Scotiabank has launched a new Global AI Platform that provides customers with intelligent and personalized financial advice.
The platform is enabling the Bank to provide fast, relevant advice by anticipating and understanding customers’ needs. It is being used to operationalize several customer models into its retail banking businesses across the Americas.
The platform’s compute power enables the fast delivery of insights, ultimately providing better data to support customers in their financial goals. It has also been designed to be used in all business lines across the enterprise.
Phil Thomas, EVP Customer Insights, Data and Analytics, Scotiabank, commented:
“A key part of Scotiabank’s AI strategy has been to build a strong talent pool of data scientists and data engineers, fully integrating them with business analytics professionals who have deep banking knowledge,
To enable our winning teams to deliver financially impactful AI initiatives, we’ve created a global modern analytics platform that is flexible, resilient and integrated into our businesses.”
Dan Rees, Group Head, Canadian Banking for Scotiabank, commented:
“This global pandemic has reinforced the importance of delivering customized financial advice that speaks to our customers’ unique business and household situations,
Scotiabank’s investments in technology have allowed us to continue to provide the valued advice and support our customers have told us they’re receiving from us, as a leading bank in customer satisfaction.”
Nacho Deschamps, Group Head, International Banking & Digital Transformation, Scotiabank, commented:
“Scotiabank has been strategically integrating AI, data and analytics directly into the business across the Americas,
The Bank’s investment in the new Global AI Platform will enable us to continually drive transformation at a rapid pace with data-driven solutions that provide a better understanding of our customers.”
Scotiabank intends to evolve the platform to seamlessly deploy analytics applications, not just to on-premise hardware but also in cloud-based environments. This will enable the platform to satisfy the ever-increasing demand for analytics computations. Additionally, it makes available as much GPU compute as needed to enable complex AI tasks.
