Banking 3.0 and Insurance 3.0: Artificial Intelligence at the Heart of the Transformation of the Italian Financial System

Milan, November 11, 2026 – The Italian financial sector is focusing on Banking 3.0 and Insurance 3.0, two new service models in which artificial intelligence is no longer merely a tool for digitization but has become a driving force behind the transformation of customer relationships, work organization, and the distribution of financial and insurance products.

This is what emerges from research conducted by Cetif, the Research Center of theUniversità Cattolica del Sacro Cuore and presented at the Cetif Summit . The figures and trends were gathered by the research hubs dedicated to Digital Banking and Digital Insurance & Distribution, working groups that analyze the evolution of service models and the impact of emerging technologies. These studies also suggest that institutions are already addressing issues related to Industry 4.0, where autonomous agents will be increasingly integrated into operational processes—and not just those related to customer service.

Banking 3.0: From Digital Banking to Smart Banking
Banking 3.0 represents the transition from a bank that offers services through digital channels to a model capable of understanding the customer’s context, anticipating their needs, and proposing personalized solutions.

This evolution is made possible by the convergence of machine learning, generative AI, agent-based AI, cloud computing, advanced data analytics, and automation. These are hot topics and high-performance technologies whose adoption is accelerating rapidly, creating a sense of urgency that is essential for moving faster—otherwise, there is a risk of being left behind.
The applications span various areas of the banking value chain.

In customer relations, traditional chatbots are evolving into autonomous agents capable of performing actions that were previously unimaginable, such as interpreting complex requests and supporting increasingly complex operations. Currently, 11% of chatbots use Generative AI, and 22% of organizations are experimenting with it. In terms of personalizing offerings, data analysis enables the development of services that are increasingly aligned with customer needs and behaviors. Generative AI is becoming firmly established in numerous processes related to marketing and sales but is beginning to extend into typical banking processes. The agent-based sector, however, is still lagging behind, with the first experimental use cases appearing in the areas of marketing plan development and product portfolio management.

In credit and risk management, machine learning supports data analysis and
decision-making processes, while in fraud prevention, it helps identify
anomalous behavior and suspicious transactions.

However, the study Cetif highlights that the adoption of new technologies must be accompanied
by the development of skills and the evolution of organizational models, especially as
intelligent systems gain greater operational autonomy.

Insurance 3.0: Artificial Intelligence Transforms Protection and Advisory Services
In the insurance sector, a survey Cetif shows that 55% of agency staff’s time
is spent on administrative and managerial tasks, compared to 30% dedicated to
sales activities. This figure highlights the potential of artificial intelligence to free up resources from
that can then be allocated to consulting and customer relations. Essentially, many of these routine processes
will soon be managed by agents.

Cetif 's Digital Insurance & Distribution Hub highlights how AI can be applied across the entire
insurance value chain, from risk assessment to distribution, from policy management
to after-sales support.

One of the most significant areas is support for distribution networks. According to data from Cetif, over
50% of national insurance agencies consist of a single agent
supported by fewer than three subagents. In these agencies, auto insurance products account for an average of over
65% of the portfolio.

The presence of small-scale distribution networks and the burden of administrative tasks
make it particularly important to introduce tools capable of simplifying the
day-to-day work of intermediaries.

Generative artificial intelligence can assist agents in preparing quotes,
analyzing contractual documentation, managing communications, and
identifying clients' protection needs.

In particular, intelligent assistants can make policy clauses, exclusions, and
policy conditions easier to understand, thereby facilitating the relationship between the insurance company, the intermediary, and the policyholder.
From risk assessment to claims management: where AI is applied in insurance
The applications of artificial intelligence in the insurance sector are not limited to the
commercial relationship.

In underwriting and risk assessment, intelligent systems can analyze
structured and unstructured information, summarize complex documents, and support
specialists in evaluating coverage.

In claims management, AI can help classify claims, analyze
documentation, support expert assessments, and monitor the status of cases, thereby facilitating
faster processes and a better experience for the policyholder.

In marketing and distribution, predictive tools make it possible to identify potential
insurance needs, flag gaps in coverage, and develop more personalized proposals.
The vision outlined by Cetif is that of a model in which insurance coverage can
evolve in response to changes in the customer’s life, shifting from a relationship
primarily focused on the time of enrollment to an ongoing interaction.

The goal is not to replace the intermediary, but to enhance their capabilities through
decision-support tools, reducing the burden of repetitive tasks and improving the quality of
consulting services.

Customers are changing faster than financial institutions
Another factor driving this transformation is consumer behavior.
The rise of generative artificial intelligence is changing the way people search for
information, compare products, and prepare to make financial and insurance decisions.

Customers can use conversational tools to understand the features and terms of
products, evaluate alternatives, and come prepared for a discussion with an advisor by already having access to preliminary information and
analyses.

This evolution poses new challenges for financial institutions, which are called upon to offer digital experiences
that are simple, personalized, and consistent with the expectations of an increasingly well-informed clientele.
For banks and insurance companies, artificial intelligence therefore represents an opportunity not only to
improve efficiency, but also to rethink the role of digital channels and human advice.
Federico Rajola: “The real transformation isn’t technological; it concerns the service model”
“Banking 3.0 and Insurance 3.0 represent a profound evolution of the financial system, in
which artificial intelligence becomes a central element of the relationship between institutions and customers,”
comments Federico Rajola, Director Cetif. - Our research shows that AI is already
transforming numerous banking and insurance processes, from risk management to distribution,
and from customer support to advisory services.

But the most significant change concerns the ability to transition
from predominantly reactive service models to systems capable of anticipating customer needs and
offering increasingly personalized responses. The data also highlight how much work remains to be done:
technology is advancing rapidly, while organizations, skills, and governance models have yet to evolve.

"The real challenge for Italian financial institutions will be to transform the potential of
artificial intelligence into tangible value for customers, professionals, and businesses, while keeping trust,
accountability, and the quality of the relationship at the center."

The challenge for the coming years: integrating technology, expertise, and governance
The path toward Banking 3.0 and Insurance 3.0 will depend not only on the availability of
increasingly advanced technologies, but above all on the ability of financial institutions to integrate them into their
processes and organizational models.

Research at Cetif highlights how the convergence of traditional AI, generative AI
and agent-based systems is opening up new possibilities for automation and personalization, but at the same time requires
new safeguards, professional expertise, and data management capabilities
.

The vision is of a financial system in which artificial intelligence does not replace
the value of human relationships, but helps make them more informed, timely, and
personalized.

A change that could gradually redefine the role of banks,
insurance companies, and distribution networks, placing the quality of the customer experience at the center of the new
service models.