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, according to IDC, which 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.
So what have finserv leaders learned so far?
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.
“We’ve all heard the phrase ‘trust is earned in drops and lost in buckets.’ For banks, that saying rings especially true,” says 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,” says Abraham Izquierdo, MD 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,” says Pessanha.
In that same vein, Andrea Cosentini, Intesa Sanpaolo’s head of Data Science and Responsible AI, explains 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 adds: “By analysing historical loan data, Intesa Sanpaolo can develop new lending models for underserved segments and 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,” says Pessanha. “Walking before you run is essential.”
Andrew McCammack, data science officer at Old National Bank, stresses 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 adds: “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,” says 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 adds. “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,” says 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,” says 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 echoes 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, says Izquierdo: “Generative AI will play an important role for us in strengthening our cybersecurity posture and fostering business continuity.”