“Legacy” is the typical pejorative shorthand the financial services industry has settled on when describing its own incumbent and slow-moving infrastructure, rigid processes and sprawling technology stacks.
They’re the same layers that FinTech challengers promised to displace. But as artificial intelligence reshapes the economics of modernization, the payments and financial industry is beginning to reconsider whether legacy systems are liabilities to escape, or assets to orchestrate.
“The systems that are in place, I think something like 75% of transactions are still running over mainframes, and it’s because they work, and the need is for reliability and security,” Garrett Baird, vice president of product, banking and FinTech at Paymentus, told PYMNTS during a discussion for the May edition of the “What’s Next in Payments” series, “When Legacy Becomes Leverage.”
“The challenge now is that customer expectations have evolved,” Baird added. “Customers are beginning to expect more speed, more intelligence, more personalization, and have those experiences be totally connected.”
The result is a growing tension between stable infrastructure and modern experience design.
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Orchestration Solves ‘Russian Nesting Dolls’
In many financial institutions, decades of incremental technology layering have produced operational fragmentation that slows innovation even as institutions invest heavily in modernization programs.
Baird described one FinTech chief technology officer’s characterization of modern banking architecture as “Russian nesting dolls” made up of layers of middleware, APIs and legacy platforms stacked atop one another over years of expansion and integration.
That complexity, however, is precisely where the modernization debate is evolving. The question is not whether incumbents should replace legacy systems wholesale, but whether AI can bring about the orchestration necessary to unlock the intelligence trapped within them.
“It’s not about abandoning legacy systems, but modernizing around them intelligently,” Baird said.
That orchestration model reflects a broader shift underway across enterprise software. AI is emerging not simply as an automation layer, but as connective tissue capable of navigating fragmented systems and surfacing context across them. In payments and banking, where customer data often resides across disconnected cores and service environments, that capability could fundamentally alter how institutions modernize.
“AI is uniquely good at finding the value and the patterns in the history of one’s relationship with an organization,” Baird said, adding that the future moat may not be speed or user experience alone but accumulated relational context across ecosystems.
When asked whether incumbents are advantaged or constrained by their legacy positions, Baird said he thinks “the answer is both.”
“The advantages that incumbents bring, like scale and maturity around compliance and regulation, they obviously have the distribution scale too,” he said. “Those things matter tremendously in financial services.”
Yet, large financial institutions are often bogged down by internal silos, entrenched operating models, and modernization programs focused too narrowly on rip-and-replace strategies.
“There’s a much bigger opportunity when it comes to unlocking the intelligence that already exists within these systems,” Baird said.
Reinvention Is a Business Model Question
The competitive battlefield across financial services is one that’s shifting toward orchestration, identity and continuity across channels. Expectations formed by eCommerce and consumer apps are migrating directly into regulated industries, and consumers no longer tolerate fragmented service experiences simply because payments are mission-critical.
Baird noted that the industry has long assumed consumers will tolerate friction — endless screens, manual data entry, repeated authentication — so long as the payment clears. That assumption, he says, is getting harder to defend.
The deeper implication is that AI may be shifting the strategic center of gravity in financial services away from infrastructure ownership alone and toward contextual intelligence layered on top of existing infrastructure. That dynamic could benefit incumbents and FinTechs, provided they partner effectively.
“Anything that contributes further to fragmentation, anything that creates more dolls, if you will, those become a problem,” Baird said.
That concern is becoming more relevant as financial institutions race to deploy AI capabilities across customer service, underwriting, fraud management and operations.
Without unified orchestration and identity layers, organizations risk creating a new generation of fragmented experiences built on top of already fragmented infrastructure. In an industry built on trust, reliability and scale, legacy may no longer be the obstacle. Properly orchestrated, it may become the advantage.
