Risk manager: Bank of Italy

Since the outbreak of the Covid-19 pandemic in early 2020, many central banks around the world have significantly inflated their balance sheets, with large-scale asset purchases being used to inject monetary stimulus.

Measured using conventional rating methodologies, it might be considered that financial risk has grown at the same rate as balance sheets, since rating agencies tend to look at the average probability of default of issuers over time.

Credit assessment

An alternative approach, which the Bank of Italy has adopted, is to compute empirical estimates based on market prices. Antonio Scalia, head of the financial risk management directorate at the bank, argues that this provides a more nuanced view of risk that rating agencies do not adequately capture.

“This is because central banks are not like other players in the financial markets. They are not private institutions,” Scalia says. “If a central bank intervenes heavily, it may change the perception of risk for private players, and the amount of risk embedded in market prices may thus become much smaller than the risk measure derived from agency ratings, which have a through-the-cycle orientation and are largely backward-looking.”

This market risk-implied methodology is intended to complement Bank of Italy’s existing in-house credit assessment system (Icas), which has been in place since 2013. This approach has become much more significant as the central bank’s balance sheet has swelled.

Between 2019 and 2021, the Bank of Italy’s balance sheet nearly doubled, rising from €960 billion ($1 billion) to €1,538 billion (although the two years that followed saw it shrinking again to €1,253 in 2023).

“If we relied just on the ratings issued by rating agencies, we would have seen financial risk grow by an amount almost proportional to the overall exposure from monetary policy operations,” says Scalia. “We put forward a complementary risk measure based on market prices, which better reflects the risk perception of market players at any point in time.”

In 2024, the central bank sought to enhance the transparency and accountability of its rating methodology by publishing a paper on the statistical model.

The model integrates machine learning techniques within a traditional logistic approach. Every month the model produces an estimate of the probability of default with a fully automated procedure. The discriminatory power improves as the size of the company increases, thus ensuring a proper evaluation of the largest exposures in monetary policy operations.

“Icas plays a crucial role in monetary policy implementation, by allowing all counterparties to pledge credit claims to non-financial firms. The Icas contribution to the transmission of monetary policy is even more important during episodes of market tension, by supporting the overall availability of collateral. Icas is also employed in case of bank-level liquidity strains, when it fosters the operational readiness to provide emergency liquidity assistance without compromising on sound risk management,” says Scalia.

Scalia adds that the Icas rating process is based on a two-stage procedure that “combines a statistical model with an expert assessment, performed by two analysts and possibly the rating committee, to obtain the final rating of the firm”.

This is not to say that the Bank of Italy ignores rating agencies altogether. On the contrary, Scalia says it is crucial to consider these two components of credit risk assessment in tandem.

“The two assessments take a different perspective. Rating agencies take a medium-term orientation and move fairly slowly. Market implied ratings take a much more responsive view of risk, which can immediately assess the impact of significant changes in a central bank’s financial exposure,” Scalia says.

Corporate mapping

The Bank of Italy has also adopted the use of artificial intelligence to map out the ownership network of businesses under the central bank’s supervision.

Developed with the University of Oxford and TU Wien, the central bank’s logic AI model harnesses ‘automated reasoning’ to uncover individual and/or corporate relationships. It was rolled out in October 2023 and can answer questions, such as why an individual owns a certain share of an organisation. It can also perform ‘what if’ analysis, for example, how changes in an ownership structure could affect other companies. A member of the Bank of Italy’s supervision team said the tool has “made the difference” in helping the supervisor to understand the consequences of an acquisition and is helpful in “administration” and “authorisation” proceedings.

Longer-term sustainability

The Bank of Italy’s risk management credentials are further boosted by its increasing focus on the sustainability of its investments.

In 2024, the Italian central bank rolled out a new integrated financial risk management framework for its investments, integrating risks relating to environment, social and governance (ESG) factors alongside economic and financial risks. This has brought sustainability considerations, previously applied only to its equity portfolio, up to the strategic level.

Regarding the selection of issuers and securities, the new framework goes beyond negative screening and the best-in-class approaches, which rely solely on historical data, such as ESG scores and past or current emissions. Instead, portfolio management incorporates a new internally defined, forward-looking score that captures each company’s commitment to reducing emissions, through an assessment of the ambition, credibility and timeline of the targets.

“We are very anxious to make sure meaningful progress is made against commitments, which is why we have started a dialogue with a selected number of high-emitting companies in our portfolio,” says Marco Fanari, head of equity and corporate risk. “The idea is that these proprietary, forward-looking metrics will be amended in the coming years, so as to more accurately reflect the actual efforts companies are making.”

While this strategy may lead to a slower decarbonisation of the central bank’s portfolio in the short term compared with divesting altogether from high-carbon sectors, Fanari argues that it is better suited to support an orderly climate transition.

“Indeed, excluding companies only on the basis of their historical level of emissions could penalise those that are most active towards climate transition, but whose emissions may be among the highest,” Fanari says. “The initiative has allowed the bank’s risk management function to conduct an independent assessment of decarbonisation trajectories, complementing those provided by external suppliers and firms’ proprietary models.”

Fanari says it is important for the bank to have a holistic view of risk, and integrating ESG factors is an important component of this. “The idea is to put all of the risk together, consider the optimal composition of our investments and, from this, form a constructive view of the financial health of our institution,” says Fanari.

The Central Banking Awards 2025 were written by Christopher Jeffery, Daniel Hinge, Daniel Blackburn, Joasia Popowicz, Riley Steward, Jimmy Choi, Levente Koroes, Thomas Chow and Blake Evans-Pritchard.