BNY CEO Bets on AI Transformation

BNY CEO Robin Vince says the bank is using artificial intelligence to reshape its operations and client services, arguing that the company is well positioned to benefit from AI. BNY traces its lineage to the 1784 formation of The Bank of New York; its current form followed a 2007 merger with Mellon Financial Corporation. It ranks as the 10th-largest bank in the United States. The bank allocates $4 billion of its $13 billion capital expenditure budget to technology, with a substantial share now going to AI. Vince says BNY has discussed AI for three years and has invested in it for longer, expecting it to reduce friction, improve outcomes and create internal capacity.

Vince describes BNY’s approach as “AI is for everyone, everywhere, and everything.” The bank built Eliza, an enterprise AI platform, and is investing in staff capabilities so teams can develop and govern AI consistently and use it at scale. Eliza analyzes process steps, system interactions and workflow patterns to help employees rethink how work is done. BNY says it may extend these capabilities to clients to address similar challenges and optimize workflows end to end, creating more capacity for staff and improving client services.

Vince names three strategic goals: generate internal capacity so employees can take on more work without increasing the expense base; improve products and features; and provide clients with services that were not economically viable without AI. BNY has more than 400 AI solutions in production, and Vince expects that number to grow. On returns, he says the bank is generating value and intends to invest further, without seeking false precision in measuring overall returns. It tracks AI spending more closely through financial operations (FinOps), including token costs, model selection and routing decisions built into Eliza.

Vince says BNY manages costs by working with AI providers on commercial arrangements and product development, and by routing work to suitable models, including open-source options and models that are six or 12 months old. Eliza provides a shared layer for employees and AI agents to use those models, enabling routing across providers. Last month, BNY opened the BNY AI Lab at Carnegie Mellon University to advance research on verifying AI-generated code and evaluating agents for critical systems. Vince says the bank aims to pursue AI with ambition, intensity and discipline to improve its commercial, operational and financial performance.

BNY CEO Robin Vince says the bank is using artificial intelligence to reshape its operations and client services, arguing that the company is well positioned to benefit from AI. BNY traces its lineage to the 1784 formation of The Bank of New York; its current form followed a 2007 merger with Mellon Financial Corporation. It ranks as the 10th-largest bank in the United States. The bank allocates $4 billion of its $13 billion capital expenditure budget to technology, with a substantial share now going to AI. Vince says BNY has discussed AI for three years and has invested in it for longer, expecting it to reduce friction, improve outcomes and create internal capacity.

Vince describes BNY’s approach as “AI is for everyone, everywhere, and everything.” The bank built Eliza, an enterprise AI platform, and is investing in staff capabilities so teams can develop and govern AI consistently and use it at scale. Eliza analyzes process steps, system interactions and workflow patterns to help employees rethink how work is done. BNY says it may extend these capabilities to clients to address similar challenges and optimize workflows end to end, creating more capacity for staff and improving client services.

Vince names three strategic goals: generate internal capacity so employees can take on more work without increasing the expense base; improve products and features; and provide clients with services that were not economically viable without AI. BNY has more than 400 AI solutions in production, and Vince expects that number to grow. On returns, he says the bank is generating value and intends to invest further, without seeking false precision in measuring overall returns. It tracks AI spending more closely through financial operations (FinOps), including token costs, model selection and routing decisions built into Eliza.

Vince says BNY manages costs by working with AI providers on commercial arrangements and product development, and by routing work to suitable models, including open-source options and models that are six or 12 months old. Eliza provides a shared layer for employees and AI agents to use those models, enabling routing across providers. Last month, BNY opened the BNY AI Lab at Carnegie Mellon University to advance research on verifying AI-generated code and evaluating agents for critical systems. Vince says the bank aims to pursue AI with ambition, intensity and discipline to improve its commercial, operational and financial performance.