Advanced simulations and ‘stress-proof’ models help digital bank successfully navigate uncertain scenarios
Streamlined scenario-based analysis helps direct strategic planning.
Rapid access to powerful risk analytics
Banca Progetto relies on predictive analytics and a cloud-first approach to mitigate risk, better serve clients and plan for the future
A number of new players are emerging on the global banking scene. They are not just FinTech startups, but also real credit institutions, which have two main features:
- A marked vocation toward the extensive use of technologies to enable all banking processes, whatever they may be.
- A strong nature of specialization in very specific products and services.
Banca Progetto is one of these players. It formed in 2015, following the reorganization of Banca Popolare Lecchese by Oaktree Capital Management. With offices in Milan and Rome, Banca Progetto operates in the consumer credit and corporate credit market primarily through digital channels and an intensive commercial network of agents and credit brokers present throughout Italy, without branches.
The bank has a business model that is as simple as it is effective: Banca Progetto collects liquidity mainly through deposit accounts in Italy and other European countries and provides only two credit services: medium- and long-term loans assisted by a public guarantee fund to small and midsize businesses and salary- and pension-backed personal loans to individuals. A choice that has positive impact either in terms of risk management implications or on the bank’s capital health.
But what really characterizes Banca Progetto is its continuous investment in technological innovation. Banca Progetto is the first Italian bank that has completely outsourced its IT infrastructure to a public cloud, Amazon Web Services (AWS), passing all supervisory controls and obtaining the green light from the control and guarantee authorities. This choice allows the bank to be agile and flexible in its day-to-day operations and to concentrate on core activities, including risk management – which, again, relies on the use of advanced technologies such as SAS’ scenario impact simulator.
SAS spoke with Roberto Russo, Chief Risk Officer of Banca Progetto, to learn more.
It is more important than ever to modify the approach to risk management by focusing on advanced simulations and modeling of reality, moving away from the deterministic approach toward more sophisticated and effective predictive analytics. Roberto Russo Chief Risk Officer Banca Progetto
What sets Banca Progetto apart in the Italian financial landscape?
The high rate of technological innovation is one of the main features. We are the first Italian bank to have chosen – and obtained – the option of moving all our IT infrastructure to a public cloud environment. By choosing AWS cloud technology as the foundation of our innovation, we can better cater to our customers’ constantly evolving needs.
This choice allows us unlimited operational capacity in terms of volume, flexibility and availability of state-of-the-art technology and substantial control over operations. (Governance and responsibility for applications and data remain entirely in the hands of the bank.) Not having to manage the hardware is an element of great agility for Banca Progetto, also in economic terms.
Aligning with AWS becomes an important risk mitigation factor. This is due to the guarantees on service levels and also to the fact that AWS is a player that has necessarily invested in the construction of data centers in Europe. This is a mandatory step to comply with all the strict European regulations and offer high guarantees to customers. For example, we have a redundant business continuity system on three sites – or regions – one of which is in Italy, the other two in the EU.
The process was not simple. Bank of Italy, our supervisory authority, had a rigorous, firm and very thorough investigation into all the aspects of risk analysis. We showed that we were aware of the “world we were heading toward,” and how to govern it.
Since the onset of the COVID-19 pandemic, the banking sector has faced unprecedented challenges. The decisions that banks and lenders make may determine if they survive the crisis and how strongly they can recover. With economic conditions outside of everyday norms, making business decisions based on historical trends is insufficient. In your experience, how will risk management change after this crisis? What has already changed?
In my opinion, instability, volatility and uncertainty will increasingly be the norm. The only thing that will be certain is change. In such contexts, it is more important than ever to modify the approach to risk management by focusing on advanced simulations and modeling of reality, moving away from the deterministic approach toward more sophisticated and effective predictive analytics.
We have to start from the assumption that there will never be any model that can predict exactly what will happen in reality; however, navigating through scenarios of uncertainty requires pragmatic but innovative approaches. In this sense, the very role of risk management must be redesigned, moving from a function of mere control to a function of decision making to support the business.
In our case, we have evolved the traditional approach to risk management based on deterministic models. We have realized that, both for short-term decisions and for those to be assessed with a more prospective view in the medium to long term, it is necessary to equip ourselves with advanced analytics. We are already carrying out advanced simulations to analyze possible scenarios up to 2022. Having such sophisticated and effective risk management tools at our disposal also is a plus for the business in cultivating a constant long-term vision.
What are the reasons that led you choose SAS’ scenario impact simulator?
SAS has been a leader in advanced analytics and risk management for years and has a strong reputation in finance. I've really appreciated SAS’ vision and ability to create a tool suited to the times we live in, in the right timeframe. SAS proved to be fast in proposing technological solutions that, on the one hand, take away the burden of programming, building and fine-tuning the necessary tools from the operators, and on the other hand offer very advanced and effective functionalities with respect to the objectives of those who use the tools themselves (i.e., understanding where to go, how and with what risks).
From a business point of view, we chose SAS’ scenario impact simulator because it allows us to understand what decisions to take with the greatest possible awareness. It’s a very sophisticated and rich platform, and one of the advantages I highlight is the support of the SAS people who help us – through training and recommendations – to understand how we can make the most out of the technology.
Today we mainly use it to check the sustainability of operational and strategic business plans, simulating different future scenarios and then analyzing all impacts in these possible scenarios, from the consequences in terms of risk to the analysis of income, assets and liquidity.
We will also be using it shortly for capital planning, the document that will be used by shareholders to determine what further investments to make to support the bank’s development. The better we are at simulating and understanding the impact of risk on our prospective portfolio, the more efficiently we will use capital.
Banca Progetto – Facts & Figures
Having advanced predictive models and “stress-proof” simulations is proving to be crucial in managing the impacts of such a volatile economy. Moving in this direction, does it still make sense to talk about stress tests?
Stress tests, in my view, are crucial components of simulations and scenario analysis. They allow us to understand how predictive models we use are “stress-proof” in contexts of high volatility and uncertainty. Stress tests are considered key elements for sound and prudent bank management, and this will increasingly be the case as we move into a world where informed decisions will have to be made under conditions of limited rationality.
They are, and will continue to be, increasingly important in the future, especially if they are part of a much broader approach to analysis which, as I have mentioned, must have the capacity for forward-looking vision as its true differentiating value.
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