Royal Bank of Canada is seeing increased efficiency and output through continued investment and deployment of AI.  

The $1.1 trillion bank launched RBC Assist for 30,000 employees in this year, Geoffrey Morton, senior director of fraud strategy at RBC, told FinAi News. This internal, gen AI-driven chatbot is designed to help employees perform functions ranging from checking company policies to writing code, Morton said.

“Think of it as an internal ChatGPT trained on our bank’s data,” he said. 

During the company’s fiscal fourth-quarter earnings call today, Chief Executive Dave McKay said RBC has been deploying gen AI for:  

• Coding;  

• Fighting fraud;  

• Personalized banking; and  

• Capital markets functions.  

“We’re also leveraging AI to build the technology platform of the future, showing early results in enhanced security to protect the bank and clients, technology operations, and AI-enabled developer productivity,” McKay said. “This includes the development of over 5 million lines of code, over 55,000 code reviews and over 3,000 test suites.” 

The bank expects to generate $700 million to $1 billion of enterprise value through AI, he said. The bank didn’t disclose the amount of its AI investment. 

Getting to ROI 

According to an RBC memo published today, the $1.1 trillion bank calculates the value AI creates by totaling the yearly benefits it expects to receive through: 

• Additional revenue; 

• Avoiding costs; 

• Lower expenses;  

• Less fraud; and  

• Reduced risk losses. 

The bank then subtracts its spend on software and building the AI infrastructure, according to the memo. 

“Importantly, our target is net of investments, including building on investments already made in data storage, GPU clusters, proprietary LLMs, risk governance and in people,” McKay said on the call. 

The bank is working with chip designer Nvidia to deploy gen AI tools within its capital markets operations, according to FinAi News’ prior reporting. 

Nvidia’s gen AI-aided tool has helped RBC: 

• Allow agents to process 10 times more documents;  

• Generate reports 60% faster; and  

• Shrink the alpha pattern discovery timeline by nearly 80%. 

The bank expects to continue seeing “the benefits of our long-term organic investments in data platforms and foundational models,” McKay said. 

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