J.P. Morgan Payments executive Matthew McCown will take the stage at the FinAi Banking Summit in March, adding a big-name voice to a conference focused on how banks are actually using artificial intelligence at scale. The event arrives as financial institutions face rising pressure to turn AI talk into measurable results.
A Key Voice From J.P. Morgan Payments
Matthew McCown, executive director of the data and analytics team at J.P. Morgan Payments, is scheduled to speak on Tuesday, March 3, 2026.
His appearance is part of the FinAi Banking Summit, which will be held March 2–3 at the Westin Denver Downtown.
McCown will join a panel titled “AI strategy at scale: Lessons from global banks” at 11 a.m. local time. The session is expected to focus less on theory and more on execution, something banks are increasingly being asked to show.
One sentence sums up the draw. This is about what works, not what sounds good.
Panel Focused on Real-World AI Use
McCown will be joined on the panel by Prageeth Sandakalum, vice president and principal product manager for digital, data and AI at U.S. Bank.
Together, the panelists are set to discuss how large banks are applying AI across complex organizations without losing control of risk, governance, or customer trust.
According to the event outline, discussion points will include:
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Applying AI across products and operations
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Aligning technology efforts with broader business goals
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Building data-driven products that can grow without breaking
These topics may sound familiar, but the difference lies in scale. Global banks don’t get second chances when systems fail.
McCown’s Role Inside a Massive Payments Engine
McCown joined J.P. Morgan in 2018 and has held several roles within its payments data and analytics organization.
Today, he leads teams that include product analysts, data scientists, and technologists. Their work supports one of the largest payments businesses in the world, touching merchants, corporates, financial institutions, and consumers across regions.
That context matters.
Payments sit at the intersection of speed, trust, and regulation. Any AI system operating there must be accurate, explainable, and resilient. There’s little tolerance for guesswork.
McCown’s perspective comes from operating inside those constraints, not around them.
J.P. Morgan’s AI Track Record Draws Attention
J.P. Morgan’s broader AI efforts have drawn industry notice in recent years.
In October, the bank ranked first across innovation, leadership, and transparency in the Evident AI 2025 Evident AI Index. The ranking evaluated how financial institutions deploy AI responsibly and at scale.
Following the release, Teresa Heitsenrether, the bank’s chief data and analytics officer, said the recognition reflected sustained investment rather than one-off projects.
The message was clear. AI has to show returns, not just promise them.
LLM Suite Signals a Shift From Pilots to Production
One example often cited is J.P. Morgan’s rollout of its AI-driven LLM Suite in October.
The internal platform is designed to support a range of use cases, from operational efficiency to client-facing workflows. According to the bank, the system has already delivered measurable efficiency gains, a phrase investors pay attention to.
For a bank with roughly $4 trillion in assets, small percentage improvements translate into serious money.
That’s why sessions like McCown’s matter. They offer a look at how institutions move beyond pilots and proofs of concept.
Why FinAi Is Drawing Growing Interest
The FinAi Banking Summit has carved out a niche by focusing narrowly on AI in financial services.
Rather than broad tech showcases, the agenda leans toward governance, deployment challenges, and lessons learned the hard way. Attendees typically include bank executives, product leaders, risk specialists, and data teams.
Holding the event in Denver also reflects a shift away from traditional coastal conference hubs.
It’s meant to be practical, not flashy.
For many attendees, hearing from practitioners inside large banks offers more value than keynote speeches filled with predictions.
Payments as a Testing Ground for AI
Payments is often where AI ambitions meet reality first.
Fraud detection, transaction monitoring, pricing, routing, and customer support all generate huge volumes of data. That makes payments attractive for AI use, but also unforgiving when systems fail.
False positives annoy customers. False negatives cost money.
McCown’s experience sits squarely in that tension, which makes his input especially relevant as banks try to scale AI without undermining reliability.
One short line captures it. In payments, mistakes are loud.
A Broader Banking Conversation
The panel McCown joins is part of a larger conversation taking place across the industry.
Banks face rising competition from fintech firms that move faster and take more risk. At the same time, regulators are paying closer attention to how AI decisions are made and explained.
That leaves little room for shortcuts.
Events like FinAi function as a kind of pressure valve, giving leaders space to compare notes, admit missteps, and recalibrate.
Listening to peers who’ve already rolled systems out can save months of trial and error.
Looking Ahead to March in Denver
McCown’s appearance adds weight to the summit’s agenda, especially for attendees focused on payments, data infrastructure, and enterprise AI governance.
While the session itself will last an hour, the implications stretch further. Banks watching from the sidelines are eager to learn which approaches scale cleanly and which quietly fail.
By March, the AI conversation in banking will likely be louder, sharper, and more demanding.
That makes firsthand insight from inside J.P. Morgan Payments particularly timely.
