29th (EC)2 Conference on
"Big Data Econometrics with Applications"
Opening remarks by Salvatore Rossi
Senior Deputy Governor of the Bank of Italy
and President of the Institute for the Supervision of Insurance (IVASS)

It is my great pleasure to open this conference and to welcome all the speakers
and participants. I thank the organizers for designing such a broad and topical
programme.
With the increasing digitalization of the economy, data has become central in all
the social sciences, and economics is no exception. In fact, some have talked about
data being the new oil of today's world. Econometrics and statistics are therefore
becoming increasingly dependent on the availability of huge and heterogeneous
datasets.
Only few years ago, the econometric profession was rather cautious about Big
Data. Classical econometrics is based on theory and so relies on approaches that
differ significantly from those of Big Data analytics. Econometricians have been
taught for decades to start with a theory and then use data to prove or disprove it.
Big Data and machine learning work in the opposite way: they allow one to
look for patterns simply by processing huge amounts of data, regardless of possible
underlying models. It's important to note that most econometricians have expressed
concern about the reliability and representativeness of such vast datasets.
However, it's becoming evident that Big Data could disrupt traditional
econometrics. Data collection from social media has produced unprecedentedly
large and complex, though unstructured, datasets on economic agents' behaviour
and interactions, and these are proving to be a goldmine of economic information.
We have been working with data analysis for many years, but it is now time to
adapt our computational approaches to the new context.
The Bank of Italy, because of its multiple functions, follows the evolution of
Big Data very attentively. We will discuss this topic in a workshop organized with
the Bank of International Settlements next 15 January here in Rome.
In the last few years we have progressed along our learning curve. We have
combined skills in economics, econometrics, statistics and computer science to
deal with the increasing volume, variety and velocity of data, which we have then
used to estimate unemployment and inflation, to improve our economic forecasts,
and to measure consumer and business sentiment.
We, like all central banks, must also be ready to cope with the increasing
public demand for access to granular data. As a data producer, the Bank of Italy has
always strived to make its statistics available to the widest possible audience. We
already share some data with researchers and other institutions, while protecting
confidentiality. We have also started to design a Research Data Centre that will
provide a safe haven for processing different kinds of microdata.
The number of possible applications of Big Data for central banks is huge, but
some are critical.
The financial services sector handles sensitive information about individuals
and firms. More data available in digital format makes life easier for analysts but
increases exposure to security breaches.
As more services go online, data ubiquity, and hence data security, are proving
to be a major challenge for both private companies and central banks. Financial
operators are able to gather massive amounts of data about customers and visitors,
which are then analysed to generate insights into buying behaviour. Some of this
data is personal, and deserves to be protected against inappropriate use. That is a
goal that the whole of society must pursue.
Another important aspect of these innovative technologies is financial
stability. New entries have arrived in the landscape of financial services; Fintech
is a portmanteau word meaning any application of digital technologies to finance.
Under this label we can include both giants of the digital world wanting to enter
the financial market and tiny start-ups whose ambition is to erode the market power
of the incumbents.
All this is beneficial to competition and productivity in the financial industry,
provided that the new entrants are properly supervised. Technology can help to
innovate financial products and services currently provided by the traditional industry
to the benefit of consumers. However, given all the well-known interconnections
between operators in the market, the repercussions of technological innovation on
the system's stability are not clear. Public institutions like central banks and other
financial supervisory authorities should examine the matter carefully.
The Bank of Italy has created an internal multidisciplinary team on Big Data,
Machine Learning and Artificial Intelligence. The team includes economists,
statisticians and computer scientists from different departments, working in close
cooperation with the Information Technology Department. IVASS, the insurance
supervisory authority working under the umbrella of the Bank of Italy, has opened
a regulatory sandbox for some aspects of Fintech/Insurtech.
To conclude, I am confident this conference will be an important occasion to
review the most recent findings on Big Data econometrics and its application to
national institutions, in particular central banks, and international organizations.
Bringing together researchers from central banks and academia, as we do on this
occasion, can provide a broad variety of contributions and perspectives. I am sure
we will have two productive and interesting days.
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