When AI makes experts better, clients win

As the financial services industry embraces AI, new tools are proliferating and productivity gains are starting to accumulate across the sector. But what remains unclear is whether clients are better served.

In the institutional securities servicing business, and in BBH’s business in particular, our clients aren’t looking for AI productivity. They’re looking for better outcomes. That means lower error rates, faster resolution, greater consistency, fewer missed signals, and better information for decision-making. They want to be confident their service provider will expertly manage complexity and risk on their behalf. Where AI is used, they want to be sure that judgment and accountability remain with the people who service their business.

Productivity gains will always matter, but they are the means to an end.

Our end goal is, and has always been, to take a service modelthat works today and make it stronger, faster, more consistent, more scalable and more resilient – not because it was flawed or broken, but because technology can unlock a version that wasn’t possible before. We strive for a model where information moves more intelligently and exceptions surface earlier. Where our experts focus on the most pressing decisions, not all decisions, and our institutional knowledge scales across teams. That’s a smarter, faster service. One that becomes indispensable to our clients.

BBH’s AI platform is built to achieve those ambitious goals by supporting our experts’ ability to apply informed, directed judgment to their work, improving the quality and consistency of the outcomes delivered. Our objective is to extend their expertise to the fullest potential.

Because better-supported experts create better-served clients. That’s the real power of AI.

Today’s AI is an accelerant. But expertise is still the edge.

The path to get there

The global securities services industry has been automating for decades. Over that period, BBH has applied predictive analytics, structured automation, and machine learning to reduce manual tasks and strengthen oversight, creating value for our business and an industry-leading service for our clients.

These capabilities form a strong foundation which delivers measurably superior results to our clients today. For example, we use AI to improve NAV oversight today by isolating true exceptions faster and focusing our expert’s attention where it matters most. That’s not simply automation. It’s a shift in the operating model, from broad-based detection to focused decision support. Instead of reviewing every anomalous variance, our teams now concentrate on the exceptions that actually require judgment and critical thinking – resolving issues faster and more confidently.

Automating the work that was out of reach before

Much of the operational work in asset servicing begins with unstructured inputs. Corporate action notices, capital call documents, investor instructions, and fund transfer requests arrive in formats that vary by issuer, counterparty, market, and product. Converting, interpreting, and normalizing those messages into something usable historically resisted automation. That’s because those tasks require context, judgment, and the ability to synthesize across sources.

Today’s AI changes that. At BBH, today’s AI synthesizes information across sources, giving our experts better-prepared insights faster. An agent reads corporate action notices, extracts key terms, summarizes events, and presents structured output for review.

What were once time-consuming activities are now becoming automated and more scalable.

The transition from single agent to integrated task orchestration

At BBH, we started with single agent use cases where one agent extracts, summarizes, or prepares a first draft of an operational output. That was a practical and necessary starting point. But as we better understand the power that AI brings, we’ve shifted our thinking from how AI can perform a task faster to how AI can support entire workflows.

Now, the larger opportunity is in view: multiple capabilities connecting into broader workflows. Sequential independent agents stitched together support different stages of a process resulting in a consolidated output to an expert for validation and decision-making. That’s where AI moves from supporting a task to reshaping how a service is delivered end-to-end.

Expertise, amplified

Assuredly, AI will be transformational for the future of financial services. But as the work is done faster, human judgment and expertise will be ever more essential. The firms that will win will harness the power of AI to raise the service bar for clients.

At BBH, our experts are our strongest differentiator. They know what questions to ask. They know when an output doesn’t look right. They understand the difference between a technically correct answer and an operationally appropriate one. They recognize client nuance, market practice, control obligations, and exception risk in ways that large language models alone cannot.

When AI handles the preparation and professionals own the judgments, the result is collective intelligence. This creates a different kind of scale, measured by speed, quality, consistency, and confidence in the decisions we make on behalf of our clients. In a trust business like ours, confidence and accountability are vital.

Accountability is the operating model 

A successful AI program must be founded on structural models that emphasize control, review and accountability. Without those, AI creates the appearance of progress while introducing new forms of operational complexity and risk. With it, AI scales our service with confidence.

At BBH, we take a centralized approach to how AI is designed, governed, and distributed across the organization. We identify common patterns, build reusable capabilities, and apply them across workflows so that impact advances through discipline, not duplication.

Our AI Acceptable Use Committee is engaged before any use case goes live. This governance committee reviews all AI-related initiatives and provides a documented risk mitigation assessment for each use case. If there are unanswered questions, they are addressed by a committee of expert people, not by an agent.

Our accountability model requires clear answers to practical questions. Who owns the decision at each step? Where is human review required? How are exceptions escalated? How will outputs be monitored over time? These aren’t treated as open questions. They are built into how every AI-enabled workflow is designed, approved, and governed by defined owners.

For us, accountability reinforces reliability and stability, an approach which contributes to building long-term, trusted relationships with clients.

Designed by experts, built for clients

For more than 200 years, BBH has thoughtfully and successfully combined new technologies with deep expertise, disciplined execution, and clear accountability. Our AI journey is no different. Centered around the human judgment of our experts, our AI approach enhances BBH’s qualities that our clients value – exceptional service, trusted expertise, and innovative thinking.

With AI, productivity is the means. Expertise is the edge. Better service is the goal.