Artificial intelligence is no longer a side project in banking. It is becoming the engine reshaping how institutions operate, how advisers work and how clients experience financial services. But the real barrier to scaling AI lies deeper than the tools themselves.
Much of the industry still runs on technology foundations built decades ago, and systems designed for batch processing and siloed data cannot support the speed and intelligence modern AI demands.
As part of FinTech Global’s WealthTech100, Harry Slade spoke with Kaue Tozzi, Head of Product Strategy & Partnerships at Temenos, about how AI is reshaping the architecture of financial services and what banks must do to remain competitive in the next phase of industry transformation.
From feature to foundation
The financial services industry has experimented with AI for years, but its role is now shifting from experimentation to core capability.
“The most significant technological shift shaping wealth management is AI,” Tozzi said. “Its impact is redefining how banks operate, compete and serve clients.”
The constraint is not the technology itself but the infrastructure supporting it.
Many institutions still rely on rigid systems designed long before real-time analytics or machine learning were possible. Fragmented data flows and batch processing make it difficult to deploy intelligent systems that depend on constant access to current information.
“AI cannot be adopted effectively on legacy, monolithic systems,” Tozzi explained. “Batch-based infrastructures designed decades ago cannot support the scale, speed and adaptability that AI demands.”
As a result, attention is shifting toward platform architecture. Instead of adding isolated AI capabilities, banks are beginning to modernise core systems so intelligence can be embedded across everyday operations.
For Temenos, that means cloud-native, composable platforms capable of integrating real-time data and analytics across the organisation.
“Banks that embed intelligence directly into their core platforms, rather than bolting it on, gain a structural advantage in agility, cost efficiency and client experience,” Tozzi explained.
Trust remains the industry’s most valuable currency
Technological transformation is occurring alongside rising regulatory scrutiny and customer expectations. For banks, innovation must be balanced with the responsibility to safeguard data and maintain resilience.
“Trust has become the true differentiator, especially in wealth,” Tozzi said.
The spread of AI across banking platforms is also prompting a rethink of security architecture.
“This is forcing a clear shift away from perimeter-based security toward zero-trust models,” Tozzi explained. “Access is continuously verified, controls are enforced by design and trust is earned at every interaction.”
Embedding these controls within core platforms allows banks to innovate without compromising governance.
“AI innovation is paired with explainability, auditability and operational resilience,” Tozzi explained.
In wealth management, institutions must show that automated decision-making remains transparent and compliant with regulatory standards.
AI begins to reshape the client experience
While much of the debate around AI focuses on infrastructure and governance, its most visible effects are beginning to appear in the everyday interactions between financial institutions and their clients.
Banks are already using AI to remove administrative friction from wealth management. Tasks such as onboarding documentation, compliance checks and client preparation are increasingly handled automatically.
For Tozzi, this marks the beginning of a wider shift in how financial services are delivered.
“AI is already improving financial services experiences in a very practical way. It removes friction and adds intelligence at scale without compromising trust,” he said. “In wealth, that means automating the heavy administrative lift, including onboarding, checks, preparation and documentation, and turning data into guidance with clear explanations, next-best actions and more relevant personalisation.”
The implications extend beyond efficiency.
“The shift is that AI is becoming the interface, not just a feature,” Tozzi explained. “It is moving financial services from static workflows to conversational, contextual support across channels.”
Despite these advances, human judgement remains central.
“In a regulated industry, the winning model is human-in-theloop, transparent and accountable,” Tozzi said. “AI doesn’t replace advisers. It amplifies judgement and acts as a force multiplier across teams.”
Flexibility becomes essential for global banking
As technology capabilities expand, banks are also confronting a more complex operating environment. Clients, assets and regulations increasingly span jurisdictions, forcing institutions to rethink how infrastructure supports international growth.
“There is no single operating model that fits every market, client or regulator, especially in wealth management where clients, assets and regulatory obligations increasingly span jurisdictions,” Tozzi said.
Technology platforms must therefore accommodate differing regulatory requirements while maintaining global scale.
“Flexible deployment models allow institutions to scale globally and meet local requirements around data, security and resilience,” he explained. “Cloud-native architectures deliver speed and scalability, while hybrid models provide the control and compliance many banks still require.”
The dangers of getting modernisation wrong
Recognising the need for modernisation is one challenge. Executing it successfully is another.
“Banks most often get modernisation wrong by trying to do too much at once,” Tozzi said. “They either attempt high-risk big-bang core replacements or they layer new technology on top of fragmented legacy systems. Both approaches limit agility and slow real progress.”
Instead, Temenos advocates a structured approach.
“The smarter path is progressive modernisation,” Tozzi explained. “Fix the data foundations first, modernise the core through composable capabilities, extend innovation through targeted solutions and embed intelligence directly into everyday workflows.”
Under this model, transformation becomes continuous rather than disruptive.
“Modernisation is not about bolting AI at the end,” Tozzi said. “It is about building a foundation that can continuously evolve.”
The capabilities defining the next generation of banks
Several capabilities are beginning to distinguish the most competitive banks.
“In wealth management, we see six capabilities standing out,” Tozzi said. “AI embedded directly into adviser workflows rather than treated as a separate tool. Digitalfirst service models combining self-service with human-led advice. Global cross-border operating capabilities reflecting how wealth and clients are increasingly mobile.”
He also points to the growing importance of real-time intelligence.
“Real-time portfolio, risk and compliance intelligence will replace batch-based processes,” he explained.
New forms of digital infrastructure are also reshaping the asset landscape.
“Banks will also need support for digital and tokenised assets, including custody, compliance and secure integration,” Tozzi said, “as well as composable platforms that allow institutions to integrate and manage best-ofbreed solutions as the ecosystem evolves.”
Rethinking technology as a strategic asset
For Tozzi, the institutions best positioned to navigate this transition will rethink how they view technology. “Stop treating technology as a cost to control and start treating it as a driver of trust, growth and differentiation,” he said. “Technology alone isn’t the answer,” Tozzi added. “But when it is combined with strong human judgement and a relentless focus on client outcomes, it becomes a powerful competitive advantage.” The banks that modernise their foundations today will be best positioned to lead the next era of AI-enabled banking
The full WealthTech100, including profiles on each company, can be found here.
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