AI is no longer a distant promise on the banking industry’s horizon. It’s a present-day imperative – and banks are rising to the moment. IDC forecasts the sector’s annual AI spending will reach nearly $67 billion globally by 2028, more than double the estimated $31 billion banks invested in 2024. What have finserv leaders learned so far?
With Sibos 2025 underway, a new report from SAS, From Algorithms to Impact: Banking’s AI Future, presents perspectives from forward-looking executives at Banorte (Mexico), Intesa Sanpaolo (Italy), Millennium BCP (Portugal) and Old National Bank (US) – institutions proving that practical AI innovation doesn’t depend on size. The report distils their insights into five essential lessons for charting a responsible and profitable path.
SAS is bringing these and other guidance to life at this week’s Sibos conference in Frankfurt. With five speaking engagements, SAS experts are defining how banks can harness AI grounded in transparency, fairness and trust to drive innovation.
“We’ve all heard the phrase ‘trust is earned in drops and lost in buckets.’ For banks, that saying rings especially true,” said Stu Bradley, Senior Vice President of Fraud, Risk and Compliance Solutions at SAS. “Trust is financial services’ most valuable currency – and its most fragile. AI can help banks strengthen trust when deployed responsibly, but without strong governance and guardrails, the risks rise faster than the rewards.”
Lesson 1: Anchor your business case, not your buzzwords.
Banks can’t afford to treat AI as a side project, nor to deploy it in silos. AI must be fully integrated into everyday business strategy and completely aligned with building long-term resilience and competitiveness, advise industry executives.
“Innovation and AI must be recognised as a pillar of the institution’s strategy,” said Abraham Izquierdo, Managing Director of Trading and Treasury Risks at Banorte. “Leadership from the top is non-negotiable.”
For José Miguel Pessanha, Chief Risk Officer at Millennium BCP, the priority is clear: “We are developing models to help us better prepare for adverse scenarios in the next five years. If an economic crisis arises, we can more effectively mitigate the effects of a rise in defaults.”
Lesson 2: Lead with people, not technology.
While AI is rapidly changing how banks’ employees approach their jobs, human judgment remains indispensable. Industry leaders agree: Investment in skills and culture is as important as investment in platforms and AI-powered banking solutions.
“AI tools cannot definitively answer key questions: How will I minimise the impacts for the bank? What will be the risk strategy afterwards? This comes down to the creative problem-solving abilities of leadership,” said Pessanha.
In that same vein, Andrea Cosentini, Intesa Sanpaolo’s Head of Data Science and Responsible AI, explained how the culture side of people-first leadership has become one of the bank’s differentiators. “By recognising data-driven successes, we create a culture where data is valued as a strategic asset.”
This shift is allowing Intesa Sanpaolo to better serve its customers and communities, he added: “By analysing historical loan data, Intesa Sanpaolo can develop new lending models for underserved segments, promoting financial inclusion.”
Lesson 3: Get the fundamentals right before you scale.
Banking leaders emphasise the importance of establishing a core infrastructure and critical capabilities – think a robust, cloud-native platform with well-established data governance and synthetic data principles – before pursuing advanced use cases.
“We saw the need to harmonise our data to service different needs – from provisioning to capital calculations, liquidity calculations and interest rate risk,” said Pessanha. “Walking before you run is essential.”
Andrew McCammack, Data Science Officer at Old National Bank, stressed that even light, low-code applications require robust foundations to scale: “GenAI is exceptionally helpful in developing a full code base. With this insight, we’re driving a new wave of innovation.”
Banorte’s Izquierdo added, “AI and cloud deployments must be multi-year and step-by-step. Recognise your long-term ambition, but set short-term, precise goals. Commit to a pace that maintains compliance and builds trust.”
Lesson 4: Empower your bank’s innovators.
Future-proofing with AI means shifting from procuring innovation to driving it. Equipping IT and developer teams with AI tools unleashes productivity gains, freeing employees from menial tasks and unlocking their capacity for deeper problem-solving and innovation.
A telling example: Faced with the tedious, manual process of loan data entry, Old National used AI to generate 90% of the code for a new web-based workflow. “Microsoft Excel sheets don’t even exist anymore,” said McCammack. “Now, people have time for deep analysis that’s more rewarding and valuable to the business.”
“We encourage an environment where asking ‘why’ is valued,” Pessanha of Millennium added. “Data scientists can then design experiments and models to test hypotheses and validate – or disprove – assumptions, potentially revealing breakthrough solutions.”
Banorte is seeing similar innovation gains, according to Izquierdo: “We can make strategic decisions for the short-term, medium-term and long-term based on facts, data and modeling. We’re able to better pivot and respond directly to volatility or to complexity in markets.”
Lesson 5: Stay curious, stay connected, stay innovative.
There’s nothing set-it-and-forget-it about AI. AI is an ongoing journey of experimentation, feedback and adaptation. Banking leaders also stress the importance of connecting with others – both internal stakeholders and external parties – to keep pace with AI’s rapid evolution, from today’s GenAI deployments to tomorrow’s agentic and quantum AI innovations.
“We’re looking to connect more with academics and startups to understand what they are focusing on,” said Millennium’s Pessanha.
“We’ve started pursuing a strategy where we are building a whole suite of light applications, where AI is used to build the source code […],” said McCammack of Old National. “If you want to scale that and roll it out to the enterprise, you need a full code base, and GenAI is exceptionally helpful in developing it.”
Cosentini of Intesa Sanpaolo echoed the same trend: “GenAI can fuel innovation by generating new ideas and solutions, helping us stay ahead of the competition and adapt to changing market conditions. However, its full potential is realised only when guided by human oversight, ensuring that creativity, responsibility and strategic judgment remain at the centre of the process.”
Banorte is also stretching its use of GenAI, said Izquierdo: “Generative AI will play an important role for us in strengthening our cybersecurity posture and fostering business continuity.”
SAS at Sibos: Driving the dialogue on AI’s next frontier
As a trusted partner to the global banking community for nearly five decades, SAS isn’t merely participating in Sibos 2025. The data and AI leader is helping lead the conversation on how AI is redefining the financial services landscape.
Sibos will feature SAS experts in five high-impact conference sessions that explore topics ranging from real-time decisioning in payments and generative AI-driven fraud prevention to navigating workplace transformation and achieving ROI with GenAI.
SAS will also showcase live demos and practical innovations that empower banks to modernise operations, elevate customer experience and strengthen compliance. Attendees are invited to join the conversation in person throughout the conference at Sibos Booth E063.