Royal Bank of Canada

Leveraging data analytics to create exceptional experiences for over 17m customers.

Client expectations are shifting from casual, tailored greetings and the occasional timely offer to a world where customer experience deepens relationships, prioritizing the customer’s interests before the organization.

Royal Bank of Canada (RBC) is one of North America’s leading diversified financial services companies, providing personal and commercial banking, wealth management, insurance, investor, and capital markets products and services on a global basis. They are not only one of Canada’s biggest banks, but are among the largest in the world (ranked #256 in global Fortune 500 in 2019).

To be among the world’s most trusted and successful financial institutions, RBC puts the client first, always, to ensure clients thrive and communities prosper.

They do so by leveraging data analytics for greater customer insights to create exceptional customer experiences, staying connected with their customers, and reimagining the role the bank plays in their lives. With millions of customers, transforming customer experiences and deepening relationships requires bringing data together to fuel AI engines that drive decision making. Project teams are dedicated to enriching the analytical ecosystem, which RBC aptly refers to as DNA (Data & Analytics).

Royal Bank of Canada by the numbers

32.6B

Total revenue (FY2019)

17M

Clients

Countries

1,400+

Branches

Ahmed El-Kays

Senior Director, Data Architecture

Ahmad El-Kays’ responsibilities at RBC include enterprise data and analytics architecture, enterprise data modeling, enterprise data analysis and meta data engineering. Over the last couple of years, Ahmad has been tasked to build the RBC data knowledge teams and currently leads an organization of over 60 data and analytics experts. Prior to his current role, Ahmad worked at Scotiabank’s enterprise architecture groups and RBC’s enterprise information management. He holds a M.Sc. in Computer Science from McGill University in Montreal.

Automating processes for improved decision-making applying greater customer insights at scale.

“The purpose for the next few years is around every client interaction to be informed by AI, which is using AI to serve our clients according to what their needs are, not according to what we think their needs are.”

Ahmed El-Kays
Senior Director, Data Architecture Royal Bank of Canada (RBC)

The RBC DNA team set forth a data strategy and is responsible for:

Building new data capabilities, supporting modern data and analytics practices, providing a scalable and resilient data ecosystem, scaling data science enterprise-wide, generating agile insights, and building a flexible and accessible platform to meet demands driven by new RBC data and business capabilities.

Quite simply, the team relies on Teradata to enable their enterprise analytics ecosystem which becomes the "DNA" of RBC’s business. Teradata Vantage is the modern analytics platform, supporting the analytics for all of RBC’s lines of business.

Lines of business relying on analytics in Teradata Vantage include:

Personal and commercial banking

Wealth management

Insurance

Anti-money laundering/fraud

CRM systems

Branches

Call center

Sales

For organizations as large and sophisticated as RBC, enabling a modern enterprise analytics ecosystem requires multidimensional scalability to support business-critical activities.

Through scalable query concurrency, complexity, data volume, sophisticated schemas, data freshness, and mixed workloads, leading banks of the future will demand hyperscale performance across all dimensions, not just a single scalable dimension.

RBC’s data orchestration treats customers as a segment of one

“The business needs to serve the clients the insights and give them relevant offers on the spot, offering the insight or the advice as you're doing the transaction. For example, as you're on our website looking for a mortgage, we want to service you in a way that's relevant to you rather than what's relevant to the bank.”

By integrating cross-functional data, RBC stitches together lines of business to break silos and form unified customer insights. As analytical models are deployed, the insights derived from those models return to Vantage. Making for even more intelligent, orchestrated data. The result is a predictive platform that leverages and integrates all the data to provide actionable answers to any question against any data, any time.

With the help of a Teradata’s modern analytics platform performing at enterprise scale, RBC remains an enterprise that will dominate into the future.

RBC uses customer insights to automate decision-making, transform the customer experience, and deepen relationships with its 17M clients. The bank continues to unlock the imagination and insights of its people and partners to create even greater value for its clients, and the communities where they operate. “DNA has the richest data set in the bank that's both in our data warehouse and data lake. By using real-time data, we can offer the business a number of data services that is relevant to what they're trying to do. We launched a recommender engine based on machine learning and leveraging the data that we have, building models around it to offer our commercial account managers the right information to offer to their clients. Up until now, it was whatever they thought is relevant, rather than whatever they know is relevant.”

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RBC's answer:

17M customers

RBC turns to Teradata Vantage as a modern analytics platform to deepen customer relationships and create relevant financial services, ensuring their clients thrive and communities prosper.

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