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DeepSee.ai and Broadridge discuss accelerating T+1 preparedness with FTF News.
June 23, 2026 – As Europe races toward T+1, we wanted to have a candid conversation about what’s holding the industry back, and tackle these challenges together with our partner Broadridge.
We sat down with Steve Shillingford, David Kirby and Maureen Lowe (founder, president & editor-in-chief of FTF News) to discuss the implications for firms getting ready for the transition and what they can do to accelerate their preparedness.
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Keep reading for some of our favorite highlights from this episode.
The “Fix Your Data First” Myth and What Actually Moves the Needle Post-Trade
The advice has become almost axiomatic in financial services: before you layer AI on top of your operations, clean up your data. Once it is organized and consistent, the automation can help you.
Steve Shillingford, CEO and founder of DeepSee, respectfully disagrees.
“No one with a data lake actually has clean data,” he said in the interview. “That’s a never-ending battle. Better to put your effort into context — and let agents do that work in real time.”
The Problem with Waiting for Perfect
The “clean data first” mandate sounds reasonable in theory. In practice, it’s a moving target that gives firms an excuse to delay modernization indefinitely.
Data quality is a continuous process, not a destination. While firms wait for the mythical clean data lake, settlement cycles keep shortening, volumes keep growing, and operational pressure keeps mounting.
T+1 is already live in the US. Europe and the UK are targeting October 2027, and that transition is, by most accounts, meaningfully more complex than North America’s. The pressure to resolve breaks faster, catch SSI errors earlier, and process more with leaner teams isn’t going away. Waiting for pristine data before deploying intelligent automation isn’t a risk management strategy. It’s a delay strategy.
Orchestration Over Agents
One of the more nuanced points from the conversation is the distinction between deploying an AI agent and building real orchestration. Dropping a single AI agent into an existing workflow is easy. Getting agents to work together (passing context, handling exceptions, routing decisions to the right place) is where the real complexity lives and where the real value gets created.
This distinction matters because a lot of post-trade operations aren’t broken at the level of a single task. They’re broken at the handoff. A trade break email arrives in a shared inbox. Someone has to read it, understand it, figure out who owns it, escalate it, and ultimately resolve it.
That’s not one problem. It’s five or six, strung together by human judgment and institutional knowledge that’s almost impossible to document.
Email, unglamorous as it sounds, is where so much of this workflow starts and ends. It’s the connective tissue of post-trade operations, and where things fall apart when volume spikes and headcount doesn’t.
On AI and Jobs
The conversation also touched on a question that comes up in every AI discussion in financial services: What happens to the people?
Shillingford’s framing is worth noting: reallocation, not replacement.
The future isn’t a trading floor with no humans. It’s one where humans are managing machines, reviewing exceptions that agents surface, making judgment calls that require institutional knowledge and relationship context. The volume of work isn’t going down, just changing.
The DeepSee and Broadridge Partnership
The conversation itself was a byproduct of something significant: a formal partnership between DeepSee and Broadridge, backed by an equity stake. For DeepSee, it’s validation from one of the most deeply embedded infrastructure providers in global capital markets. For Broadridge clients, it’s a path to purpose-built AI agents that don’t require the firm to have solved their data problems before they can start seeing value.
That’s the through-line of everything Shillingford articulated: you don’t have to have everything perfect to move forward. You need the right context, the right orchestration, and agents that are built to work in the messy reality of financial operations.
The settlement clock is ticking. The firms that wait for perfect will still be waiting when the deadline arrives.
