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Digitization of banks: how are financial institutions evolving?

Banks are evolving: new technologies and new business models have been implemented, but there are some problems left to overcome

How are financial institutions evolving to face the advent of the digital economy? What is their level of digital transformation? What technologies are they adopting? These are some of the questions asked in the interview with:

Alberto Firpo, CEO & Co-Founder of Agile Lab 


Barbara Pavan, Head of Data Preparation & Automated Testing, Retail Digital Transformation of Intesa Sanpaolo 

Over the years, we have developed a strong experience with the Digital Transformation in the Banking sector.

Contact us today if you’d like to learn how to manage and generate real value from your data.


Digital transformation is key in all industries. Are Italian banks going digital?

Italian banks are moving towards digitization, but it is a long-term path. We are moving, for example, in the direction of microservice architectures, which will facilitate integration with external data and FinTechs, as well as projects involving data feeds in "near real time", thus enabling asynchronous processes like the Amazon model, and the use of mobile banking apps has increased, also because of the pandemic. In general, in the Analytics field, the sector is still very focused on fact finding rather than on forward looking. That is using Analytics to understand data and not yet to derive value from it with prescriptive or predictive use, for example through optimization. As for Artificial Intelligence, we are moving from Robotic Process Automation to Intelligent Automation, but we are not yet exploring the opportunities provided by Social Robotics. The real keystone for the adoption of digital solutions, however, will be represented by the ability to understand that digitization is not a question of technology, but of people and processes. To effectively become an “Intelligent Enterprise” it is necessary to shift attention from pure cost saving to the optimization of investments, working to acquire and develop the necessary skills for the future of banks, reviewing processes and organizational structures. I believe this will be the biggest challenge.

What is real time banking and what advantages does it bring?

Real time Banking is the ability to share information from a specific business domain of the bank to all consumers within the organization or for specific processes relating to contact with the customer, the proposition of products where an immediate response constitutes a competitive advantage. This information can simply be “replicated” by a legacy subsystem, without particular reprocessing, but made available in a scalable manner for many consumers, or it can be subject to more or less complex processing such as a credit scoring updated to the latest event concerning a specific customer. The advantages are many: Sharing information within the organization in real-time in a less expensive and more scalable way, for processes that require greater decision-making speed; Overcoming the limits imposed by the legacy system, modernizing it but maintaining it, thus avoiding an expensive and difficult to manage phase out; Speeding up the decision-making process, also for use cases directly connected to the market, such as in the case of a scoring calculated in near real time that allows you to automatically and immediately “decide” whether or not to disburse a loan to a certain cluster of customers, greatly shortening the process lead time, thus benefitting both customers and the bank itself

Are there limits to the adoption of real time banking?

Real time Banking, or more generally the possibility of providing and analyzing data in real-time, is just one of the components that make up a broader framework of transformation. From this point of view, the limits are only organizational and they can only be overcome by leaving the “comfort zone” and overcoming the inevitable inertia that more or less every organization possesses.

And more generally, is there any obstacle that slows down the digitalization in Italian banks?

First of all, I would call them “challenges”, rather than “obstacles”: it is important to have the right point of view. As for the ambition to become data-driven organizations (data in the digital age has been defined as “the new oil”), Italian banks are facing, some more than others, the challenge of monetizing the value of data. In particular, in terms of data management, they are now approaching issues with which banks in other realities, such as in the UK world, have already dealt with. There is therefore a need to define a company-wide data strategy. Another important challenge will be to attract and retain distinctive skills to be able to initiate the digital transformation. Last but not least - it will be necessary to work on the corporate culture: it is essential to develop a growth mindset, that is, a growth mentality in which mistakes and challenges are seen as opportunities and not a threat. This is an important issue, perhaps the most difficult to deal with because desire and motivation are not enough to achieve real change. It is a human factor: it was found that even when it comes to life or death, only 3 out of 7 patients (43%) change their habits. The status quo is powerful, especially in traditional organizations such as banks, but I believe we must strive to change ourselves and the organizations we work in. To quote the paradox of Martec's law, technology changes exponentially but organizations change logarithmically; it follows that management will have to choose ever more carefully what changes to implement and, in this process, the role of people is a key factor for success.

Is artificial intelligence coming to the world of banks?

Regardless of the definitions of “Artificial Intelligence” which I’d rather not dwell on, we have seen the use of machine learning or deep learning applied effectively in some processes, aimed at cost saving or at improving interaction with the customer, such as for fraud prediction, self-servicing channels (both voice and chatbot), KYC-KYB and more generally automated on-boarding, risk management and regulatory compliance, cybersecurity. Among the most interesting use cases, I would also mention some Fintechs that are very successful in offering alternative services to banking, especially in the context of wealth management and asset allocation. Comparing the performance of an asset manager with that of a complex system of automated models, it turns out that the latter actually outperforms the former, also thanks to the ability to automatically manage the allocation of an investment through complex interactions between multiple "competing models" "and very large historical data windows. These are all capabilities that on average are very difficult to implement for an asset manager using “traditional” tools.

