retail, small business, and commercial customers in Canada, as well as 10 million retail and commercial customers in Latin America, the Caribbean, and Central America. The bank has about 90,000 employees and assets of about $1.2 trillion.

Scotiabank’s two areas of AI application

Over the past couple of years, Scotiabank has engaged in an AI strategy that is very focused on last-mile execution, Lee said. “Where we’ve seen other organizations sometimes fail to capture the benefits of AI and machine learning is that it doesn’t necessarily always result in practical outcomes,” she said. “So, you’ll find that sometimes we call it ‘blue-collar’ AI or analytics, but it’s really around making sure that we see the [AI] models through all the way from inception to [deployment into] production.”

And that means that AI is embedded directly into existing processes and delivering real benefits to stakeholders, such as providing timely advice and personalized offerings for customers, creating some degree of efficiency so employees can better serve customers, or enabling the bank to better predict when its customers might be going through some distress, Lee said. “There is a lot more that we can be doing to actively monitor and really understand the behaviours and therefore the needs and preferences of our customers,” she said.