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More than 30,000 professionals make up the ecosystem of Cetif: we facilitate the meeting and exchange between banks, insurers and companies in an academic Center, competent and independent environment to share knowledge, experience and strategies on the most innovative drivers of change.
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More than 40 Executive Education tracks, 4 Master's programs and numerous Company Specific Programs: we transfer innovative financial-oriented content with a scientific approach.
An experimental spin off combining academic research and entrepreneurial approach: we turn innovation and digitization into a concrete business advantage.
Today, we can say thatIT modernizationin the Italian banking sector is well underway, even if it is proceeding at different speeds depending on the situation. On the one hand, we see institutions migrating to hybrid cloud architectures, redesigning entire application domains, and working on new data platforms. On the other hand, there are banks that are proceeding more cautiously, often because they are dealing with a very complex technological legacy.
And it is precisely this legacy that represents the biggest obstacle: not so much because it is "old," but becauseit is deeply intertwined with business processes. Dismantling or rewriting it is never a simple technical exercise: it means facing high costs, operational risks, and long periods in which new and historical systems must coexist.
However, there arethree forcesdriving change. The first is technology, which now offers completely new possibilities thanks to the cloud, AI, and the ability to process and leverage large volumes of data.
The second is competition, which requires banks to be much faster in both launching products and improving the services they offer to customers. And then there is the regulatory front, which in recent years has seen a significant increase in security, resilience, and control requirements. All these factors combined create an environment in which innovation is no longer an option but a necessity.
It is in this scenario that the cloud is becoming a key enabler. It allows you to scale capacity and resources very quickly, test solutions with greater agility, and draw on advanced services without having to build them internally.
At the same time, the centrality of data is transforming the way banks make decisions and design services. Aneffective data platformnot only allows banks to better understand their customers and personalize services, but also to automate processes and streamline internal functions that historically required a lot of time and manual labor.
Of course, all this only works if there is clear governance and adequate skills in place: the cloud is not a magic wand, and it can also be very expensive if not managed properly.
The introduction of AI is further accelerating this transformation. It is not just a matter of creating chatbots or conversational tools, but of redesigning entire architectures. To take advantage of next-generation models, you need consolidated data platforms, well-governed flows, intelligently exposed APIs, and tools capable of bringing insights to the heart of operational processes.
It is a profound change that many banks are tackling, starting with pilot projects, while others have already defined roadmaps and long-term partnerships. The maturity varies, but the direction is the same for everyone.
This technical evolution is also changing the way people work. We are seeing increasing integration between IT and business: more cross-functional teams, product-oriented roles, and new professional figures specializing in cloud, data, architecture, and security.
It is a cultural change even before it is a technological one. Banks are investing heavily in internal training, creating dedicated courses and actual centers of expertise.Innovation governanceis also evolving: on the one hand, clear and centralized rules are needed to ensure security and quality; on the other hand, teams must be given sufficient autonomy to experiment and bring new solutions to market quickly.
On the regulatory front, there is no doubt that regulations such asDORA, GDPR, the AI Act, and supervisory guidelines have a significant impact on technological choices. It is impossible to ignore them because they set very stringent requirements for resilience, data protection, supplier management, and algorithm transparency.
This may slow down some decisions, but at the same time it forces the industry to build more robust and controllable architectures. And, in the long run, it translates into greater confidence and stability.
Looking ahead, the priorities for accelerating modernization are clear: systematically measure system obsolescence, strengthen data platforms, seriously manage costs and cloud architectures, and launch structured legacy disposal programs.
The remaining obstacles are mainly organizational and cultural: it is not just a question of replacing technologies, but of changing mindsets, processes, and ways of collaborating. When this cultural shift takes place, modernization projects become much faster and more effective.
If we look ahead five or ten years, the IT infrastructure of banks will be very different from what it is today. Hybrid models will prevail, with more extensive use of the cloud and solutions that simultaneously guarantee flexibility, data sovereignty, and security.
The data platform will be at the center of everything: both for customer services and internal operations. The architectures will be modular, based on APIs and microservices, and automation will be widespread at every level—from software development to security controls.
AI will become a pervasive element, integrated into decisions, processes, and daily operational support. Alongside these, technologies such as data meshes, advancedMLOpstools, and intelligent observability solutions will emerge.
The legacy will not disappear overnight, but will be progressively reduced, encapsulated, and managed until the business case allows for its complete disposal.