What other technologies, innovations or paradigms will have a significant impact?

Technologies are always a tool to serve the business and not vice versa. So from this point of view everything is useful if it can help a bank embrace the transformation I previously explained: both for creating new revenue streams and in terms of process and organization. If we think of an "enterprise" type organization, therefore with many interactions between stakeholders, data consumers and data producers in a multi-business unit and multi country environment (typical characteristics of some "big" banks), democratization, access and the reuse of data are more important than wanting to apply “Artificial Intelligence” at all costs to a process that may not necessarily bring value. In this instance, one of the paradigms that can have a significant impact is Data Mesh, a trend that is emerging on a global scale and which applies to Data Management concepts such as Domain Driven Design and Decentralization of Ownership, while evolving data management from a centralized platform to a distributed ecosystem of “Data Products”. And this is a much more important concept than one might believe: thinking about data as a product disrupts the organization, but opens up very interesting scenarios that go exactly in the direction of helping the “fast” creation process of product bundles, which serves the business. Data Mesh is first of all organization and people, and only then architecture, and is seen by many as a possible solution to help speed up and scale business initiatives and at the same time solve organizational inefficiencies originating from the centralized organizational pattern associated with more traditional “monolithic” Data Lakes (or Data Warehouses), a pattern originating from a “ purely technological” approach that does not take into consideration the real value creation process.

What are the risks for financial institutions not embracing digital transformation?

In my view, the risks are not coming so much from international outsiders in direct competition on the Italian market, but rather from Fintech players, for reasons that everyone knows, and above all from Tech giants that can slowly indirectly erode value from a bank’s customers (“unbundling” the bank), by offering financial services associated with the purchase of other goods sold on other channels (for example, the numerous services that Amazon offers actually take value away from a bank: Amazon Pay, Amazon Go, Amazon Cash, Amazon Protect, Amazon Allowance, Amazon Lending and so forth). This happens because a Tech Giant is an extremely efficient software machine, but not only that: it is also able to quickly evolve and create new “product offerings” by following the behavior and needs of the customers with whom it establishes a recurring relationship. And precisely this is the true meaning of “digital transformation”: digital transformation means becoming a software company or, even better, a data-driven company, to be able to evolve and manage change in a resilient way, first of all trying to protect and monetize to the fullest the existing relationship with one’s customers (B2C or B2B), by positioning product “bundles" consisting of third-party services, proper “traditional” services and even one’s own software or digital assets, also creating new more “agile” and less subject to regulatory restrictions assets to bring to market. For a bank, this does not necessarily imply selling consumer goods (eg televisions !!) to its customers, but instead it means strengthening the trust relationship already existing with its customers, trying to satisfy a specific need or seize an opportunity.

Will the transformation into digital banks lead to the closure of local branches?

The digital transformation requires new skills and a review of both processes and ways of working, therefore it will certainly lead to the need to create new professional figures within banks. Artificial Intelligence systems, for example, should provide for certification not only by the business sponsor, but also by an impartial body, so that they comply to fair social rules. In addition, they require continuous monitoring so that they do not deviate from the objectives, as they learn from the data. In general, technology must be seen as something that enhances human abilities, freeing people from repetitive and more ‘mechanical’ tasks, and allowing them instead rot focus on those that require discernment skills and the so-called "human touch”, still highly appreciated by the clientele. It is therefore essential to implement upskilling and reskilling programs to support the change. Furthermore, to ensure that training is effective “at scale”, it is important to start from the analysis of existing HR processes: technology and people are a powerful combination to transform the way of doing business.

How will banks' business models evolve?

Banks will have to exploit the complementarities between the legacy activities of the physical world (e.g. direct contact with customers) and digital activities. We must expect multiple changes in customers, competitors, regulation, value proposition, profit formulas, partnerships. On the latter point, for example, as also shown by the market trends of the tech world in 2020, fintechs have become suppliers of innovative solutions that banks buy and integrate into their systems, reducing time to market. The right approach, however, is not that of starting from the technology to define the useful business model for serving the customer. Rather, it is necessary to start with the changes in the customer's needs: from here we move to identify how to create value and what organizational factors are needed to build the business model, generating, with a bottom up approach, a “digital core” that permeates the organization and allows banks to provide their customers not only with products, but also solutions.

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