Banking on the power of data: The analytical approach to trust, performance and productivity

Intesa Sanpaolo promotes a data-driven culture with support from SAS^® analytics

As the digital age propels finance into new frontiers, it’s the mastery over data that distinguishes industry leaders from the followers. Analytics not only sharpens decision making but also fosters innovation, efficiency, productivity and an intimate understanding of all data. It is this data-centric approach that has enabled Italy’s Intesa Sanpaolo Group, one of the top banking groups in Europe, to grow its culture of analytics. Intesa Sanpaolo’s international presence further underscores data’s importance for navigating diverse markets and realizing potential in all the economies.

Massimo Modolin, Senior Director of the Management Planning and Control Department at Intesa Sanpaolo, is responsible for customer and contract management data oversight and its related methodologies. To understand how a data-driven culture and innovation generate value for Intesa Sanpaolo, we asked Modolin for some insights.

Could it be argued that a business’ success depends on the importance it places on data culture?

Modolin: I would say so. We have an immense source of data and information. Knowing this data, knowing where it is, how to mine it, how to use it, and making sure that it has value and can be accessed and available as knowledge that is useful to the business is an engaging challenge that, I can say with some pride, has long been met in our company on many levels.

In the Management Planning and Control Department, for example, there are about 250 people with different skills, from the more technical to the more functional and analytical. We are united by a data culture that is ingrained in the way we work. It is the same for our colleagues in IT and the departments and business functions that ‘enjoy’ data in different ways through the knowledge they generate.

In terms of my department’s structure, I can say that a data-driven culture is now embedded in our DNA.

How do you promote a data-driven culture? What are the basic steps to building a data-driven company?

Modolin: Because data is an immense asset, it is critically important to build its foundational pillars. This means paying the utmost attention to the nature and security of the data, a responsibility our IT colleagues have. But there are other pillars, such as the methodologies for using the data: governance, quality, how information is constructed and how knowledge is represented.

When data is correct, solid, reliable and accessible, a data-driven culture extends almost naturally into the company. Of course, said like that, it all sounds easy. The effort to get to such a high-value situation is not trivial. It demands resources in terms of skills and investment and assets in terms of tools, methodologies and technologies.

What role does innovation play in cultural change? What are you doing to introduce innovation and make it part of the ordinary process?

Modolin: A few years ago, we embarked on a journey of innovation, both within my department and the overarching Group. We established a single, centralized system for identifying and collecting data and information so we can obtain detailed data analysis without always having to call on IT. At the level of ‘ordinary processes,’ this frees time and resources in general and empowers the various business functions to become promoters of innovation.

In my department, for example, the ability to consult data autonomously – change parameters and construct information – without the constraints of predefined and preset reporting allows us to provide answers more quickly to the business and proactively suggest further analysis and reporting.

As a result, experimentation, such as the analysis we’ve devoted to use cases in artificial intelligence, has also entered our ordinary process. This is how we are bringing innovation to governance and business – always offering new ways to access insights and knowledge that are increasingly effective and valuable for business decisions.

What best practices have you adopted for a virtuous data analysis process?

Modolin: Sharing ideas, even in a somewhat unstructured way, is an indispensable condition for continuous improvement. From the more specific point of view of data analysis, best practices range from the care of the data to the widespread use of intelligence systems, from business intelligence to the most advanced analytics to artificial intelligence. I would add: Always have that air of curiosity that pushes you to want to know more, to understand better and to build new knowledge to share.

How does SAS analytics help you and your department derive information that is useful for decision making?

Modolin: In our role, technology is vitally important, both for those with advanced technical skills and for nontechnical users, as I am. I start from the assumption that it is impossible to analyze the enormous amount of data we have without a powerful, robust and reliable tool. Without a sophisticated platform designed specifically to help people extract value from data, it would be unrealistic to think that we could make decisions supported by objective and correct evidence.

Having said that, I am not a technical person. However, in a short time, I was able to use all the SAS functionality without taking a training course. Data visualization and SAS’ intuitive interface played a key role. I am the concrete example of the fact that if a technology is well designed, even though it’s complex in its DNA, it is easily accessible to anyone. And it is from this accessibility that it derives its maximum effectiveness for the business.

How do performance, productivity and trust translate internally?

Modolin: Performance and productivity have become synonymous with flexibility, a milestone we’ve achieved through our implementation of SAS analytics. SAS is not just a powerhouse of capabilities; it is also easy to use. The flexibility and agility we’ve gained through SAS have increased our productivity and made us advocates of innovation. And trust in our elaborations stems also from the dependability of the results of SAS analytics. This dependability has made data analysis critical to our activities and has strengthened the decision processes and strategies.